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1 I. INTRODUCTION 2 A. An Integrative Strategy 2 B. A State Space Model of the Brain-Mind 3 C. Caveat Lector 4 II. THE PHENOMENOLOGY AND PSYCHOPHYSIOLOGY OF WAKING, SLEEPING AND DREAMING 5 DREAMING and the BRAIN: Toward a Cognitive Neuroscience of Conscious States (1 of 222) [1/6/2000 2:48:02 PM] A. Early findings of distinct differences between REM and NREM mentation 6 B. Overview of the NREM-REM Sleep Mentation Controversy 12 1. REM Sleep Dreaming is not Qualitatively Unique 13 2. The Relationship Between Dream Features and Dream Report Length 17 C. Methodological Considerations in the Study of Dreaming 21 1. The Reduction of Psychological States to Narrative Reports 21 2. The Sleep Laboratory Environment 26 3. The Question of "Similarity" and "Difference" 29 4. The Source and Fate of Dream Memory 33 5. Type I vs. Type II Statistical Analyses 39 6. The Need for New Approaches 40 III. THE COGNITIVE NEUROSCIENCE OF WAKING, SLEEPING AN...
Schematic representation of the REM sleep generation process. A distributed network involves cells at many brain levels (left). The network is represented as comprising three neuronal systems (center) that mediate REM sleep electrographic phenomena (right). Postulated inhibitory connections are shown as solid circles; postulated excitatory connections as open circles; and cholinergic pontine nuclei are shown as open circles with darkened boundaries. It should be noted that the actual synaptic signs of many of the aminergic and reticular pathways remain to be demonstrated, and, in many cases, the neuronal architecture is known to be far more complex than indicated here (e.g., contributions of hypothalamic and basal forebrain systems). During REM, additive facilitatory effects on pontine REM-on cells are postulated to occur via disinhibition (resulting from the marked reduction in firing rate by aminergic neurons at REM sleep onset) and through excitation (resulting from mutually excitatory cholinergic-noncholinergic cell interactions within the pontine tegmentum). The net result is strong tonic and phasic activation of reticular and sensorimotor neurons in REM sleep. REM sleep phenomena are postulated to be mediated as follows: EEG desynchronization results from a net tonic increase in reticular, basal forebrain, thalamocortical, and cortical neuronal firing rates. PGO waves are the result of tonic disinhibition and phasic excitation of burst cells in the lateral pontomesencephalic tegmentum. Rapid eye movements are the consequence of phasic firing by reticular and vestibular cells; the latter (not shown) directly excite oculomotor neurons. Muscular atonia is the consequence of tonic postsynaptic inhibition of spinal anterior horn cells by the pontomedullary reticular formation. Muscle twitches occur when excitation by reticular and pyramidal tract motorneurons phasically overcomes the tonic inhibition of the anterior horn cells. Abbreviations: RN, raphe nuclei; LC, locus coeruleus; P, peribrachial region; PPT, pedunculopontine tegmental nucleus; LDT, laterodorsal tegmental nucleus; mPRF, medial pontine reticular formation (e.g., gigantocellular tegmental field, parvocellular tegmental field); RAS, midbrain reticular activating system; BIRF, bulbospinal inhibitory reticular formation (e.g., gigantocellular tegmental field, parvocellular tegmental field, magnocellular tegmental field); TC, thalamocortical; CT, cortical; PT cell, pyramidal cell; III, oculomotor; IV, trochlear; V, trigmenial motor nuclei; AHC, anterior horn cell. (Modified from Hobson et al. 1986.)
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1. Introduction
Dreaming is a universal human experience that offers a
unique view of consciousness and cognition. It has been
studied from the vantage points of philosophy (e.g., Flana-
gan 1997), psychiatry (e.g., Freud 1900), psychology (e.g.,
Foulkes 1985), artificial intelligence (e.g., Crick 1994),
neural network modeling (Antrobus 1991; 1993b; Fookson
& Antrobus 1992), psychophysiology (e.g., Dement &
Kleitman 1957b), neurobiology (e.g., Jouvet 1962) and even
clinical medicine (e.g., Mahowald & Schenck 1999; Ma-
howald et al. 1998; Schenck et al. 1993). Because of its
broad reach, dream research offers the possibility of bridg-
ing the gaps in these fields.
We strongly believe that advances in all these domains
make this a propitious time to review and further develop
these bridges. It is our goal in this target article to do so. We
will study dreams (defined in the American Heritage Dic-
tionary [1992] as “a series of images, ideas, emotions, and
sensations occurring involuntarily in the mind during cer-
tain stages of sleep”) and REM sleep, as well as the nu-
merous forms of wake-state and sleep-state mentation. We
will also review polysomnographically defined wake and
sleep states. Our analyses will be based on comparisons and
correlations among these various mental and physiological
1.1. An integrative strategy
Three major questions seem to us to be ripe for resolution
through constructive debate:
1. Are the similarities and differences in the conscious
experiences of waking, NREM, and REM sleep defined with
sufficient clarity that they can be measured objectively? If
so, do the measures establish clear-cut and major differ-
ences between the phenomenological experience of these
three physiological states?
2. Are the similarities and differences between the brain
Dreaming and the brain:
Toward a cognitive neuroscience
of conscious states
J. Allan Hobson, Edward F. Pace-Schott,
and Robert Stickgold
Laboratory of Neurophysiology, Department of Psychiatry, Harvard Medical
School, Massachusetts Mental Health Center, Boston, MA 02115
{allan_hobson; edward_schott; robert_stickgold}
Abstract: Sleep researchers in different disciplines disagree about how fully dreaming can be explained in terms of brain physiology.
Debate has focused on whether REM sleep dreaming is qualitatively different from nonREM (NREM) sleep and waking. A review of
psychophysiological studies shows clear quantitative differences between REM and NREM mentation and between REM and waking
mentation. Recent neuroimaging and neurophysiological studies also differentiate REM, NREM, and waking in features with phenom-
enological implications. Both evidence and theory suggest that there are isomorphisms between the phenomenology and the physiology
of dreams. We present a three-dimensional model with specific examples from normally and abnormally changing conscious states.
Keywords: consciousness, dreaming, neuroimaging, neuromodulation, NREM, phenomenology, qualia, REM, sleep
J. Allan Hobson is Professor of Psychiatry at Harvard
Medical School, Boston, MA, where he has been Direc-
tor of the Laboratory of Neurophysiology since 1967. He
is recipient of the 1990 Von Humbolt Prize for Science
from the German government and the 1998 Distin-
guished Scientist Award of the Sleep Research Society.
His major research interests are the neurophysiological
basis of the mind and behavior, sleep, and dreaming and
the history of neurology and psychiatry. He is author of
The dreaming brain (1988), Sleep (1998), Consciousness
(1998), Dreaming as delirium (1989) and, forthcoming
in 2001, The dream drug store and Out of its mind, Psy-
chiatry in crisis (with Jonathan Leonard).
Edward F. Pace-Schott is Instructor of Psychiatry at
Harvard Medical School, Boston, MA. His research in-
terests include the cognitive neuroscience of dreaming,
substance abuse, and sleep deprivation. He is also a psy-
Robert Stickgold is Assistant Professor of Psychia-
try at Harvard Medical School, Boston, MA. His back-
ground is in biochemistry and cellular neurophysiology.
He is a cognitive neuroscientist studying the roles of
sleep and dreaming in off-line memory reprocessing, in-
cluding off-line memory consolidation, transfer, inte-
gration, and erasure.
substrates of the states of waking, NREM, and REM sleep
defined with sufficient clarity that they can be measured
objectively? If so, do the measures establish clear-cut dif-
ferences between these states at the level of brain regions,
as well as at the cellular and molecular levels?
3. To the extent that affirmative answers can be given to
the two preceding questions, can a tentative integration of
the phenomenological and physiological data be made?
Can models account for the current results and suggest ex-
periments to clarify remaining issues?
Hoping to stimulate a useful debate, we will answer all
three of the preceding questions affirmatively, document-
ing our responses with appropriate data drawn from our
own work and from that of our colleagues. Referring to this
ample literature, one can now identify numerous opera-
tionally defined psychological and physiological parameters
with which to make such conscious state comparisons. In
developing our answers, we will advance the thesis that the
conscious states of waking, NREM, and REM sleep differ
in three clear and important ways which are measurable at
both the psychological and physiological levels. The three
parameters will become the axes of a state space model that
we introduce only briefly here but discuss in more detail in
concluding this article.
1.2. A state space model of the brain-mind
In essence, our view is that the brain-mind is a unified sys-
tem whose complex components dynamically interact so
as to produce a continuously changing state. As such, any
accurate characterization of the system must be multidi-
mensional and dynamic and must be integrated across the
neurobiological and psychological domains. Both neurobi-
ological and psychological probes of the system must there-
fore be designed, applied and interpreted so as to recognize
and clarify these features.
As a first step in that direction, we have created a three-di-
mensional state space model (AIM) that allows us to repre-
sent the system according to variables with referents in both
the neurobiological and psychological domains as is shown in
Figure 1. They are activation (A), information flow (I), and
mode of information processing (M). Each of these terms has
meaning both at the cognitive and neurobiological levels.
Roughly speaking, these dimensions are meant to capture
respectively: (1) the information processing capacity of the
system (activation); (2) the degree to which the information
processed comes from the outside world and is or is not re-
flected in behavior (information flow); and (3) the way in
which the information in the system is processed (mode).
The resulting state space model, while still necessarily
overly simplistic, is nonetheless a powerful tool for studies
of consciousness. It captures many aspects of the neurobi-
ological, cognitive, and psychological dynamics of wake-
sleep states, and is unique in several important respects that
we will discuss in light of the controversial conceptual and
empirical issues that have stymied the study of waking,
sleeping, and dreaming.
1.3. Caveat lector
In setting the stage for a full explication of our integrative
AIM model (sect. 4), we will review the evidence regarding
the differentiation of brain-mind states at the levels of psy-
chophysiology (sect. 2) and basic and clinical neuroscience
(sect. 3). Although these reviews are extensive, they do not
broach many of the fundamental questions of sleep re-
search. For example, we do not consider the biological
functions of REM sleep as we do elsewhere (Hobson
1988a) nor do we address the equally interesting question
of how psychological and cognitive factors impinge upon
sleep neurobiology, a subject which has been the focus of
our most recent work (Stickgold et al. 1998a; 1999a; 2000a;
Xie et al. 1996). As has often been shown, cognitive activity
affects sleep as well as vice versa (e.g., Smith & Lapp 1991)
reflecting, certainly, a reciprocal effect of psychological fac-
tors and their neural substrates. Additionally, we sidestep
entirely the intriguing but difficult issue of whether dream-
ing itself, as a conscious experience, has a psychological
function over and above the postulated benefits of sleep to
homeostasis and heteroplasticity (Hobson 1988a). Finally,
it is important to note that we deal here exclusively with
what Chalmers (1995b) has termed the “easy problem” of
consciousness, that is, the mechanisms of the cognitive
components of consciousness, rather than the “hard prob-
lem” of how consciousness itself could arise from a neural
system (see, e.g., Tononi & Edelman 1998; Woolf 1997).
2. The phenomenology and psychophysiology
of waking, sleeping, and dreaming
In this section we discuss the evidence which has been gath-
ered over the past 40 years in an effort to define the con-
scious states of waking, sleeping, and dreaming and to mea-
sure their formal features quantitatively. With respect to
the first question raised by us in the introduction, we will
defend the position that these three states can be defined,
that their components can be analyzed and measured, and
that they are significantly different from one another.
After presenting our justification for this claim, we will
Hobson et al.: Dreaming and the brain
Figure 1. The Activation-Input Source-Neuromodulation model
(AIM). Illustration of three dimensional state space and the psy-
chological neurobiological correlates of each dimension. See sec-
tion 4 and also Hobson (1990; 1992a; 1997a).
address the claim made by many psychologists that differ-
ences between REM and NREM mentation – and even dif-
ferences between REM and waking mentation – are much
smaller than we believe. In the course of this discussion, we
will identify several areas of disagreement and then suggest
some new approaches to their resolution.
Definitions of dreaming have ranged from the broadest
“any mental activity occurring in sleep” to the narrower one
that we prefer:
Mental activity occurring in sleep characterized by vivid senso-
rimotor imagery that is experienced as waking reality despite
such distinctive cognitive features as impossibility or improba-
bility of time, place, person and actions; emotions, especially
fear, elation, and anger predominate over sadness, shame, and
guilt and sometimes reach sufficient strength to cause awaken-
ing; memory for even very vivid dreams is evanescent and tends
to fade quickly upon awakening unless special steps are taken
to retain it.
We believe that this highly specified definition serves both
folk psychology and cognitive neuroscience equally well. It
captures what most people mean when they talk about
dreams and it lends itself admirably to neurocognitive
analysis as we now intend to show.
2.1. Early findings of distinct differences between
REM and NREM mentation
Before proceeding, we provide definitions of “REM” and
“NREM” sleep for those readers unfamiliar with these
terms. These two clearly distinguishable types of sleep are
defined, by convention, in terms of electrophysiological
signs detected with a combination of electroencephalo-
graphy (EEG), electroculography (EOG), and electromyo-
graphy (EMG) whose measurement is collectively termed
“polysomnography” (see Rechtschaffen & Kales 1968).
First described by Aserinsky and Kleitmann in 1953, REM
sleep (also known as “paradoxical,” “active” or “desynchro-
nized” sleep) is characterized by: (1) wake-like and “acti-
vated” (high frequency, low amplitude or “desynchro-
nized”) activity in the EEG; (2) singlets and clusters of rapid
eye movements (REMs) in the EOG channel; and (3) very
low levels of muscle tone (atonia) in the EMG channel.
NonREM (NREM) sleep includes all sleep apart from
REM and is, by convention, divided into four stages corre-
sponding to increasing depth of sleep as indicated by the
progressive dominance of the EEG by high-voltage, low-
frequency (also termed “synchronized”) wave activity. Such
low frequency waves dominate the deepest stages of
NREM (stages 3 and 4) which are also termed “slow-wave”
or “delta” sleep. We refer the reader to Hobson (1989) for
a comprehensive primer on sleep physiology.
Aserinsky and Kleitman’s (1953) report of the correlation
of REM sleep with dreaming began an intense period of re-
search on the relation of brain to mind that lasted well into
the 1970s. In the early days of the human sleep-dream lab-
oratory era, much attention was paid to the specificity, or
lack thereof, of the REM-dream correlation using the
newly available sleep laboratory paradigm. Normal sub-
jects, usually students, were awakened from either the
NREM or REM phase of sleep in the sleep laboratory and
asked to report their recollection of any mental experience
preceding the awakening.
During this period, the similarities and differences in
mentation between the brain states of waking, NREM, and
REM sleep were lavishly documented (e.g., Foulkes 1962;
Foulkes & Fleisher 1975; Goodenough et al. 1959; Herman
et al. 1978; Monroe et al. 1965; Nielsen 1999; Pivik &
Foulkes 1968; Rechtschaffen 1973; Rechtschaffen et al.
1963; Vogel 1991). We have summarized these REM-
NREM differences in Table 1. Some of the important con-
clusions from this cross-sectional normative paradigm are:
1. Following REM sleep awakenings, variously defined
dream reports are obtained much more frequently (Aserin-
sky & Kleitman 1953; 1955; Dement 1955; Dement &
Kleitman 1957b; Kales et al. 1967; Wolpert & Trosman
1958) or at least substantially more frequently (Foulkes
1962; Goodenough et al. 1965a; Hobson et al. 1965; Moli-
nari & Foulkes 1969; Rechtschaffen et al. 1963; Stoyva
1965) than after NREM awakenings. For reviews of this
early work see Foulkes (1966; 1967), Herman et al. (1978),
Nielsen (1999), Pivik (1991), Rechtschaffen (1973), and
Snyder (1967). In an extensive review of 29 REM and 33
NREM recall rate studies, Nielsen (1999) found an average
REM recall rate of 81.8 (68.7)% compared to an average
rate for NREM of 42.5 (621.0)%.
2. The frequency of dream recall rapidly drops off as
awakenings are delayed beyond the end of a REM period
(Dement & Kleitman 1957b; Goodenough et al. 1965b;
Wolpert & Trosman 1958), a finding which has recently
been both supported (Stickgold et al. 1994a) and chal-
lenged (Rosenlicht et al. 1994). Subjects who are able to
indicate that they are dreaming during sleep more often in-
dicate dreaming during REM than during NREM (Antro-
bus et al. 1965).
3. There exists a positive relationship of both report
word count and subjectively estimated dream duration with
the length of preceding REM sleep (Dement & Kleitman
1957b) and this relationship has been recently replicated
for word count (Stickgold et al. 1994a). Moreover, stimulus-
incorporation studies suggest that there exists a positive re-
lationship between the length of time dream events would
occupy in real time and the duration of the preceding REM
sleep epoch (Dement & Wolpert 1958).
4. Judges are able to distinguish unaltered REM menta-
tion reports from NREM reports (Monroe et al. 1965), a
finding that has been recently replicated (e.g., Herman et
al. 1978; Reinsel et al. 1992). Furthermore, some dreamers
can subjectively determine whether they themselves had
been awakened from REM or from NREM (Antrobus &
Antrobus 1967).
5. Reports from REM sleep awakenings are typically
longer (Antrobus 1983; Casagrande et al. 1990; 1996b;
Foulkes & Rechtschaffen 1964; Foulkes & Schmidt 1983;
Stickgold et al. 1994a; Waterman et al. 1993), more per-
ceptually vivid, more motorically animated, more emotion-
ally charged, and less related to waking life than NREM re-
ports (Antrobus et al. 1987; Cavallero et al. 1992; Foulkes
1962; Herman et al. 1978; Ogilvie et al. 1982; Rechtschaf-
fen et al. 1963; see Nielsen, 1999 and Table 1 for sum-
maries). In addition, there is linguistic evidence for greater
consolidation of dream elements in REM (Salzarulo &
Cipolli 1979).
6. In contrast to REM reports, NREM reports contain
thought-like mentation and representations of current con-
cerns more often than do REM sleep reports (Foulkes
1962; Rechtschaffen et al. 1963).
In a review of early data, Monroe et al. (1965) stated that
“the high degree of success attained by the judges [in dis-
Hobson et al.: Dreaming and the brain
Hobson et al.: Dreaming and the brain
Table 1. Phenomenological differences between REM and NREM dream reports
Study # S’s x # awak- % recall (any % using more report visual
Sleep Stage # S’s # nights enings content) strict criteria length bizarreness vividness emotionality movement
Antrobus (1983) 73 73 not compared no data given not compared REM vs St. 2 not compared not compared
REM 73 no report REM .St.2 n.s. when length
St. 2 NREM 73 no report p,.01 controlled
Aserinsky & Kleitman (1953) 10 14 “dreaming”
REM 27 74 74
NREM 19 22 11
Casagrande et al. (1996) 20 40 $1 sentence using word w. Antrobus et w. Antrobus et not compared not compared
REM REM & $1 action” count indices: al., 1976 index: al., 1976 index:
early (in night) 40 early 75 early: early: early:
late (in night) 40 late 75 REM. 2 & SO REM. 2 & SO REM. 2 & SO
NREM (St. 2 abbreviated “2”) NREM (2) late: late: late:
early 40 early 50 REM & 2. SO REM & 2. SO REM & 2. SO
late 40 late 70 using a global using a global
Sleep onset NREM St. 2 (SO) NREM (SO) rating: rating:
early 40 early 50 REM always . REM always .
late 40 late 55 2 & SO 2 & SO
Cavallero et al. (1992) 60 120 not compared temporal units implausibility not compared % containing not compared
REM 60 89.2 5.1
34 n.s. 62
St. 3&4 NREM 60 64.5 1.88 50 34
Cicogna et al., 1998 not compared temporal units implausibility* not compared number reported body feelings
late spontaneous REM 36 72 144 95 7.3 84.2% .76 21.1%
late spontaneous St. 2 144 91 6.0 79.6% .60 10.2%
Dement (1955) 13 ? not compared “dreaming” not compared not compared not compared not compared not compared
REM 51 88.2
NREM 19 0
Dement & Kleitman (1957) 9 61 not compared “dreaming” not compared not compared not compared not compared not compared
REM 191 79.6
NREM 160 6.9%
Hobson et al.: Dreaming and the brain
Foulkes (1962) 8 56 “vs. thinking” judged scene judged visual judged present judged present
REM 108 87 82 shift:REM. vs. not:REM. /absent: REM. /absent: REM.
NREM 136 74 54 NREM p,.02 NREM p,.02 NREM p,.02 NREM p,.01
St. 1 NREM 32 69 56 subject-judged: subject-judged subject-judged subject-judged subject-judged
St. 2 NREM 32 74 51 REM.NREM “distortion”: “% visible”: “present”: “activity”:
St. 3&4 NREM 32 70 51 p,.05 R.N p,.05 R.N p,.05 R.N p,.05 R.N p,.05
Foulkes & Rechtschaffen (1964) 24 48 not compared word count subject-judged subject-judged subject-judged subject-judged
NREM 84 61.9 158.6 p5.01 p5.01 p5.01 p5.01
Foulkes & Schmidt (1983) 23 69 .1 temporal unit temporal units not compared not compared not compared not compared
REM 82 93 80 5.5
NREM 78 67 40 1.33
Goodenough et al. (1959) 16 48 not compared not compared not compared not compared not compared not compared
REM 91 69.2
NREM 99 34.3
Goodenough et al. (1965a) 10 98 “dreaming” word count judged: judged visual not compared judged activity:
REM 120 84 76 115 REM . NREM imagery:REM REM . NREM
NREM 240 45 21 34 p,.02 .NREM p,.01 p,.01
Hobson et al. (1965) 10 4060 “dreaming” not compared not compared not compared not compared not compared
REM 195 87.2 76.4
NREM 102 37.2 13.7
Kales et al. (1967) 3 40 dream1thinking “dreaming” not compared not compared not compared not compared not compared
REM 134 83 81
NREM 108 35 7
Kamiya (1961) 25 250 “dreaming” not compared not compared not compared not compared not compared
REM ? ? 85
NREM 400 46 27
Molinari & Foulkes (1969) 10 40 tonic / phasic not compared not compared not compared subject judged not compared not compared
REM 40 80 100 tonic / phasic
descend / ascend 60 100
NREM 79 72 75 7980
Ogilvie et al. (1982) 9 27 not reported not reported not compared judged: REM. judged: REM. judged: REM. not compared
REM 54 St. 2 NREM St. 2 NREM St. 2 NREM
NREM 54 p,.05 “marginally” “tendency”
Hobson et al.: Dreaming and the brain
Table 1. (Continued)
Study # S’s x # awak- % recall (any % using more report visual
Sleep Stage # S’s # nights enings content) strict criteria length bizarreness vividness emotionality movement
Pivik & Foulkes (1968) 20 40 not compared not compared not compared not compared not compared not compared
NREM total 158 64.6
NREM St. 2 74 71.6
NREM St. 3 56 64.3
NREM St. 4 28 46.4
Rechtschaffen et al. (1963) 17 30 Ss say dreaming not compared subject judged subject judged subject judged not compared
REM 86 87 37% bizarre 74% vivid 74% emotional
NREM 23 41 6% bizarre 24% vivid 24% emotional
Salzarulo & Cipolli (1979) 8 80 “contentful” # sentences not compared not compared not compared not compared
REM 240 95 4.22
NREM 240 85 3.48
Stickgold et al. (1994) Nightcap 11 110 (spont.) . 100 words not compared not compared not compared not compared
REM 88 83 62 314
NREM 61 54 18 65
Stoyva (1965) 7 (deaf ) 28 not compared not compared not compared not compared not compared not compared
REM 51 73
NREM 68 38
Waterman et al. (1993) 12 24 72 not reported not reported REM.NREM not compared w.Antrobus et not compared not compared
al., 1976 index
and length
partialed out:
Wolpert & Trosman (1958) 10 51 “dreaming” not compared not compared not compared not compared not compared
REM 54 90.8 85.2
NREM St. 2 26 3.8 0
*Cicogna et al. 1998 actually found significantly more “space-time distortions” and a trend toward more “dimensional distortions” in Stage 2 versus REM reports, while the trend in global
bizarreness (implausibility) went in the usual REM.Stage 2 direction. R 5 REM, N 5 NREM, spont. 5 spontaneous awakenings from identified sleep stage.
Hobson et al.: Dreaming and the brain
tinguishing REM from NREM reports] indicates that phys-
iological sleep phase, REM or NREM, is highly diagnostic
of the presence, amount, and quality of reported sleep men-
tation” (p. 456). In discussing the findings of this study,
Rechtschaffen (1973) concluded that “these figures – dis-
criminability ranging from about 70 to 90% – probably rep-
resent one of the best correlations ever discovered between
psychological and physiological variables” (p. 163).
In REM sleep, the integrated conscious experience that
is commonly referred to as dreaming is characterized by the
following remarkably consistent set of features (see Hobson
1988b; 1994 for reviews):
1. Dreams contain formed hallucinatory perceptions,
especially visual and motoric, but occasionally in any and all
sensory modalities (Hobson 1988b; McCarley & Hoffman
1981; Snyder 1970; Zadra et al. 1998).
2. Dream imagery can change rapidly, and is often
bizarre in nature (Hobson 1988b; 1997b; Hobson & Stick-
gold 1994a; Hobson et al. 1987; Mamelak & Hobson 1989a;
McCarley & Hoffman 1981; Porte & Hobson 1986; Rein-
sel et al. 1992; Revonsuo & Salmivalli 1995; Williams et al.
1992). It has also been noted that dream reports contain a
great many images and events which are relatively com-
monplace in everyday life (Dorus et al. 1971; Snyder 1970).
3. Dreams are delusional; we are consistently duped into
believing that we are awake unless we cultivate lucidity
(Barrett 1992; Hobson 1997b; Kahan 1994; LaBerge 1990;
1992; Purcell et al. 1986).
4. Self-reflection in dreams is generally found to be ab-
sent (Rechtschaffen 1978) or greatly reduced (Bradley et al.
1992) relative to waking and, when present, often involves
weak, post hoc, and logically flawed explanations of im-
probable or impossible events and plots (Hobson 1988b;
Hobson et al. 1987; Williams et al. 1992). It has been re-
cently asserted, however, that self-reflection, self control
and other forms of metacognition are more common in
dreams than previously thought (Kahan 1994; Kahan &
LaBerge 1994).
5. Dreams lack orientational stability; persons, times, and
places are fused, plastic, incongruous and discontinuous
(Hobson 1988b; 1997b; Hobson et al. 1987; McCarley &
Hoffman 1981; Revonsuo & Salmivalli 1995; Rittenhouse et
al. 1994; Stickgold et al. 1994b; 1997b; Williams et al. 1992).
6. Dreams create story lines to explain and integrate all
the dream elements in a single confabulatory narrative (Bla-
grove 1992b; Cipolli & Poli 1992; Cipolli et al. 1998; Foulkes
1985; Hobson 1988b; Hunt 1991; Montangero 1991).
7. Dreams show increased and intensified emotions, es-
pecially fear-anxiety (Domhoff 1996; Merritt et al. 1994;
Nielsen et al. 1991), which appear to integrate bizarre
dream features (Merritt et al. 1994), and may even shape
the narrative process (Seligman & Yellin 1987). Although
the trend toward a predominance of negative emotion is
prominent in most studies, other workers have found more
balanced amounts of positive and negative emotion (for a
good review, see Schredl & Doll 1998). Emotion also ranks
as a prominent explanatory focus in functional theories of
dreaming (e.g., Cartwright et al. 1998a; Greenberg et al.
1972; Kramer 1993; Perlis & Nielsen 1993).
8. Dreams show increased incorporation of instinctual
programs (especially fight-flight), which also may act as
powerful organizers of dream cognition (Hobson 1988b;
Hobson & McCarley 1977; Jouvet 1973; 1999).
9. Volitional control is greatly attenuated in dreams
(Hartmann 1966b). The dreamer rarely considers the pos-
sibility of actually controlling the flow of dream events (Pur-
cell et al. 1986) and, on those infrequent occasions when
this does occur, the dreamer can only gain lucidity with its
concomitant control of dream events for a few seconds
(LaBerge 1990). Unlike the rarer form of dream control of-
fered by lucidity, however, the more mundane self-control
of thoughts, feelings and behavior may be fairly common in
dreams (Kahan 1994).
All of these features can be found in REM dreams, and
most REM dreams contain a majority of these features.
Contrastingly, they are found relatively rarely in NREM re-
ports (see Nielsen 1999). This is the empirical basis of our
contention that all of these features will eventually be ex-
plainable in terms of the distinctive physiology of REM
We interpret the foregoing evidence as strongly support-
ing our conclusion that there are clear-cut and major dif-
ferences among the states of waking, sleeping (NREM) and
dreaming (REM) at the phenomenological level. We take
the robust evidence for quantitative differences in amount
of NREM and REM sleep mentation as convincing proof
of the validity of an important role for not only activation
(factor A) but for the two other factors, information source
(I) and modulation (M) in our AIM model. In addition, we
take the evidence that state transitions are gradual rather
than discontinuous and the evidence that correlations be-
tween phenomenology and physiology are statistical rather
than absolute as further support of this model.
2.2. Overview of the NREM-REM sleep
mentation controversy
Although the discovery of REM sleep and its strong corre-
lation with dreaming (Aserinsky & Kleitman 1953) initially
led to the strong hypothesis that dreaming occurred only
during REM sleep (Dement & Kleitman 1957b), this hy-
pothesis was clearly refuted by the discovery that reports of
dreaming could be elicited from NREM sleep (Foulkes
1962) and that reports of dream-like mentation could also
be obtained at sleep onset (Foulkes & Vogel 1965) and even
from quiet waking (Foulkes & Fleischer 1975; Foulkes &
Scott 1973). Given dreaming’s lack of absolute state speci-
ficity, some investigators sought the psychophysiological
correlates of specific dream features in the phasic events
of REM and NREM sleep (Molinari & Foulkes 1969; see
Kahn et al. 1997 and Pivik 1991 for reviews). Again, weak
but consistently positive quantitative relationships were
found (Kahn et al. 1997; Pivik 1991).
This lack of specificity led at least some investigators ul-
timately to conclude that investigations of REM sleep neu-
rophysiology could provide no data helpful to understand-
ing the genesis of dreaming (e.g., Bosinelli 1995; Foulkes
1990; 1991; 1993b; 1995; 1996a; 1997; Moffitt 1995). Such
a view was encouraged by reports suggesting that in fact the
differences between REM and NREM mentation were not
nearly as great as had first been reported (e.g., Cavallero et
al. 1992). In this section, we will present our reasons for re-
jecting these conclusions (see also Nielsen, target article).
How could the firm conclusions of the pioneer era
(19551975) have apparently dissolved in the subsequent
era of growing controversy (19751999)? In this section,
we will analyze some of the scientific problems that led to
the decline of the sleep-laboratory paradigm as this psy-
chophysiological approach lost much of its initially enthusi-
astic support. In the subsequent section we will turn our at-
tention to the concomitant development of cellular and
molecular neurobiology and show how the findings of basic
research provided an alternative approach.
2.2.1. REM sleep dreaming is not qualitatively unique.
While dream studies generally agree that REM reports are
more frequent, longer, more bizarre, more visual, more an-
imated and more emotional than NREM reports (Table 1),
a pair of papers published in 1983 (Antrobus 1983; Foulkes
& Schmidt 1983) led some researchers to the remarkable
conclusion that the “characteristics [of dreaming] are pretty
much the same throughout sleep” (Moffitt 1995) and that
“dreaming in other sleep stages is not qualitatively different
from REM dreaming” (Foulkes 1995). Because these pa-
pers are so central to the REM-NREM dreaming debate,
we now offer a detailed review and critique of their findings
and interpretations.
At the outset, it is important to point out that neither arti-
cle actually concluded that REM and NREM dreams are in-
distinguishable, or even substantially the same, in either their
quantitative or their qualitative features. In regard to qualita-
tive features, Antrobus (1983) reported that when judges
rated 154 REM and NREM reports for their relative “dream-
iness” (using scales based on “visual imagery, bizarreness, hal-
lucinatory quality and storylike quality”), they correctly iden-
tified 93% of the reports as either REM or NREM, indicating
that REM dream reports were much more dreamlike than
NREM reports. Similarly, Foulkes and Schmidt (1983, p.
276) concluded that “REM reports are likely to be signifi-
cantly more dreamlike qualitatively (e.g., in character density,
setting clarity) than typical NREM” reports, even when
elicited after only five minutes of stage REM.
In regard to quantitative features, when Foulkes and
Schmidt (1983) looked at 160 REM and NREM reports and
characterized their lengths by the number of “temporal
units” (narrative events), their data showed that temporal se-
quences (sequential events 5 temporal units 2 1) were 14
times more common in REM reports than in NREM re-
ports. In a similar way, Antrobus analyzed total recall fre-
quency (TRF), which reflects the number of words in a re-
port used to describe sleep mentation, and reported that
word count significantly distinguished REM from NREM
reports (F 5 95.52). Using the same reports (J. Antrobus,
personal communication), we have determined that the
REM reports collected by Antrobus had a median length 6.4
times longer than their matched NREM reports, a number
similar to the ratio of 7.0 obtained in a home study using re-
ports from spontaneous awakenings (Stickgold et al. 1994a).
Since both Foulkes and Schmidt (1983) and Antrobus
(1983) report such impressive differences between REM
and NREM reports, one might wonder how and why these
very authors have come to argue so strongly for a phenom-
enological sameness of these states. The critical question,
raised by Foulkes and Schmidt and by Antrobus, pertains
to the origin of the differences between REM and NREM
reports, “whether there are . . . qualitative . . . differences
as well as quantitative ones, and . . . whether such differ-
ences are merely attendant upon or are independent of the
quantitative ones” (Foulkes & Schmidt 1983, p. 269). Or, as
Antrobus wonders, whether “judges of Dreaming [dreami-
ness] implicitly rely on a dimension similar to the Total
Recall Freq.” (p. 562). It is this analysis that has led sub-
sequent writers to claim that “when the quantitative char-
acteristics of reports . . . from REM and nonREM . . . sleep
are adjusted for length there are no differences in the char-
acteristics of the reports” (Moffitt 1995, p. 19).
The normalization-for-length technique has been subse-
quently used to argue that bizarreness differences between
REM and slow wave sleep (SWS) reports (Colace & Natale
1997), the number of dream-like features in a report (Fein
et al. 1985; Rosenlicht & Feinberg 1997), memory sources
of dreams (Cavallero et al. 1990) and even dream bi-
zarreness itself (Bonato et al. 1991) are all directly and
causally dependent on report length independent of sleep
stage. Similar arguments have been advanced to explain
correlations between dream bizarreness and creativity (Liv-
ingston & Levin 1991).
We will shortly reiterate our introductory arguments
against this line of reasoning. Meanwhile, we emphasize
some of these authors’ own data that favor placing a strate-
gic emphasis on the differences between REM and NREM
mentation rather than using the similarities as a rationale
for rejecting the cognitive neuroscience paradigm in favor
of a purely cognitive description of mental states. (A simi-
lar critique of purely cognitive descriptions can be found in
Nielsen 1999; and his target article.)
For example, Antrobus has recently shown that the
REM/NREM distinction exerts a far greater effect on
bizarreness than diurnal activation (Antrobus et al. 1995).
He attributed the observed increase in bizarreness in
REM reports to the increased activation seen in that state
(Antrobus et al. 1995). It is also noteworthy that purely vi-
sual (versus verbal) imagery gave robust REM/NREM dif-
ferences suggesting a differential sensory activation be-
tween the two states (Antrobus et al. 1995). And even when
REM and NREM dreams were adjusted for length (a pro-
cedure we will shortly argue to be invalid), both Antrobus
(1983) and Foulkes and Schmidt (1983) still found signifi-
cant differences (e.g., in character density and setting clar-
ity) between the two states. Notably, the persistence of a
REM/NREM effect on bizarreness, visual imagery, and
several other dream features in spite of normalization for
report length has recently been confirmed (Casagrande et
al. 1996b; Faucher et al. 1999; Nielsen 1999; and his target
article; Raymond et al. 1999; Waterman et al. 1993). For ex-
ample, when analysis of covariance (with report length as
the covariate) is used to partial out the effect of report
length on dream features, REM reports were still judged
significantly more visual and bizarre than sleep onset or
stage 2 reports (Casagrande et al. 1996b) and more visual
than NREM reports (Waterman et al. 1993).
Even when dream features appear to be specifically
linked to distinctive REM physiology, interpretations can
still be cast toward either camp. Hong et al. (1997) reported
an impressive correlation between visual imagery and REM
density (r 5 0.8), which we would argue as evidence for a
dependence of dream imagery on a qualitative feature of
REM sleep. But Antrobus et al. (1995) consider this to be
another example of the simple dependence of dream con-
tent on levels of brain activation, arguing that rapid eye
movements are not under strict brainstem cholinergic con-
trol, but come increasingly under the control of the frontal
eye fields as general cortical activation increases.
Whatever one’s assessment of the similarity versus dif-
ference argument, it is clear that none of the analyses in
these two papers can distinguish between two competing
Hobson et al.: Dreaming and the brain
hypotheses: (1) that dream features are dependent on re-
port length; and its simpler converse (2) that report length
is dependent on dream features. We now consider the ar-
guments in favor of the second hypothesis, which we have
adopted in our own work.
2.2.2. The relationship between dream features and
dream report length.
That report length depends on dream
features was first implied by Hunt (1982) in his analysis of
dreaming as fundamentally visuospatial versus verbal-
propositional and was then explicitly proposed by Hunt et
al. (1993). We agree with their logical assumption that re-
ports with more dream features will require more words to
describe them. For example, a report with such dream fea-
tures as self-representation, visual hallucination, emotion,
narrative plot, and bizarreness will almost certainly be
longer than a report with none of these features. Similarly,
it is highly unlikely that a report with a word count of only
seven words, the median length of the Antrobus (1983)
NREM reports (J. Antrobus, personal communication),
could possibly have more than one of the above features.
Inexplicably, Antrobus (1983) and Foulkes and Schmidt
(1983) both seem to regard word count and content as in-
dependent of each other. In doing so, each has emphasized
a very different explanation. Although conceding that al-
ternative explanations were “in no way excluded by these
findings,” Antrobus (1983) concluded that the NREM re-
ports were shorter due to a defect in “the ability of the sub-
ject to recall and describe the [dream] events” (p. 567). In
this view, the shorter reports failed to include dream fea-
tures which were nonetheless present in the NREM dream
itself. To us this seems, at best, a risky assumption. In con-
trast, Foulkes and Schmidt (1983) concluded that the short-
ened reports and the rarity of dream features reported re-
sulted from differences in dream production. On this view,
the differences reflected “the relative paucity and superfi-
ciality of mnemonic units active during NREM sleep”
(p. 279) compared to REM sleep. The conclusion of
Foulkes and Schmidt (1983) is strikingly similar to our po-
sition, which is that the relative brevity of NREM reports
reflects a decrease in the types (superficiality) and number
(paucity) of dream features present in the conscious expe-
rience reported in them. If Foulkes really agrees with us on
this point, he cannot then also countenance controlling for
word count in evaluating reports.
Analyzing the same data set used by Antrobus (1983) we
have shown that REM/NREM differences can not be ex-
plained simply in terms of report length (Porte & Hobson
1986). Thus we agree with Antrobus when he pointed out
that there is still a part of the REM/NREM variance that
Dreaming (i.e., judges’ idiosyncratic scales for “dreami-
ness”) picks up better than a Total Recall Frequency factor.
Similarly, Foulkes and Schmidt (1983) reported that some
residual REM/NREM differences in temporal unit compo-
sition (e.g., in character density) persist even after report
length is controlled. Residual stage differences following
normalization for report length in these as well as additional
studies have recently been reviewed by Nielsen (1999).
In the face of such unambiguous statements, it is critical
to try to understand why these results have been so fre-
quently and so passionately misinterpreted. In part, the er-
roneous interpretations were encouraged by the original
authors. For example, Antrobus (1983, p. 567) concluded
that “although there are slight differences . . . it is quite
clear that the global judgment of Dreaming adds little, if
anything, to Total Recall [Frequency] with respect to the
association with the sleep stages REM and NREM.” Simi-
larly, Foulkes and Schmidt (1983; p. 279) concluded that
most typically observed inter-stage differences in dream
reports stem from different lengths rather than the differ-
ent stages of the reports” (emphasis added). Because they
have conflated causality with correlation, both Antrobus
and Foulkes and Schmidt unjustifiably assume that most of
the differences seen can be explained as correlates of report
length. We disagree on the basis of the following studies.
Recent evidence provides strong support for Hunt’s
proposition that report length reflects the number and in-
tensity of dreamlike features prior to awakening. Hunt et al.
(1993) have argued “it is not the length of the dream that
somehow makes bizarreness more likely, but . . . it is more
parsimonious to conclude that episodes of bizarreness within
the dream are one major determinant of overall dream
length . . . making length a necessary consequence of
bizarreness and not the other way around” (p. 180). In addi-
tion, Hunt et al. (1993) note that Hauri et al.’s (1967) factor
analysis of dreams found that bizarreness and report length
significantly load on the same factor (and therefore strongly
co-vary), “which would make their enforced statistical sepa-
ration highly questionable” (Hunt et al. 1993, p. 181). In
other words, if quantity follows quality and is, in fact, caused
by it, then longer reports are needed to describe dreamier
dreams. On this view, word count is perhaps even a direct
measure of dreaminess and might well be taken as such.
To support their position, Hunt et al. (1993) first demon-
strated that awake subjects used more words to describe a
visually bizarre picture than a mundane picture. They then
showed that the bizarreness scores correlated positively
with the number of words devoted to describing the bizarre
episodes. Finally, they showed that normalizing dream fea-
tures for report length actually eliminated the correlations
of bizarreness with non-verbal imagination test scores.
Hunt et al. therefore concluded that bizarreness directly
determines a major component of report length and that
controlling for total word count introduces an artifactual di-
lution of bizarreness scores.
In summary, a critical review of the papers of Antrobus
(1983) and Foulkes and Schmidt (1983) reveals that these
papers report significant quantitative differences in the fea-
tures of REM and NREM dreams. Both papers also find fea-
tures such as dreaminess or character density to differ sig-
nificantly between REM and NREM dreams even when
report length is unjustifiably normalized. Neither study re-
ports data that argue against the contention that the strong
correlation between report length and dream features oc-
curs because reports with more dream features require more
words to describe them (Hunt et al. 1993; Nielsen 1999). We
urge the collection of additional data to further clarify the na-
ture of these REM/NREM differences. Such data should in-
clude ample numbers of reports, collected longitudinally in
naturalistic settings, which are obtained from home awak-
enings physiologically monitored with unintrusive devices
such as the Nightcap (e.g., Rowley et al. 1998).
2.3. Methodological considerations
in the study of dreaming
The study of mental states is replete with methodological
shortcomings and conceptual confusions. We believe that
Hobson et al.: Dreaming and the brain
some of these areas of confusion can be clarified in a man-
ner that could increase consensus. In what follows, we ad-
dress five methodological issues to point out the nature of
the problems, offer clarifications, and suggest possible res-
2.3.1. The reduction of psychological states to narrative
The most profound problem in studying conscious
states is the necessity of reliance on verbal reports. This
method is problematic because these accounts are just re-
ports, not the subject’s experience of the states themselves.
This reduction of conscious experience to prose has at least
three important ramifications:
(1) A multimodal conscious experience including pseudo-
sensory perceptual, emotional, and motoric dimensions is
reduced to only one mode, that of narration. (To emphasize
this point, we merely point out that if a picture is worth a
thousand words, we certainly are not getting the whole pic-
ture with a seven-word report!)
(2) The narratives describing sleep state mentation are
all generated during the waking state and are thus likely to
mix, if not contaminate, the dreaming phenomenology with
the phenomenology of waking (for a discussion of this point
relative to dream meaning, see Hunt 1989, p. 9).
(3) Analysis of narrative dream reports is extremely lim-
ited in its power to recreate or model the true underlying
mechanism of dream production at any fundamental, pri-
mordial level of explanation (be it cognitive-mnemonic, lin-
guistic or neuropsychological) because narratives about ex-
perience display a high degree of what Pylyshyn (1989)
terms “cognitive penetrability.”
Pylyshyn’s point can be applied to dreaming as follows.
The behavior of the dream production system is highly mal-
leable using the same cognitive processes invoked to explain
its behavior such as the dreamer’s goals and beliefs (see
Pylyshyn 1989). For example, in the case of the dreamer’s
goals, the frequency of overall dream recall as well as lucid-
ity can be greatly increased by auto-suggestion techniques
that employ many of the same cognitive abilities (e.g., imag-
ination and visualization) that most theorists believe con-
tribute to dream production itself (see sect. 3.3). In the case
of beliefs, the meaning of a dream experience while it is oc-
curring is highly dependent on the dreamer’s personal (and
changeable) philosophy of what dreaming is (e.g., a message
from a deity, a psychopathomimetic experience, “travel out-
side the body,” etc.). According to Pylyshn (1989) such
highly penetrable experiences, rather than illustrating pri-
mordial cognitive mechanisms, instead reflect “the nature of
the representations and . . . cognitive processes operating
over these representations” (p. 81), which, in the case of
dream reports, is language itself. Given that Pylyshn (1989)
asserts that cognitive penetrability can affect even highly
objective and replicable psychological data (such as the vi-
sualized-image-size/image-scanning-time relationships de-
scribed by Kosslyn & Koenig 1992), penetrability is all the
more likely to influence the highly elaborated and individu-
alistic phenomenon of dream reporting. The rendering of
dream reports in conventional (wake state) grammar and
syntax may, therefore, tend to obscure important differences
between the actual experiences of waking and dreaming.
These considerations raise the concern that using the
sentence or the word as a unit for quantifying mental activ-
ity may say more about language than about the multimodal
nature of conscious experience. This is important because
so many researchers consider the quantification of report
length as the single most salient feature of a dream. In this
context, it is also worth noting that verbal retrospective re-
ports are often considered inadequate to describe mental
states that are closer to dreaming than to waking mentation.
These states include religious conversion, near-death expe-
rience, functional psychosis, delirium, drug-induced condi-
tions, and other altered states of consciousness.
This aspect of the REM physiology-dream mentation con-
troversy may be particularly relevant to the current debate
about self-representation and bizarreness in dreams of chil-
dren aged 3 to 8 (see Foulkes 1990; 1993b; 1996a; 1996b;
1997; Resnick et al. 1994). Based upon an extensive longitu-
dinal study (Foulkes 1982b) and a later cross-sectional study
(Foulkes et al. 1990), Foulkes asserted that “dreaming is ab-
sent until ages 3 to 5 and does not assume the form of adult
dreaming until ages 6 to 7” (Foulkes 1997, p. 4). Foulkes hy-
pothesizes that, lacking or being deficient in their ability to
consciously mentally represent their perceptuo-behavioral
experience, young children (like animals) may not experi-
ence dreaming in spite of having an abundance of REM
(Foulkes 1990; 1993c). He argues further that dreaming is
“a high-level symbolic skill, a form of intelligent behavior
with cognitive prerequisites and showing systematic devel-
opment over time” (Foulkes 1993c, p. 120), and that dream-
ing has, as its prerequisite, conscious representational com-
petence (Foulkes 1990; Foulkes et al. 1990). As evidence to
support this, he cites studies in which he finds very low re-
call of dreaming and little bizarreness prior to age 5 (Foulkes
1982b; Foulkes et al. 1979), low rates of reporting at ages 5
8 (Foulkes 1982b; Foulkes et al. 1990), acquisition of kinetic
versus static imagery only after age 6 (Foulkes et al. 1990),
and acquisition of self-representation as an active dream par-
ticipant as well as narrative continuity only after age 7
(Foulkes et al. 1990; 1991). Further, from his data showing
correlation of report rate with measures of visuospatial ver-
sus verbal skills (Foulkes et al. 1990), Foulkes (1993b) sug-
gests that “young children may fail to report dreams because
they are not having them, rather than because they have for-
gotten them or are unable to verbalize their contents”
(p. 201). For a recent review see Foulkes (1999).
Subsequent studies have shown that dream bizarreness
does indeed increase over ages 3 to 8 (Colace et al. 1993;
1997; Colace & Tuci 1996; Resnick et al. 1994). However,
other of Foulkes’s findings have not been supported. For
example, dream reporting rates in 4- to 5-year olds has been
reported to be almost identical to that in 8- to 10-year olds
(Resnick et al. 1994). In addition, active self representation
in dreams of 4- to 5-year olds has been reported to occur
in over 80% of their dream reports (Colace et al. 1995;
Resnick et al. 1994). Finally, substantial occurrence rates
for bizarre elements have been reported in the dreams of
both 4- to 5-year olds (0.45 per 100 words) and 8- to 10-year
olds (0.71 per 100 words) (Resnick et al. 1994).
Moreover, although rates of adult dream recall have
been related to performance on tests of visuospatial skill
(Butler & Watson 1985), rates of dream recall have also
been correlated with individual differences in visual memory
(Schredl et al. 1995). Therefore, any ontogenetic changes
in visual memory would confound the effects of develop-
mental changes in higher order visuospatial skills on dream
reporting rates in children.
Overarching these conflicting data, however, is the theo-
retical point bearing on the current discussion: that is, that
Hobson et al.: Dreaming and the brain
dream reports are given in waking and thus, of necessity,
must be constrained by an organism’s waking cognitive and
linguistic abilities. At one extreme, it must be conceded that
even if a cat had the most vivid of “dreams,” it would not be
able to report it. Similarly, if a toddler is variously unable
(or unwilling) to conceive and verbalize a complex percep-
tual-emotional-motor REM experience, it does not mean it
was not originally experienced in some form which, later in
life, might be reported as a dream. In other words, we chal-
lenge here the assumption by Foulkes (e.g., 1990) and oth-
ers (e.g., Bosinelli 1995) that “dreaming” is an experience
that can occur only if it can be later reported by an organ-
ism possessing linguistic abilities. We recognize that verifi-
cation of oneiric activity in organisms that are unable to re-
port (or even, possibly, reflect upon) their experiences is
currently impossible, although we do not rule out the pos-
sibility that new methods may someday provide hints as to
the conscious experiences of nonverbal beings (e.g., see
Marten & Psarakos 1995).
Nevertheless, as with many other psychological con-
structs such as emotional expression (e.g., Darwin 1873) or
behavioral inhibition (e.g., Goldman-Rakic 1986), such in-
ferences drawn between human developmental as well as
mammalian phylogenetic levels has a long scientific tradi-
tion. It is, therefore, not inherently invalid to cautiously
speculate from adult human oneiric experience to observed
REM behavior in infants and animals, especially given the
abundant behavioral correlates (e.g., ethologically meaning-
ful oneiric behavior; for a full discussion see Jouvet 1999).
Similarly, we specifically suggest that the human neonate,
spending as it does more than 50% of its time in REM sleep
(Hobson 1989), is having indescribable but nevertheless real
oneiric experiences. An infant’s waking experience remains
essentially indescribable and speculative to us older persons
but we do not doubt that infants enjoy some sort of waking
conscious experience. For us, it is not at all difficult to imag-
ine that an infant might be experiencing hallucinosis, emo-
tions, and fictive kinesthetic sensations during REM sleep.
Given these caveats, we suggest that more effort be put
into the development and use of other methodologies and
scales such as the photo-response visual brightness and
clarity scale (Antrobus et al. 1987; 1995; Rechtschaffen &
Buchignani 1992), temporal unit analysis (Cavallero et al.
1990; Foulkes & Schmidt 1983), computerized content
analyses (Gottschalk 1999), the analysis of dream drawings
(Hobson 1988b), or the use of affirmative probes (e.g.,
Herman 1992; Merritt et al. 1994; Pace-Schott et al. 1997a;
Stickgold et al. 1997a; see Herman 1992 and Hobson &
Stickgold 1994a for further discussion). In other words, we
need recourse to more diverse means to elicit detailed de-
scriptions of salient aspects of conscious experience.
2.3.2. The sleep laboratory environment. The sleep labo-
ratory itself constitutes a second major methodological
problem. Anyone who has ever slept in a sleep laboratory
(as all of us have!) knows that it is an inhospitable and un-
natural setting that makes sleep more difficult and less
deep than is possible in more naturalistic settings. To ap-
preciate this point, the reader need only imagine going to
an unfamiliar place in an inner city neighborhood of dubi-
ous safety, encountering a technician who is a stranger and
often of the opposite sex, having ten electrodes affixed to
the scalp with cement that smells like airplane dope and
then being bid “goodnight” and “pleasant dreams.” Hence
the famous first night effect (objectively poor sleep owing
to discomfort and anxiety) often extends to a second night,
and may contribute to a constriction of dream experience
(as in dreams of the sleep lab setting) over even longer
times. The laboratory environment may even alter the con-
tent of dreams recalled from spontaneous awakenings in
the laboratory at the end of a night’s sleep as evidenced by
the high frequency of laboratory references in morning
spontaneous awakening REM and NREM laboratory
dream reports (Cicogna et al. 1998).
Studies such as those of Dement et al. (1965), Domhoff
and Kamiya (1964), Okuma et al. (1975) and Whitman et al.
(1962) have shown substantial incorporation of the experi-
mental situation into laboratory dream reports particularly
on the first night in the laboratory but persisting, at a lower
level, into subsequent laboratory nights (Dement et al.
1965; Domhoff & Kamiya 1964). Similarly, content differ-
ences have been noted between laboratory and home
dreaming (Domhoff & Kamiya 1964; Domhoff & Schnei-
der 1999; Hall & Van de Castle 1966), although it has been
argued that these differences are very small (Domhoff
& Schneider 1999). Although these early studies were
confounded by spontaneous (home) versus instrumental
(laboratory) awakening conditions (as has been noted by
Foulkes 1979), later studies controlling for reporting con-
ditions (Lloyd & Cartwright 1991; Weisz & Foulkes 1970)
still found some content differences between the home and
laboratory dreams of adults. Waterman et al. (1993) em-
phasize that home-laboratory differences can arise from
both environmental factors and factors related to investiga-
tor expectancies and, therefore, both should be controlled.
In our view, full adaptation to the sleep lab may take four
days or longer (see Domhoff & Kamiya 1964) exceeding the
length of most laboratory studies.
As in the case of NREM compared to REM dreaming, we
are not arguing for a gross, qualitative distinction between
home and laboratory dreams. Laboratory dreams are, un-
doubtedly, largely representative of many of the formal and
content features of dreaming in naturalistic settings. Never-
theless, we suggest that quantitative constraints on the
dreaming experience may be imposed by the laboratory set-
ting so that the full potential expression of certain dream fea-
tures is limited. Of additional concern is the finding by
Antrobus et al. (1991) that REM-NREM differences in both
word count and global judgment of dreamlike quality di-
minish over 14 nights in the sleep laboratory, an effect they
attribute largely to motivational factors in dream reporting.
Minimizing any such “laboratory-fatigue” confound consti-
tutes further argument for longitudinal awakenings to be
performed in the more comfortable environs of the home.
To overcome these problems, several options are possi-
ble. First, laboratory studies can simply be extended in
time, perhaps recording each subject for a full week. This
has obvious disadvantages including inconvenience, high
cost, and the above noted motivational effects. A second
option is to continue to run relatively short (14 night) par-
adigms, and accept the suppressive effects on sleep archi-
tecture and dream content. While perhaps no longer nor-
matively valid, the data obtained would still be at least
reliable. A third option, and the one that we have chosen, is
to move recording into the home for extended longitudinal
studies using the Nightcap (Ajilore et al. 1995; Mamelak &
Hobson 1989b; Pace-Schott et al. 1994; Rowley et al. 1998;
Stickgold et al. 1994a; 1998b).
Hobson et al.: Dreaming and the brain
2.3.3. The question of “similarity” and “difference.” We
have long thought that the argument over whether mentation
in two states like REM and NREM sleep is more similar or
different was specious. Thinking the dilemma to be false, we
have ignored or minimized it in our previous writings. How-
ever, we now feel obliged to clarify for the reader how the de-
bate over REM and NREM mentation has become inextri-
cably entangled with the larger and more general question of
the mind-brain problem. In doing so, we hope to elevate the
debate from the parochial to the general level and to make
our own position on mind-brain issues crystal clear.
In some ways, understanding the conflicting opinions
that swirl around the sleep and dream mental content de-
bate is relatively straightforward. One group of psycholo-
gists, exemplified by David Foulkes and the late Alan Mof-
fitt, hypothesizes that the brain and the mind are so loosely
linked that the study of the mind need not be constrained
or even informed by the study of the brain (e.g.,
Bosinelli 1995; Foulkes 1991; 1993b; 1996a; 1997; Moffitt
1995). This group interprets the empirical data as indicat-
ing that mental content does not differ qualitatively across
brain states. There is only one dream mentation production
system that is more or less active during waking and sleep.
In such theories, termed “One-Generator” models of sleep
mentation by Nielsen (1999), it is only the fluctuating level
of cognitive activation that determines differences between
REM and NREM sleep in report length as well as in the
broad range of dream features that co-vary with report
length. By taking this position, these psychologists mini-
mize the importance of physiology, which they assert to be
irrelevant to the understanding of dreaming. How cognitive
activation could be independent of brain activation is a
question not addressed by these scientists.
Another group, consisting largely of psychophysiologists,
holds that the mind and the brain form an integrated sys-
tem, so tightly linked within and across states that detailed
qualitative and quantitative distinctions at either level of
analysis imply the existence of isomorphic distinctions at
the other. This is the position that we take. For us, the cog-
nition production system is the brain. And, of course, it is
always the same brain. But we know that the brain’s mode
of information processing changes radically across states.
So, therefore, must its mental products. Nielsen (1999)
terms this point of view a “Two-Generator” model of sleep
mentation. For us, the state-specific changes in brain func-
tion virtually guarantee concomitant changes in mental
function, even if our psychological methodology may still be
inadequate to identify these changes (just as for many years
the physiological changes also eluded us!).
With respect, we suggest that the failure to demonstrate
psychological differences concomitant with physiological
ones must be laid at the door of inadequate psychological
methodology. If psychology has so far failed to document
the robust phenomenological differences between waking
and dreaming that most people experience every day of
their lives, then more vigorous and more creative psycho-
logical research is needed. Otherwise we are faced with the
absurd and unacceptable conclusion that brain and mind
have nothing to do with each other.
That even a single, “One-Generator” system (i.e., a
“dream mentation production system”) may show dramati-
cally different features in different states is in no way a self-
contradiction. To our way of thinking, states of the brain are
analogous to other dynamic states of matter. Consider, for
example, the way that liquid water changes state with
changes in temperature: above 1008 C it is steam; below
08 C it is ice. These states are analogous to the states of wak-
ing, NREM sleep, and REM sleep in the brain (as well as to
less common mental states such as coma, hypnosis, and ma-
nia). No one would say that in the frozen state (ice) or in the
vapor state (steam) that the material is not still water. Nor
could any sentient person ignore the obvious differences in
the properties and behavior of water across states. We be-
lieve that it is equally inappropriate to argue that since there
is a single dream production system (i.e., the brain-mind),
that the properties and behavior of its products, for exam-
ple, dreams, must be identical or even similar across differ-
ent states. Such an important error in scientific thinking
would lead to minimizing or missing entirely the change in
matter (in this case the brain) that underlies the change in
its state-dependent properties (in this case, consciousness).
The question of whether REM and NREM mentation
are the same or different has often devolved into a search
for characteristics of mentation that are absolutely unique
to REM sleep. We consider this quest to be a fool’s errand
and indeed no absolute qualitative distinction between the
two states has yet been documented. Since the late 1950s,
many sleep laboratory studies have shown substantial recall
of mentation from NREM, thereby obviating an exclusive
association of sleep mentation with REM (Cicogna et al.
1998; Foulkes 1962; 1966; Foulkes & Rechtschaffen 1964;
Goodenough et al. 1959; 1965b; Kamiya 1961; Molinari &
Foulkes 1969; Pivik & Foulkes 1968; Rechtschaffen et al.
1963; Salzarulo & Cipolli 1979; Stoyva 1965; Zimmerman
1970; see Foulkes 1967, Herman et al. 1978, and Nielsen
1999 for reviews). For example, among nine studies, the
percentage of NREM awakenings yielding at least minimal
recall varied from 23 to 74% (Foulkes 1967) and, as noted,
Nielsen (1999) has found an average NREM recall rate of
42.5% over 33 published studies. Recall rates similar to
those of NREM in general have even been obtained from
stages III and IV of NREM (e.g., Bosinelli 1995; Cavallero
et al. 1992; Goodenough et al. 1965b; Herman et al. 1978;
Nielsen 1999; Pivik & Foulkes 1968; Salzarulo & Cipolli
1979; Tracy & Tracy 1974). In a review of eight studies of
stages III and IV mentation, Nielsen (1999) found an aver-
age recall rate of 52.5 (118.6)%, but also notes that a sub-
stantial percentage of subjects never recall stage III and IV
mentation or require several nights of awakenings before
reporting such mentation.
The findings of several studies have countered the hy-
pothesis that NREM mentation is simply recall from previ-
ous REM (Foulkes 1962; 1967; Foulkes & Rechtschaffen
1964; Goodenough et al. 1965b; Rechtschaffen et al. 1963),
although report length does drop precipitously following
the end of REM periods (Stickgold et al. 1994a).
The fact that differences are not absolute does not mean
however that no differences exist. Indeed, all the evidence
shows that such differences do exist and we have already ad-
vanced good reasons to believe that these may have been se-
riously underestimated. For example, similarities in dream
features such as bizarreness may be inflated when report
length is controlled in REM and NREM reports (Hunt et al.
1993) and REM-NREM bizarreness differences may persist
even when report length is partialled out (Casagrande et al.
1996b; Nielsen 1999; Waterman et al. 1993). In addition, re-
cent work comparing sleep onset REM and NREM dreams
using an experimental protocol which controlled for previ-
Hobson et al.: Dreaming and the brain
ous sleep and waking time has shown that sleep onset REM
periods are specifically related to physiological signs of
REM whereas NREM dreams were related to intrusions of
waking into NREM (Takeuchi et al. 1999b). These authors
conclude that the mechanisms underlying REM and
NREM dreaming must, therefore, differ (Takeuchi et al.
1999b). We thus conclude that while some NREM dreams
approach REM dreams in length, vividness, dreaminess,
and bizarreness (Cicogna et al. 1998; Foulkes & Schmidt
1983; Herman et al. 1978; Nielsen 1999) and while “dream-
like” versus “thought-like” mentation may predominate in
some NREM reports (Foulkes 1962; Nielsen 1999; Recht-
schaffen et al. 1963; Zimmerman 1970), NREM reports are
far more likely than REM reports to be short, dull, and un-
dreamlike (Nielsen 1999; Rechtschaffen et al. 1963).
Many of the above-noted problems inherent in assessing
the similarity versus difference of two phenomena can be
addressed with improved methodologies. For example,
when two states (such as REM and NREM) are being com-
pared in terms of specific parameters (such as bizarreness)
to a third state (such as waking), the question of the simi-
larity versus difference between the two states becomes
much more tractable.
2.3.4. The source and fate of dream memory. A tendency
to emphasize psychological similarity has also characterized
recent studies on the memory sources of REM and NREM
dreams. Using a modification of Tulving and Thomson’s
(1973) classification of memory sources and an experimen-
tal free association technique, Cavallero and his colleagues
initially found a distinct difference in memory sources be-
tween early-night REM and NREM mentation (Bosinelli
1991; Cavallero & Cicogna 1993; Cicogna et al. 1986).
Early-night NREM sources consisted primarily of discrete
biographical episodes while REM sources were a mixture
of episodic, abstract self-referential and semantic sources
(Bosinelli 1991; Cavallero & Cicogna 1993; Cicogna et al.
1986). This observation fits with the commonly accepted
distinction between NREM dreaming as a simpler and
REM dreaming as a more complex state of consciousness.
However, when REM and NREM reports were collected
later in the night and matched for “temporal unit composi-
tion” (a procedure akin to diluting bizarreness by control-
ling for word count), the same researchers emphasized the
similarity of memory sources between REM and NREM
(Bosinelli 1991; Cavallero & Cicogna 1993; Cavallero et al.
1988; 1990; 1992; Cicogna et al. 1991; Fagioli et al. 1989).
Likewise, Cicogna et al. (1991) reported few REM/Stage 2
differences in number of temporal units, implausibility, self
presence, settings or characters. Nonetheless, as in the case
of dream content (Antrobus 1983; Foulkes & Schmidt
1983), some residual state-related memory source differ-
ences continued to be reported (Cavallero & Cicogna 1993;
Cavallero et al. 1990; 1992; Cicogna et al. 1991) and these
need to be explained.
The research on memory sources for mentation among
the different behavioral states overlooks the far more ro-
bust difference in the overall functioning of memory pro-
cesses that distinguishes sleep from waking. This is the no-
torious difficulty of recalling dreams or any other mental
content following either instrumental laboratory or sponta-
neous awakening. Many dreamers are aware that recall ac-
tively eludes them as they awaken. And even when dream
recall is confident and detailed, it is common for subjects to
assert that they are sure that there was much more an-
tecedent dreaming that could not be recalled. One reason
for the neglect of this robust phenomenon is that it is diffi-
cult to study something, in this case memory, that isn’t
there! But the very absence of recall is a datum which any
dream theory must explain, especially in the face of the ro-
bust brain activation in REM sleep!
Freud’s famous explanation was that dream forgetting
was an active function of repression. We have instead at-
tributed this prominent failure of recall to a state depen-
dent amnesia caused by aminergic demodulation of the
sleeping brain (Hobson 1988b). The waking level of amin-
ergic modulation falls to 50% in NREM sleep and to nearly
zero in REM (Hobson & Steriade 1986; Steriade & Mc-
Carley 1990a). It would appear that the intense activation
of REM must overcome this demodulation and persist into
subsequent waking in order for very vivid dreams to be re-
membered. In our view, the low level of production and re-
call of NREM mentation is due to the additive effects of in-
activation and demodulation.
This hypothesis is consonant with subjective experience.
For example, when one introspectively compares recall of
a night’s dreaming with that of a corresponding waking
epoch, one of the most obvious differences lies in the far
greater amount of detail that can be recalled in waking.
Moreover, it is commonplace for long dreams to have com-
plete scene shifts of which the dreamer takes no significant
cognitive account. If such orientational translocations oc-
curred in waking, memory would immediately note the dis-
continuity and seek an explanation for it. This intuitively
convincing difference between memory for dreaming and
memory of waking mentation is confirmed by several em-
pirical studies (see below).
Although the frequent inability to recall dreamed expe-
rience in subsequent waking has been a robust finding in
dream research (Goodenough 1991), there is also strong ev-
idence of deficient memory for prior waking experience in
subsequent sleep. For example, little continuity has been
shown between pre-sleep stimuli and the content of REM
dreaming when this phenomenon has been probed using
the following paradigms:
1. Specific experimental pre-sleep stimuli in the form of
films have little effect on dream content (Cartwright et al.
1969; DeKoninck & Koulack 1975; Foulkes et al. 1967;
Foulkes & Rechtschaffen 1964; Goodenough et al. 1975;
Karacan et al. 1966; Witkin 1969; Witkin & Lewis 1967).
2. Specific experimental pre-sleep stimuli such as static
visual images or altered social milieu are rarely incorporated
into dreams (Carpenter 1987; Orr et al. 1968; Shevrin &
Fisher 1967).
3. Specific pre-sleep waking behavioral or thought ex-
periences are not easily detectable in subsequent dreams
(Bakeland 1971; Bakeland et al. 1968; Breger et al. 1971;
Cartwright 1974b; Hauri 1970).
4. Presleep mentation is infrequently picked up by the
dream process (Rados & Cartwright 1982; Roussy et al.
1996; 1997).
5. Naturalistic daytime events rarely enter dream con-
tent, casting grave doubt on the classical psychoanalytic
concept of day residue as dream instigator (Epstein 1985;
Harlow & Roll 1992).
6. Pre-sleep modification of biological drives or percep-
tual experience has very weak effects on dreaming (Bald-
ridge et al. 1965; Bokert 1968; Dement & Wolpert 1958;
Hobson et al.: Dreaming and the brain
Roffwarg et al. 1978). (For reviews see Arkin & Antrobus
1978 and Cavallero & Cicogna 1993.)
It must, therefore, be concluded that because dreaming
is so little shaped by pre-sleep experience, memory systems
active during REM sleep have extremely poor access to re-
cent waking memories. Even if dreaming is concerned far
more with emotionally salient content than with current
events, it is remarkable that the dream construction process
fails to incorporate recent episodic memories, including
emotionally salient ones, to any significant extent. Two ex-
perimental exceptions to this generality, however, should be
noted. The first involves the practice of dream incubation
whereby focused pre-sleep attention on a specific concern
has been shown to increase its rate of occurrence in subse-
quent dreaming (Saredi et al. 1997). Dream incubation
techniques, however, introduce substantial confounds in
the form of artificially imposed practice effects as well as
the focus on emotionally salient issues. The second in-
volves the finding by Rosenblatt et al. (1992) that signifi-
cantly more of cartoon segments viewed prior to sleep were
recalled following REM versus Stage 2 NREM awakenings,
a difference which disappears if a 30 second pre-reporting
waking delay is interposed after awakening. Following the
arousal-retrieval model of Goodenough (1991), Rosenblatt
et al. attribute this REM-NREM difference to greater
mnemonic capacity immediately following post-REM ver-
sus post-NREM awakenings resulting from greater im-
mediately pre-awakening cortical arousal in REM versus
NREM. Using the semantic priming task, we have re-
cently reported a similarly positive mnemonic effect of
pre-awakening REM versus NREM for associative mem-
ory processes (Stickgold et al. 1999b). Certain forms of
memory, such as generating associations to weakly related
word primes, may, in fact, be preferentially enhanced by
both the activation and the neuromodulatory differences
(see sect. 4) between REM and NREM (Stickgold et al.
1999b). In contrast, greater sleep inertia (Dinges 1990) fol-
lowing NREM awakenings (a phenomenon undoubtedly
reflecting low pre-awakening brain activation) may less se-
lectively impair a wide spectrum of mnemonic processes.
Even within sleep, memory appears impaired. If episodic
experiences within sleep were to persist in the sleeper’s
memory, one would expect greater content and thematic
continuity between contiguous REM periods than more
distant REM periods. But despite the fact that content and
thematic continuity of successive dreams is greater within
the same night than across nights, continuity does not dif-
fer between contiguous and noncontiguous REM periods
of the same night (Cipolli et al. 1987; Fagioli et al. 1989).
We have recently completed three preliminary studies
that seek to quantify aspects of memory within sleep and to
compare sleep memory to waking memory. In the first
study, 27 subjects became aware of and could later recall
three aspects of their memory functioning (semantic, re-
cent, and remote episodic) more often during two waking
experiences than during dreaming. Since both types of wak-
ing experience sampled were much shorter than the dura-
tion of a night’s dreaming, results further support the con-
cept of a mnemonic deficiency in dreaming compared to
waking (Pace-Schott et al. 1997a).
A second study examined perceived duration of dream-
ing. The 22.5 minute median perceived duration of dreams
by 54 subjects was associated with an unexpectedly large
variation. Even ignoring the highest and lowest 10% still
left a 24-fold variation. Such wide variance in a basic mem-
ory function further suggests a profound alteration of mem-
ory processes in dreaming as compared to waking (Stick-
gold et al. 1997a).
In the third study, 11 subjects recorded the processes by
which a total of 103 dreams were recalled. Fifty-two reports
(50%) were recalled in “chunks” (i.e., entire dream seg-
ments were recalled as units). Another 38 reports (37%)
were recalled all at once upon waking and 13 reports (13%)
were recalled gradually. Nine of the 11 subjects reported at
least one dream recalled in chunks, and there were often
significant delays between the recall of different “chunks.”
These results point strongly to the presence of stored
dream memories which cannot be readily accessed on
awakening and further suggests both qualitative and quan-
titative alterations in basic memory processes during and af-
ter dreaming (Stickgold 1998; Stickgold et al. 1997a).
All of the above findings can be regarded as being caused
by the failure of recent episodic memory (as defined by Tul-
ving 1994) in sleep. And as we have noted, recent episodic
memory is weak across wake-sleep and sleep-wake transi-
tions as well as within sleep itself (Pace-Schott et al. 1997b).
We believe that a deficiency of memory in dreaming may
go a long way toward explaining such distinctive and robust
dream phenomena as orientational instability, loss of self-
reflective awareness, and failure of directed thought and at-
2.3.5. Type I versus Type II statistical analyses. In analyz-
ing studies of dream mentation, it is important to under-
stand the nature of the statistical tests employed. In gen-
eral, such tests calculate the probability that a specific null
hypothesis – normally that there is no difference between
two population samples – is or is not true. The most com-
mon statistical tests, that is, Student’s t-test and ANOVA,
measure Type I error, which determines the probability
that the obtained results could be explained by the null hy-
pothesis. When the probability is sufficiently low, normally
less than 0.05, the null hypothesis is rejected and one con-
cludes that the populations are different. Such analyses,
however, provide no information on whether or not the null
hypothesis is true. Thus, while a low p-value provides strong
evidence that the null hypothesis is false, a high p-value
does not necessarily indicate that it is true.
This is relevant to the conclusion of both of the papers
we critiqued above. Antrobus (1983) concluded that “the
global judgment of Dreaming adds little, if anything, to To-
tal Recall Content with respect to the association with the
sleep stages REM and NREM” (p. 567), although his sta-
tistics did confirm a significant contribution (F(1,71) 5
15.9, p , 0.01). Nevertheless, this conclusion formed the
basis of the wider interpretation that the differences be-
tween REM and NREM reports are merely a consequence
of enhanced recall in REM.
In the second paper critiqued, Foulkes and Schmidt (1983)
concluded that global discontinuity “is stage-invariant [and]
never significantly discriminated reports from different
stages of sleep, even in length-uncontrolled comparisons”
(p. 277). Although this was true, it was also true that sleep
onset reports contained 2.3 times more global discontinu-
ity than NREM reports, a ratio that increased to more than
3 to 1 when normalized for report length (measured in
“temporal units”), a fact that could lead to a conclusion
quite different from the one drawn by the authors.
Hobson et al.: Dreaming and the brain
It thus appears premature to conclude, based on these
early studies, that robust differences between REM and
NREM sleep mentation do not exist. Until studies are car-
ried out that measure Type II error and determine the like-
lihood that the null hypothesis is correct, it is only safe to
say that these studies have failed to demonstrate either the
presence or absence of differences between REM and
NREM mentation. Under the circumstances, more recent
studies reporting the presence of significant differences
would appear more easily interpreted.
2.3.6. The need for new approaches. The conclusion that
we draw from all these studies is that there are significant
differences between the formal aspects of the states of con-
sciousness associated with waking, NREM, and REM sleep.
These differences, which are quantitative not qualitative,
have not yet been adequately characterized for a variety of
methodological reasons. Instead of continuing to argue over
this issue, we urge our colleagues to join us in a more cre-
ative attempt to capture and measure the dimensions of
conscious experience.
Basing the attempt to characterize dreaming solely on ver-
bal reports of the poorly recalled subjective experience of
subjects sleeping in unfamiliar, non-natural settings has led,
not surprisingly, to a sterile and nonproductive controversy
about whether the conscious correlates of waking, NREM
sleep, and REM sleep are more similar or different, and to a
very unfortunate split in what was once a unified field.
This mind-brain split is akin to the gulf that opened be-
tween psychiatry and neurology after Sigmund Freud aban-
doned the goals of his brain-based Project for a Scientific
Psychology and declared brain science off limits to his psy-
chology. To reunify two approaches that belong together,
we call for a new neuropsychology of conscious states that
integrates from the level of cellular-molecular events to the
formal features of the mental states of which they form the
3. The cognitive neuroscience of waking,
sleeping, and dreaming
We now turn our attention to the shifts in activation level,
input-output gating processes, and the neuromodulatory
balance of the brain that underlie the ultradian REM/
NREM cycle in humans and in animals. We first enumer-
ate the profound physiological differences that distinctively
differentiate waking, NREM, and REM sleep and show
that these differences are as robust as those shown above in
the phenomenology of waking, sleeping, and dreaming.
Then, we point out relationships between the physiological
and phenomenological changes seen as the brain-mind
shifts from one state to another, as a prelude to integrative
modeling. Our overarching hypothesis is that for each phe-
nomenological difference seen between conscious states it
is possible to identify a specific physiological counterpart.
The end result is a first approximation of a cognitive neu-
roscience of brain-mind states.
3.1. Recent findings in human neurobiology
3.1.1. Neuroimaging studies. The experimental study of hu-
man REM sleep dreaming has until recently been limited on
the physiological side by the poor resolving power of the
EEG. Even expensive and cumbersome evoked potential
and computer averaging approaches have not helped us to
analyze and compare REM sleep physiology with that of wak-
ing in an effective way. This limitation has probably helped
reinforce the erroneous idea that the brain activation of REM
sleep and waking are identical or at least, very similar. How-
ever, recent technological advances in the field of human
brain imaging have made it possible to document a highly se-
lective regional activation pattern of the brain in REM sleep
(Braun et al. 1997; 1998; Maquet et al. 1996; Nofzinger et al.
1997). At the same time, experiments of nature in the form
of strokes have allowed a correlation of the locale of brain
lesions with deficits or accentuations of dream experience in
patients (Doricchi & Violani 1992; Solms 1997a).
Before discussing these intriguing new results, it is im-
portant to stress the methodological limitations of both the
brain lesion and imaging techniques. We know from our
long and relevant experience in basic sleep research that
neither method can capture many significant mechanistic
and functional details that emerge from cellular and mo-
lecular level neurophysiology (see Hobson et al. 1986 and
Steriade & Hobson 1976 for a full discussion of these is-
sues). For example, it is now clear that the lesion method,
applied to the pontine brain stem, gave misleading results
regarding both the general role of that region in state con-
trol and failed even to hint at the specific functions of its
subcomponent nuclei. This is because the lesion method
cannot discriminate between the effects of destruction and
disconnection and cannot target specific neuronal groups in
heterogeneous regions like the brain stem.
It is important to note that the preliminary regional func-
tional neuroimaging studies that we review below suffer from
such unavoidable limitations of new technologies as the fol-
lowing (see Rauch & Renshaw 1995 for a more complete dis-
cussion). First, one must consider whether or not more effi-
cient functioning of an area might result in less versus more
observed metabolism or whether glucose or oxygen uptake by
inhibitory interneurons may produce local maxima in areas
that are, in fact, less active due to inhibition. Second, there are
statistical problems inherent in the small sample sizes used in
some of these sleep studies (e.g., Braun et al. 1998; Nofzinger
et al. 1997) as well as the repeated comparisons employed by
the statistical parametric mapping technique (Friston et al.
1991), which is used by all these investigators. Third, global
activation measures like electroencephalographic voltage av-
eraging or cerebral blood flow cannot be expected to reveal
mechanistic and functional details because they cannot iden-
tify small but influential neuronal populations like the locus
coeruleus, the raphe nuclei and the pedunculopontine
tegmental nucleus. Fourth, there is the potential of altered
sleep physiology due to the sleep deprivation (Maquet et al.
1996) or REM deprivation (Braun et al. 1997; 1998) proce-
dures used to maximize sleep stability and stimulate REM in
these studies. And fifth, the functional activity of a brain area
may vary with changes in its inputs as most dramatically illus-
trated by neuroplasticity involving recruitment of dedicated
brain areas to subserve new modalities such as the visual cor-
tex in Braille learning (e.g., Pascual-Leone 1999) or the reor-
ganization of visual association cortex following V1 damage
(e.g., Baeseler et al. 1999). Additionally, it is possible that nor-
mal functional disconnections, as occurs between V1 and vi-
sual association cortices in REM (Braun et al. 1998), result
in the same neural structures performing differing, state-
specific functional tasks.
In spite of these caveats, the widespread use of this tech-
Hobson et al.: Dreaming and the brain
Hobson et al.: Dreaming and the brain
nology and the broad agreement of the data with clinical
neuropsychological findings argues strongly for the basic
validity of neuroimaging as a tool in cognitive neuroscience
(Cabeza & Nyberg 1997; 2000). Specifically in response to
the fifth caveat above, strong suggestion that the functions
of specific brain areas are similar between REM and wake
is provided by the observable enactment of experienced
dream movement in the REM sleep behavior disorder
(Schenck et al. 1993). Moreover, wake-like function of re-
gional brain areas is preserved in many abnormal states
such as focal motor activity during seizures (Adams et al.
1997) or the recruitment of visual association cortex during
visual hallucinations (Ffytche et al. 1998; Silbersweig et al.
1995). In future sleep research, many of these limitations
may be overcome by the finer temporal and spatial resolu-
tion offered by functional MRI (fMRI) imaging (e.g., Ellis
et al. 1999; Huang-Hellinger et al. 1995; Ives et al. 1997;
Sutton et al. 1996; 1997; 1998; Lovblad et al 1999).
Our review of this new literature is undertaken with these
shortcomings in mind. Three factors weighed heavily in our
evaluation of these data: (1) their novelty and uniqueness in
beginning to describe the role of forebrain subsystems; (2)
the surprising concordance in the neuroimaging results that
emerged from studies carried out simultaneously by three
independent groups; and (3) the complementarity between
the lesion and imaging studies that confer the value of a dou-
ble dissociation on the validity of the inferences drawn.
3.1.2. PET studies indicating regional activation differ-
ences between REM sleep and waking.
Two very recent and
entirely independent PET studies confirm the importance of
the pontine brain stem in REM sleep brain activation (Braun
et al. 1997; Maquet et al. 1996). This is an important advance
because it validates, for the first time, the experimental ani-
mal data on the critical and specific role of the pontine brain
stem in REM sleep generation. At the same time, these new
studies also provide important new data for our understand-
ing of dream synthesis by the forebrain. Instead of the global,
regionally nonspecific picture of forebrain activation that has
been suggested by EEG studies, all of these new imaging
studies indicate a preferential activation of limbic and paral-
imbic regions of the forebrain in REM compared to waking
(Braun et al. 1997; 1998; Maquet et al. 1996; Nofzinger et al.
1997). One implication of these discoveries is that dream
emotion may be a primary shaper of dream plots rather than
playing a secondary role in dream plot instigation. The PET imaging findings of the Maquet group.
Maquet et al. (1996) used an H
O positron source to
study REM sleep activation in their subjects who were then
awakened for the solicitation of dream reports. In addition
to the pontine tegmentum, significant activation was seen
in both amygdalae and the anterior cingulate cortex (Table
2). Significantly, despite the general deactivation in much
of the parietal cortex, Maquet et al. (1996) reported activa-
tion of the right inferior parietal lobe (Bredman area 40) –
a brain region thought to be important for spatial imagery
construction, an important aspect of dream cognition. The
authors interpreted their data in terms of the selective pro-
cessing, in REM, of emotionally influenced memories (see
also Braun et al. 1997; Maquet & Franck 1997). The PET imaging findings of the Braun group. In
another H
0 PET study, Braun et al. (1997) largely rep-
licated the Maquet group’s findings of a consistent REM-
related brainstem, limbic, and paralimbic activation. In REM
compared individually to delta NREM and to pre- and post-
sleep waking (see Table 2), these authors showed relative ac-
tivation of the pons, midbrain, anterior hypothalamus, hip-
pocampus, caudate, and medial prefrontal, caudal orbital,
anterior cingulate, parahippocampal, and inferior temporal
cortices (Braun et al. 1997). Based on their observations, the
Braun group then offered the following speculations which
are relevant to the neurology of dreaming:
(1) Ascending reticular activation during REM as com-
pared to waking may favor a more ventral cholinergic route
leading from the brainstem to the basal forebrain over a
more dorsal route via the thalamus.
(2) Activation of the cerebellar vermis in REM may re-
flect input to this structure from the brainstem vestibular nu-
clei. We note that these nuclei also constitute an important
potential source of neuronal activation causing the unique
vestibular features of fictive movement in dreams (Hobson
et al. 1998c; Leslie & Ogilvie 1996; Sauvageau et al. 1998).
(3) Noting both a particularly strong REM sleep-related
activation of the basal ganglia and the known connectivity
of these subcortical structures, Braun et al. suggest that the
basal ganglia may play an important role in an ascending
thalamocortical activation network. They suggest that this
network extends successively from the brainstem to the in-
tralaminar thalamic nuclei, then to the basal ganglia, and
back to the ventral anterior and ventromedial thalamic nu-
clei, and thence to the cortex.
This network contains multiple regulatory back projec-
tions including interconnections between the pedunculo-
pontine tegmentum and the striatum further suggesting a
possible role for the basal ganglia in the rostral transmission
of PGO waves and the modulation of REM sleep phenom-
ena. The extensive interconnections of the basal ganglia and
the pedunculopontine area have recently been reviewed by
Rye (1997) and Inglis and Winn (1995). The role of the
basal ganglia in the initiation of motor activity may, in turn,
be related to the ubiquity of motion in dreams (Hobson
1988b; Porte & Hobson 1996).
(4) The REM-associated increase in activation of uni-
modal associative visual (Brodmann areas 19 and 37) and
auditory (Brodmann area 22) cortices contrasted with the
maintained (NREM and REM) sleep-related deactivation
of heteromodal association areas in the frontal and parietal
cortex. Combined with findings of striate cortex deactiva-
tion in REM, this group (Braun et al. 1998) has subse-
quently theorized that, during REM, internal information
is being processed between extrastriate and limbic cortices
while they are functionally isolated from the external world
both in terms of input (from the striate cortex) and output
(via the frontal cortex).
(5) The prominent decrease in the executive portions of
the frontal cortex (dorsolateral and orbital prefrontal cortices)
contrasts with the REM-associated increase in activation of
the limbic associated medial prefrontal area. This medial area
region has the most abundant limbic connections in the pre-
frontal cortex, has been associated with arousal and attention,
and disruption of this area has been shown to cause confabu-
latory syndromes formally similar to dreaming. (Note also the
dream-wake confusional syndrome associated with anterior
limbic cortical lesions reported by Solms 1997a.) The PET imaging findings of the Nofzinger group.
Also confirming widespread limbic activation in REM
Hobson et al.: Dreaming and the brain
sleep, Nofzinger et al. (1997) described increased glucose
utilization in the lateral hypothalamic area and the amyg-
daloid complex using an 18F-fluoro-deoxyglucose (FDG)
PET technique (Table 2). The largest area of activation was,
in their own words, “ . . . an extensive confluent area along
the midline that includes the lateral hypothalamic area, sep-
tal area, ventral striatum-substantia innominata, infralimbic
cortex, prelimbic and orbitofrontal and the anterior cingu-
late cortex . . . Much of this is bilateral” (p. 198). The au-
thors suggest that an important function of REM sleep is
the integration of neocortical function with basal forebrain
and hypothalamic motivational and reward mechanisms.
3.1.3. Selective deactivation of the dorsolateral pre-
frontal cortex in REM sleep.
Relevant to the cognitive
deficits in self-reflective awareness, orientation, and mem-
ory during dreaming was the H
O PET finding of signif-
icant deactivation, in REM, of a vast area of dorsolateral
prefrontal cortex (Braun et al. 1997; Maquet et al. 1996). A
similar decrease in cerebral blood flow to frontal areas dur-
ing REM has been noted by Madsen et al. (1991a) using
single photon emission computed tomography (SPECT)
and by Lovblad et al. (1999) using fMRI. Dorsolateral pre-
frontal deactivation during REM, however, was not repli-
cated by an FDG PET study (Nofzinger et al. 1997) and this
discrepancy, therefore, remains to be clarified by other
FDG as well as H
O studies. (A potential cause of this
discrepancy arising from differences between FDG and
O methods is discussed further in sect.
Nevertheless, it seems likely that considerable portions
of executive and association cortex active in waking may be
far less active in REM, leading Braun et al. (1997) to spec-
ulate that “REM sleep may constitute a state of generalized
brain activity with the specific exclusion of executive sys-
tems which normally participate in the highest order analy-
sis and integration of neural information” (p. 1190).
Taken together, these results strongly suggest that the fore-
brain activation and synthesis processes underlying dreaming
are very different from those of waking. Not only is REM
sleep chemically biased but the preferential cholinergic neu-
romodulation is associated with selective activation of the sub-
cortical and cortical limbic structures (which mediate emo-
tion) and with relative inactivation of the lateral prefrontal
cortex (which mediates directed thought). These findings
greatly enrich and inform the integrated picture of REM
sleep dreaming as emotion-driven cognition with deficient
memory, orientation, volition, and analytic thinking.
The Maquet et al. (Maquet et al. 1996; Maquet & Franck
1997), Nofzinger et al. (1997), and Braun et al. (1997)
groups all stress that their findings suggest assigning REM
sleep a role in the processing of emotion (along with its cog-
nitive and autonomic correlates) in memory systems via a
limbic-cortical interplay. Additionally, PET researchers
suggest the possible origin of dream emotionality in REM-
associated limbic activation (Braun et al. 1997; Maquet &
Franck 1997) and dream-associated executive deficiencies
in REM-associated frontal deactivation (Braun et al. 1997;
Maquet & Franck 1997). Although tantalizing correlations
such as: (1) limbic activation and dream emotionality, (2)
dream emotionality and affect-congruent dream narratives,
and (3) frontal deactivation and dream bizarreness, are now
becoming apparent in the sleep and dream literature, the
precise causal sequence among these phenomena remains
to be established by future research.
Two additional findings support this proposed cortico-
limbic interaction. First, the anterior cingulate cortex has
consistently shown increased activation in REM in other
PET studies (e.g., Bootzin et al. 1998; Buchsbaum et al.
1989; Hong et al. 1995). Second, recent studies of human
limbic structures with depth electrodes during REM sleep
have shown distinctive rhythmic EEG patterns possibly re-
lated to the REM-associated hippocampal theta rhythms
seen in animals (Mann et al. 1997; Staba et al. 1998). Hu-
man frontal midline theta has also been detected using
scalp electrodes (Inanaga 1998).
3.1.4. Global and regional decreases in activation level in
NREM sleep.
Neuroimaging studies also strongly support a
distinction between REM and NREM sleep as states whose
differing neuroanatomical activation patterns predict their
observed phenomenological differences (Table 2). PET
studies of NREM sleep generally show a decrease in global
cerebral energy metabolism (i.e., O
or glucose utilization)
relative to waking and REM (Buchsbaum et al. 1989; Heiss
et al. 1985; Madsen & Vorstup 1991; Madsen et al. 1991b;
1999b; Maquet 1995; Maquet et al. 1990; 1992; 1997). The
magnitude of this decline relative to waking has varied from
11% glucose utilization in stage 2 (Maquet et al. 1992) to
40% glucose utilization in stages 3 and 4 (Maquet et al.
1990). A similar pattern has usually been reported for global
cerebral blood flow as measured by H
near infrared spectroscopy or a modification of the Kety-
Schmidt O
uptake technique (Braun et al. 1997; Hoshi et
al. 1994; Madsen et al. 1991a; 1991b; Maquet et al. 1997;
Meyer et al. 1987; Sakai et al. 1980), although some studies
have failed to show this global hemodynamic change (An-
dersson et al. 1995; 1998; Hofle et al. 1997). In addition,
cerebral energy metabolism decreases with progressively
greater depth of NREM sleep (Maquet 1995) a result re-
cently replicated with fMRI (Sutton et al. 1997). By contrast,
in REM, global cerebral energy metabolism tends to be
equal to (Asenbaum et al. 1995; Braun et al. 1997; Madsen
et al. 1991b; Maquet et al. 1990) or greater than (Buchs-
baum et al. 1989; Heiss et al. 1985) that of waking. Cerebral
blood flow velocity measured in the middle cerebral artery
similarly shows a slowing during NREM followed by values
similar to waking during REM (Droste et al. 1993; Haiak et
al. 1994; Klingelhofer et al. 1995; Kuboyama et al. 1997).
More striking than global patterns are the now well-repli-
cated regional variations in cerebral energy metabolism over
the wake-NREM-REM sleep cycle (Table 2). Earlier stud-
ies showing specific declines in thalamic glucose utilization
in NREM relative to waking (Buchsbaum et al. 1989; Ma-
quet et al. 1990; 1992) have been confirmed by recent oxy-
gen utilization studies (Andersson et al. 1998; Braun et al.
1997; Hofle et al. 1997; Maquet et al. 1997). In addition to
prominent thalamic deactivation, all three recent studies
have found regional deactivation during NREM in the pon-
tine brain stem, orbitofrontal cortex, and anterior cingulate
cortex (Braun et al. 1997; Hofle et al. 1997; Maquet et al.
1997). NREM deactivation of lateral prefrontal cortex was
also observed in some studies (Andersson et al. 1998; Braun
et al. 1997). Thalamic activation was found to decline sig-
nificantly concomitant with increased delta EEG activity
and there was an additional decline associated with in-
creased spindle-frequency activity when the decrements as-
sociated with delta were subtracted (Hofle et al. 1997). (For
a very recent review see Maquet 2000.)
Hobson et al.: Dreaming and the brain
Table 2. Review of relative activation of cortical and subcortical areas in REM and SWS noted in four recent PET studies ( from Hobson 1998a; 2000)
STUDY Maquet Nofzinger Braun et al. Braun et al. Maquet Hofle Braun et al.
et al. 1996 et al. 1996 1997 1997 et al. 1997 et al. 1997 1997
RELATIVE TO all other stages waking pre- (& post*)- NREM 3&4 all other stages change with pre- or post-
sleep waking increased delta sleep waking
pontine tegmentum increase increase (R*) increase decrease decrease:R decrease
midbrain increase* increase decrease
dorsal mesencephalon increase decrease
thalamus increase: L increase decrease decrease: M decrease
hypothalamus increase: R, Lat. increase: A-POA increase: A-POA decrease decrease: A-POA
basal forebrain decrease
limbic system
left amygdala increase increase
right amygdala increase
septal nuclei increase
hippocampus increase* increase
basal ganglia/striatum
caudate increase: A, I, L increase* increase decrease decrease
putamen increase decrease: P
ventral striatum (n. accum- increase increase decrease
bens, sub.innominata)
lenticular nuclei decrease
ebellum incr. (vermis)* increase (vermis) decrease decrease: I
Hobson et al.: Dreaming and the brain
STUDY Maquet Nofzinger Braun et al. Braun et al. Maquet Hofle Braun et al.
et al. 1996 et al. 1996 1997 1997 et al. 1997 et al. 1997 1997
TECHNIQUE all other stages waking pre or post- NREM 3&4 all other stages change with pre or post-
RELATIVE TO sleep waking increase delta sleep waking
FRONTAL decrease: L, small areas
increase: R
dorsolateral prefrontal decrease: increase decrease: 46* decrease: 46
L: 10,11,46,47
R: 8,9,10,11,46
opercular decrease: 45* decrease: 45
paraolfactory increase
lateral orbital increase: 11,12 decrease: 11* decrease: 11,25 decrease: R 11 decrease: 11
medial orbital decrease: R
caudal orbital increase increase decrease
gyrus rectus increase
Brodmann area 40 increase: R A 40 decrease: 40* increase: L 40 decrease: 40
(supramarginal gyrus) decrease: L 40
angular gyrus decrease: 39* decrease: 39
precuneus decrease decrease: 7
cuneus decrease: 19
pericentral increase: L 3/4
mesiotemporal decrease: R 28
middle increase R incr: A R,L 21
posterior superior increase: 22 increase: L 22
inferior/fusiform increase: 37,19 increase 37,19
(post-sleep only)
OCCIPITAL decrease: L, small areas
medial incr: R 17/18
incr: L 17
post-rolandic sensory increase
medial (prelimbic) prefrontal increase: R 32 increase: 10 increase: 10 decrease: 10
anterior cingulate increase: 24 increase: 24 increase: 32* increase: 32 decrease: 24,32 decrease: 24/32 decrease: 32
posterior cingulate decrease: 31 dec.: R sm. areas decrease*
infralimbic increase: 25
insula increase: L decrease: P increase: A I decrease: A
parahippocampal increase increase: 37* increase: 37
entorhinal increase increase (in fusiform)
temporal pole increase: 38 decrease: 38
Abbr: L-left hemisphere; R-right hemisphere; A-anterior; P-posterior; C-caudal; M-medial; Lat.-lateral; I-inferior; S-superior; A-POA-anterior preoptic area; all numerals = Brodmann’s
area; sm.-small, dec.-decrease, inc.-increase.
Hofle et al. (1997) and Maquet et al. (1997) both inter-
pret this pattern of decline as reflecting the progressive de-
activation of the reticular activating system (RAS) that ac-
companies deepening NREM sleep. This deactivation leads
to dysfacilitation of thalamocortical relay neurons, which al-
lows the emergence of underlying thalamocortical oscilla-
tory rhythms (Steriade & McCarley 1990a; Steriade et al.
1993a; 1993b; 1993c; 1993d; 1994; for recent reviews see
Steriade 1997; 1999; 2000). GABAergic neurons of the thal-
amic reticular nucleus then further hyperpolarize and dys-
facilitate thalamic relay neurons as NREM deepens (Steri-
ade et al. 1994). In this hyperpolarized condition, thalamic
neurons become constrained to burst firing patterns first in
spindle (1214 Hz) and later in delta (14 Hz) frequencies
as NREM deepens from Stage 2 to delta sleep (Steriade et
al. 1993a; 1993d). The cortex may further constrain these
spindle and delta-wave-generating thalamocortical bursts
within a newly described slow (,1 Hz) oscillation seen in
cats (Steriade et al. 1993a; 1993b; 1993c; 1993d) and hu-
mans (Achermann & Borbely 1997). In conclusion, the
metabolic decline seen during NREM is centered on the
central core structures (brain stem, thalamus) which are
known to play a role in generation of the slow oscillations of
NREM sleep (Maquet 2000; Maquet et al. 1997).
The regional pattern of deactivation in NREM, there-
fore, sharply contrasts with the regional activation of these
same regions (i.e., thalamus, pontine brain stem, anterior
cingulate cortex) in REM (Braun et al. 1997; Maquet et al.
1996; Nofzinger et al. 1997). Details of these stage-related
differences are shown in Table 2. Note that a recent cat
study has shown a similar pattern of brain glucose metabo-
lism in REM (Lydic et al. 1991a).
3.1.5. Interpreting the PET imaging results with respect to
the psychophysiology of dreaming.
According to PET re-
searchers, regional activation during REM may reflect a spe-
cific activation of subcortical and cortical arousal and limbic
structures for the adaptive processing of emotional and moti-
vational learning (Maquet et al. 1996; Nofzinger et al. 1997).
Such processing may, in turn, account for the emotionality
and psychological salience of REM dreaming (Braun et al.
1997). Some support for this comes from a PET (glucose)
study showing correlation between content-analyzed dream
anxiety and medial frontal activation (Gottschalk et al. 1991a).
In summary, the markedly differing physiology of wake,
NREM, and REM cerebral activation should be reflected in
the respective phenomenology of mentation reported from
these three conscious states. More particularly, the specific
phenomenology of REM mentation may reflect the neuro-
biologically specific brain activation pattern. Nofzinger et al.
(1997) conclude that “the current findings of increased lim-
bic and paralimbic activation during REM sleep . . . as well
as global, regionally nonselective cortical deactivation and
decreased metabolism during NREM sleep, are generally
supportive of the traditional notion that more story-like af-
fect-laden dreams are more attributable to the REM sleep,
than NREM sleep behavioral state” (p. 199).
3.1.6. Brain lesions resulting in loss or alteration of
dreaming. Solms’s nosology for lesion-related disorders of
A set of findings and conclusions which have
proved remarkably complementary to the neuroimaging re-
sults have been reached following a neuropsychological
survey of 332 clinical cases of cerebral lesions as well as a
review of 73 extant publications on the dreaming-related
sequelae of cerebral injury (Solms 1997a). Using these wel-
come and long overdue neuropsychological data, Solms
proposes a new nosology for the brain-lesion related disor-
ders of dreaming.
In one syndrome, “global anoneria,” total cessation of
dreaming in patients (whose normal waking vision is pre-
served) results from either posterior cortical or deep bilat-
eral frontal lesions. The posterior global anoneria syndrome
results from lesions of the inferior parietal lobes in either
hemisphere, with lesions to Brodmann’s areas 39 and 40 be-
ing the most restricted damage sufficient to produce the
syndrome. The anterior variant of global anoneria results
from deep medial frontal damage resulting in the discon-
nection of the mediobasal frontal cortex from the brain
stem and diencephalic limbic regions. In this syndrome, bi-
lateral damage to white matter in the vicinity of the frontal
horns of the lateral ventricles was the most restricted site
causing the syndrome.
The nosological distinction of a second syndrome, non-vi-
sual dreaming, from syndromes of global cessation of dream-
ing, was first systematically formulated by Doricchi and Vi-
olani (1992). In this syndrome, termed “visual anoneria” by
Solms (1997a), bilateral medial occipito-temporal lesions
produce full or partial loss of dream visual imagery (again
with normal waking vision). Among his own patients, a de-
crease in the “vivacity” of dreaming was reported by two pa-
tients with damage to the seat of normal vision in the medial-
occipital-temporal cortex (especially areas V3, V3a, and V4
but not V1, V5, or V6). Notably, a correlate of visual anone-
ria was visual irreminiscence, the inability to produce men-
tal imagery in waking. In addition, partial variants of visual
anoneria exist which involve selective loss of particular visual
elements (e.g., “kinematic anoneria” or “facial anoneria”).
In addition to these two disorders of attenuated dream-
ing, Solms reported another interrelated pair of symptom
complexes that combined increased frequency and inten-
sity of dreaming. He suggested that increased vivacity and
frequency of dreaming was associated with anterior limbic
lesions while recurring nightmares are associated with tem-
poral seizures. Conclusions suggested by convergent PET and
lesion findings.
We believe that these findings map partic-
ularly well onto the neuroimaging findings on REM. For
example, extrastriate visual cortex is activated during REM
(Braun et al. 1997; 1998) and lesions to this region produce
the distinctive dream deficits of full or partial visual anone-
ria (Solms 1997a). In contrast, the striate visual cortex is de-
activated during REM (Braun et al. 1998) while lesions to
this region do not affect dreaming (Solms 1997a). Similarly,
the seat of spatial cognition in the inferior parietal cortex
(BA 40) is activated in the right (but not the left) hemi-
sphere during REM (Maquet et al. 1996) while damage to
this region, especially on the right, is sufficient to produce
global anoneria (Solms 1997a). Moreover, much of the lat-
eral prefrontal area is deactivated during REM (Braun et
al. 1997; Maquet et al. 1996), while lesions to this region do
not affect dreaming (Doricchi & Violani 1992; Solms 1997a).
Two exceptions to this general correspondence involve
lesions of the brainstem (for which Solms reports no atten-
uation of dreaming) and lesions of the rostral limbic system
(for which Solms reports an accentuation of dreaming). In
Hobson et al.: Dreaming and the brain
the case of pontine lesions, we suggest that any lesion ca-
pable of destroying the pontine REM sleep generator
mechanism would have to be so extensive as to eliminate
consciousness altogether. We base this caveat upon the dif-
ficulty of suppressing REM by experimental lesions of the
pons in animals. In the case of the rostral limbic system, we
caution that lesions there could as well be irritative as de-
structive and that lesions in different areas of this function-
ally highly heterogeneous region (Devinsky et al. 1995)
could produce dramatically different effects.
3.2. Reciprocal interaction: A neurobiological update
The discovery of the ubiquity of REM sleep in mammals pro-
vided the brain side of the brain-mind state question with an
animal model (Dallaire et al. 1974; Dement 1958; Jouvet &
Michel 1959; Jouvet 1962; 1999; Snyder 1966). While animal
studies showed that potent and widespread activation of the
brain did occur in REM sleep, it soon became clear that
Moruzzi and Magoun’s concept of a brain stem reticular ac-
tivating system (Moruzzi & Magoun 1949) required exten-
sion and modification to account for the differences between
the behavioral and subjective concomitants of waking and
those of REM sleep (see Hobson & Brazier 1981).
3.2.1. Implications for dream theory. We take the theoret-
ical position that it is the cellular and molecular level brain
events to be discussed that bias the brain to produce the
conscious state differences that contrast waking, NREM,
and REM sleep. As we will point out in detail in section 4
when we develop the AIM model, the shift from aminergic
dominance in waking to cholinergic dominance in REM
lowers the probability that consciousness will be exterore-
ceptive, logical, and mnemonic while correspondingly rais-
ing the probability that consciousness will be interoceptive,
illogical, and amnesic.
3.2.2. Behavioral state-dependent variations in neuro-
A conceptual breakthrough was made possible
by the discovery of the chemically specific neuromodulatory
subsystems of the brain stem (e.g., Dahlstrom & Fuxe 1964;
for reviews see Foote et al. 1983; Gottesmann 1999; Hob-
son & Steriade 1986; Hobson et al. 1998; Jacobs & Azmita
1992; Lydic & Baghdoyan 1999; Mallick & Inoue 1999; Rye
1997; Steriade & McCarley 1990a) and of their differential
activity in waking (noradrenergic and serotonergic systems
on, cholinergic system damped) and REM sleep (noradren-
ergic and serotonergic systems off, cholinergic system un-
damped) (Aston-Jones & Bloom 1981; Cespuglio et al. 1981;
Chu & Bloom 1973; 1974; Hobson et al. 1975; Jacobs 1986;
Lydic et al. 1983; 1987; McCarley & Hobson 1975; McGinty
& Harper 1976; Rasmussen et al. 1986; Reiner 1986; Steri-
ade & McCarley 1990a; Trulson & Jacobs 1979). The original reciprocal interaction model: an
aminergic-cholinergic interplay.
The model of reciprocal
interaction (McCarley & Hobson 1975) provided a theo-
retical framework for experimental interventions at the cel-
lular and molecular level that has vindicated the notion that
waking and dreaming are at opposite ends of an aminergic-
cholinergic neuromodulatory continuum, with NREM sleep
holding an intermediate position (Fig. 2). The reciprocal in-
teraction hypothesis (McCarley & Hobson 1975) provided
a description of the aminergic-cholinergic interplay at the
synaptic level and a mathematical analysis of the dynamics
of the neurobiological control system (Figs. 2 and 3A). In
this section we review subsequent work that has led to the
alteration (Fig. 3B) and elaboration (Fig. 4) of the model.
Although there is abundant evidence for a pontine peri-
brachial cholinergic mechanism of REM generation cen-
tered in the pedunculopontine (PPT) and laterodorsal
tegmental (LDT) nuclei (for recent reviews see Datta 1995;
1997b; 1999; Hobson 1992b; Hobson et al. 1993; Lydic &
Baghdoyan 1999; Rye 1997), not all pontine PPT and LDT
neurons are cholinergic (Kamodi et al. 1992; Kang & Kitai
1990; Leonard & Llinas 1990; 1994; Sakai & Koyama 1996;
Steriade et al. 1988) and cortical acetylcholine release may
be as high during wakefulness as during sleep (e.g., Jasper
& Tessier 1971; Jimenez-Capdeville & Dykes 1996; Mar-
rosu et al. 1995).
Recently, reciprocal interaction (McCarley & Hobson
1975) and reciprocal inhibition (Sakai 1988) models for
control of the REM sleep cycle by brain stem cholinergic
Hobson et al.: Dreaming and the brain
Figure 2. The original Reciprocal Interaction Model of physio-
logical mechanisms determining alterations in activation level. A:
Structural model of Reciprocal Interaction. REM-on cells of the
pontine reticular formation are cholinoceptively excited and/or
cholinergically excitatory (ACH1) at their synaptic endings. Pon-
tine REM-off cells are noradrenergically (NE) or serotonergically
(5HT) inhibitory (2) at their synapses. B: Dynamic Model. Dur-
ing waking, the pontine aminergic system is tonically activated and
inhibits the pontine cholinergic system. During NREM sleep,
aminergic inhibition gradually wanes and cholinergic excitation
reciprocally waxes. At REM sleep onset, aminergic inhibition is
shut off and cholinergic excitation reaches its high point. C: Acti-
vation level. As a consequence of the interplay of the neuronal sys-
tems shown in A and B, the net activation level of the brain (A) is
at equally high levels in waking and REM sleep and at about half
this peak level in NREM sleep. (Taken from Hobson 1992a.)
and aminergic neurons have been questioned (Leonard &
Llinas 1994). Specifically, the self-stimulatory role of acetyl-
choline on pontine PGO-bursting neurons has not been
confirmed in in vitro slice preparations (Leonard & Llinas
1994). For example, ACh has been shown to hyperpolarize
cell membranes in slice preparations of the rodent para-
brachial nucleus (Egan & North 1986a), LDT (Leonard &
Llinas 1994; Luebke et al. 1993), and PPT (Leonard & Lli-
nas 1994). Similarly, LDT and PPT neurons with burst dis-
charge properties most like those hypothesized to occur in
PGO-burst neurons (“type I” neurons) may not be cholin-
ergic (Leonard & Llinas 1990). Much evidence remains,
however, that the reciprocal interaction model accurately
describes essential elements of REM sleep cycle control
even though some of its detailed synaptic assumptions need
correction (Fig. 3B).
Hobson et al.: Dreaming and the brain
Figure 4. Additional synaptic details of the revised reciprocal in-
teraction model shown in Figure 3B derived from data reported
(solid lines) and hypothesized relationships suggested (dotted
lines) in recent experimental studies (numbered on Figure and be-
low). See text for discussion of these findings. Additional synaptic
details can be superimposed on the revised reciprocal interaction
model without altering the basic effects of aminergic and cholin-
ergic influences on the REM sleep cycle. Excitatory cholinergic-
non-cholinergic interactions utilizing Ach and the excitatory amino
acid transmitters enhance firing of REM-on cells (6, 7) while inhib-
itory noradrenergic (4), serotonergic (3), and autoreceptor cholin-
ergic (1) interactions suppress REM-on cells. Cholinergic effects
upon aminergic neurons are both excitatory (2), as hypothesized
in the original reciprocal interaction model and may also operate
via presynaptic influences on noradrenergic-serotonergic as well
as serotonergic-serotonergic circuits (8). GABAergic influences
(9, 10) as well as other neurotransmitters such as adenosine and
nitric oxide (see text) may contribute to the modulation of these
interactions. Abbreviations: open circles, excitatory postsynap-
tic potentials; closed circles, inhibitory postsynaptic potentials;
mPRF, medial pontine reticular formation; PPT, pedunculopon-
tine tegmental nucleus; LDT, laterodorsal tegmental nucleus; LCa
peri-locus coeruleus a; 5HT, serotonin; NE, norepinephrine;
Ach, acetylcholine; GL, glutamate; AS, aspartate; GABA, gamma-
aminobutyric acid. References: (1) Baghdoyan et al. 1997; El Man-
seri et al. 1990; Kodama & Honda 1996; Leonard & Llinas 1990;
1994; Luebke et al. 1993; Roth et al. 1996; Sakai & Koyama 1996;
Sakai et al. 1990. (2) Egan & North 1985; 1986b. (3) Horner et al.
1997; Leonard & Llinas 1994; Luebke et al. 1992; Thakkar et al.
1997. (4) Sakai & Koyama 1996. (5) Portas et al. 1996. (6) Sakai &
Koyama 1996; Sakai & Onoe 1997; Vanni-Mercier et al. 1989; Ya-
mamoto et al. 1990a; 1990b. (7) Greene & McCarley 1990; Leo-
nard & Llinas 1994; Sakai & Koyama 1996. (8) Li et al. 1997. (9)
Nitz & Siegel 1997; Datta 1997b; Datta et al. 1991. (10) Porkka-
Heiskanen et al. 1997a (from Hobson et al. 1998b).
Figure 3. Synaptic modifications of the original reciprocal in-
teraction model based upon recent findings. A: The original model
proposed by McCarley and Hobson (1975) and detailed in Figure
2. B: Synaptic modifications of the original reciprocal interaction
model based upon recent findings of self-inhibitory cholinergic
autoreceptors in mesopontine cholinergic nuclei and excitatory
interactions between mesopontine cholinergic and noncholiner-
gic neurons (see Fig. 4 for more detail and references). Note that
the exponential magnification of cholinergic output predicted by
the original model (Fig. 2) can also occur in this model with mu-
tually excitatory cholinergic-noncholinergic interactions taking
the place of the previously postulated, mutually excitatory cholin-
ergic-cholinergic interactions. In the revised model, inhibitory
cholinergic autoreceptors would contribute to the inhibition of
LDT and PPT cholinergic neurons, which is also caused by nor-
adrenergic and serotonergic inputs to these nuclei. Therefore the
basic shape of reciprocal interaction’s dynamic model (illustrated
in Fig. 2B) and its resultant alternation of behavioral state (illus-
trated in Fig. 2C) could also result from the revised model. Ab-
breviations: open circles, excitatory postsynaptic potentials; closed
circles, inhibitory postsynaptic potentials; RN, dorsal raphe nu-
cleus; LC, locus coeruleus; mPRF, medial pontine reticular for-
mation; PPT, pedunculopontine tegmental nucleus; LDT, latero-
dorsal tegmental nucleus; 5HT, serotonin; NE, norepinephrine;
Ach, acetylcholine; glut, glutamate. New findings supporting the cholinergic en-
hancement of REM sleep.
Numerous findings confirm the
hypothesis that cholinergic mechanisms are essential to
the generation of REM sleep and its physiological signs
(for recent reviews see Capece et al. 1999; Datta 1995;
1997;1999; Gottesmann 1999; Hobson 1992b; Hobson et
al. 1986; 1993; Hobson & Steriade 1986; Lydic & Bagh-
doyan 1999; Jones 1991; 1998; Mallick & Inoue 1999; Mc-
Carley et al. 1995; 1997; Rye 1997; Sakai 1988; Semba
1999; Steriade & McCarley 1990a). A selection of the many
recent examples follows:
1. Microinjection of cholinergic agonist or cholinester-
ase inhibitor into many areas of the paramedian pontine
reticular formation induces REM sleep (Baghdoyan et al.
1987; 1989; Hobson et al. 1993; Vanni-Mercier et al. 1989;
Velazquez-Moctezuma et al. 1989; 1991; Yamamoto et al.
1990a; 1990b). In addition to these short term REM in-
duction sites, carbachol injection into a pontine site in the
caudal peribrachial area has been shown to induce long-
term (over 7 days) REM enhancement (Calvo et al. 1992;
Datta et al. 1992; 1993).
2. Cholinergic (type II and III) PPT and LDT neurons
have firing properties which make them well suited for the
tonic maintenance of REM (Leonard & Llinas 1990).
3. PGO input to the LGB is cholinergic (Steriade et al.
1988) and can be antidromically traced to pontine PGO-
burst neurons (Sakai & Jouvet 1980). Retrograde tracers in-
jected into the thalamus label 50% or more of cholinergic
PPT/LDT neurons (Oakman et al. 1999; Rye 1997). More-
over, stimulation of mesopontine neurons induces depo-
larization of cortically projecting thalamic neurons (Curro-
Dossi et al. 1991).
4. PGO waves can be blocked by cholinergic antagonists
(Hu et al. 1989) and neurotoxic lesions of pontomesen-
cephalic cholinergic neurons reduce the rate of PGO spik-
ing (Webster & Jones 1988).
5. PPT and LDT neurons show specifically c-fos and fos-
like immunoreactivity following carbachol-induced REM
sleep (Shiromani et al. 1995; 1996).
6. Low amplitude electrical stimulation of the LDT en-
hances subsequent REM sleep (Thakkar et al. 1996).
7. Electrical stimulation of the cholinergic LDT evokes
excitatory post synaptic potentials (EPSPs) in pontine retic-
ular formation neurons which can be blocked by scopo-
lamine (Imon et al. 1996).
8. The excitatory amino acid, glutamate, when microin-
jected into the PPT dose-dependently increases REM
sleep (Datta 1997a; Datta & Siwek 1997).
9. Microdialysis studies showed enhanced release of en-
dogenous acetylcholine in the medial pontine reticular for-
mation during natural (Kodama et al. 1990) and carbachol-
induced (Lydic et al. 1991b) REM sleep.
10. Thalamic ACh concentration of mesopontine origin
is higher in wake and REM than in NREM (Williams et al.
1994), a REM-specific increase of ACh in the lateral genic-
ulate body has been observed (Kodama & Honda 1996),
and both muscarinic and nicotinic receptors participate in
the depolarization of thalamic nuclei by the cholinergic
brainstem (Curro-Dossi et al. 1991).
11. Although in vivo cholinergic REM enhancement has
been difficult to demonstrate in rats (Deurveiller et al.
1997), such enhancement has recently been reported
(Datta et al. 1998; Marks & Birabil 1998) and a specific car-
bachol-sensitive site in the dorsal locus subcoeruleus of rats
has recently been described (Datta et al. 1998). Moreover,
rats that are genetically supersensitive to ACh show en-
hanced REM sleep (Benca et al. 1996).
12. The new presynaptic anticholinergic agents have
been shown to block REM (Capece et al. 1997: Salin-
Pascual et al. 1995).
13. Muscarinic activation by carbachol has been shown
to increase G-protein binding in brainstem nuclei associ-
ated with REM sleep (Capece et al. 1998).
14. Cholinergic PPT neurons have now been quantita-
tively mapped in the human pontine brainstem (Manaye et
al. 1999).
It may not be an exaggeration to state that the evidence
for cholinergic REM sleep generation is now so over-
whelming and so widely accepted that this tenet of the re-
ciprocal interaction model is an established principle. (For
a recent review see Semba 1999.) New findings supporting the serotonergic and
noradrenergic suppression of REM sleep.
But what about
the essence of the theory: the idea that cholinergic REM
sleep generation can only occur when the noradrenergic
and serotonergic mediators of waking release their in-
hibitory constraint? The evidence for inhibitory serotoner-
gic and noradrenergic influences on cholinergic neurons
and REM sleep is now also quite strong. For example:
1. Serotonergic neurons have been shown to project to
the LDT and PPT (Honda & Semba 1994; Steininger et al.
1997) and serotonin has been shown to hyperpolarize rat
cholinergic LDT cells in vitro (Leonard & Llinas 1994;
Luebke et al. 1992) and to reduce REM sleep percent in
vivo (Horner et al. 1997).
2. Serotonin has been shown to counteract the REM-
like carbachol-induced atonia of hypoglossal motoneurons
(Kubin et al. 1994; 1996; Okabe & Kubin 1997).
3. Extracellular levels of serotonin are higher in waking
than in NREM and higher in NREM than REM in the hy-
pothalamus (Auerbach et al. 1989; Imeri et al. 1994), dor-
sal raphe (Portas et al. 1998) and frontal cortex (Portas
et al. 1998) of rats, as well as the dorsal raphe (Portas &
McCarley 1994) and medial pontine reticular formation
(Iwakiri et al. 1993) of cats. And, the same pattern of extra-
cellular serotonin concentration change over the sleep-
wake cycle has recently been demonstrated in the human
amygdala, hippocampus, orbitofrontal cortex, and cingulate
cortex (Wilson et al. 1997).
4. Microinjection of the serotonin agonist 8-OH-DPAT
into the peribrachial region impeded REM initiation in cats
(Sanford et al. 1994b) and systemic injection of 8-OH-
DPAT into serotonin-depleted rats also suppressed REM
(Monti et al. 1994). However, localization of the serotoner-
gic REM suppressive effect to the PPT/LDT has recently
been challenged in favor of an amygdalar-pontine interac-
tion (Morrison et al. 1999; Sanford et al. 1996; 1998b).
5. Microinjection with simultaneous unit recording has
shown that 8-OH-DPAT suppresses the firing of REM-on
but not REM-and-Wake-on cells of the cholinergic LDT
and PPT (Thakkar et al. 1997; 1998).
6. In vivo microdialysis of serotonin agonists into the
dorsal raphe nucleus (DRN) decreased DRN levels of sero-
tonin (presumably via serotonin autoreceptors on DRN
cells), which in turn increased REM sleep percent (Portas
et al. 1996; Thakkar et al. 1998).
7. Electrical stimulation of the pons in the vicinity of the
Hobson et al.: Dreaming and the brain
(noradrenergic) locus coeruleus reduced REM sleep in rats
(Singh & Mallick 1996) and locus coeruleus neurons have
been shown to become quiescent during REM in the mon-
key (Rajkowski et al. 1997).
8. The alpha-2 noradrenergic agonist clonidine suppresses
REM in human subjects (Gentili et al. 1996; Nicholson &
Pascoe 1991) and the cat (Tononi et al. 1991) while the no-
radrenergic antagonist idazoxan increases REM when in-
jected into the pontine reticular formation of cats (Bier &
McCarley 1994).
9. There is near universal suppression of REM sleep in
humans by acute dosage of serotonin and norepinephrine
reuptake-inhibiting antidepressants (Gaillard et al. 1994;
Nicholson et al. 1989; Vogel 1975; Vogel et al. 1990).
10. Mesopontine injection of a serotonin agonist de-
pressed ACh release in the lateral geniculate body (Kodama
& Honda 1996).
It can therefore also be stated that aminergic suppression
of REM sleep is now an established principle (for recent
reviews see Monti & Monti 1999 and Luppi et al. 1999a;
1999b). Modification of the original reciprocal interaction
hypothesis to accommodate new findings.
of simple reciprocal inhibition or interaction models, which
are consonant with recent findings, have been proposed
for the brain stem control of REM sleep. For example,
Leonard and Llinas (1994) suggest in regard to the Mc-
Carley and Hobson (1975) model that “indirect feedback”
excitation via cholinergic inhibition of an inhibitory input or
cholinergic excitation of an excitatory input or some com-
bination of the two could replace direct feedback excitation
in their model” (p. 327). A similar mutually excitatory or
mutually inhibitory interaction between REM-on choliner-
gic and REM-on noncholinergic mesopontine neurons has
also been proposed in the cat (Sakai & Koyama 1996). Such
a mechanism is depicted in Figures 3B and 4.
From recent in vitro studies in the rat, the following
modification of reciprocal interaction has been proposed
proposed by Li et al. 1997 (see Fig. 4). During waking, pre-
synaptic nicotinic facilitation of excitatory locus coeruleus
noradrenergic inputs to the dorsal raphe enhances sero-
tonergic firing. During REM, when the locus coeruleus is
silent, the same presynaptic nicotinic input may facilitate
serotonergic self-inhibition by raphe neurons themselves.
In vivo microdialysis studies of GABA in the cat further
suggests selective suppression of noradrenergic locus co-
eruleus neurons by GABAergic inhibition during REM
(Nitz & Siegel 1997) as can be seen in Figure 4. Both of
these modifications retain one or both of the major tenets
of the reciprocal interaction model: cholinergic facilitation
and aminergic inhibition of REM.
It is important to realize that many of the studies ques-
tioning reciprocal interaction or reciprocal inhibition (e.g.,
Egan & North 1986a; 1986b; Leonard & Llinas 1990; 1994;
Luebke et al. 1993) have been carried out on in vitro rodent
models, and the relationship of these findings to findings on
the in vivo generation of REM sleep signs in the cat is only
in its early stages (Datta 1995; Hobson et al. 1993; Sakai &
Koyama 1996). Moreover, the hyperpolarization by ACh of
cholinergic cells cited in these studies might be explained by
recent findings suggesting the presence of ACh autorecep-
tors that contribute to homeostatic control of cholinergic ac-
tivity (Baghdoyan et al. 1997; El Manseri et al. 1990; Ko-
dama & Honda 1996; Leonard & Llinas 1990; 1994; Roth et
al. 1996; Sakai & Koyama 1996; Sakai et al. 1990). In con-
trast to the hyperpolarization of some mesopontine cholin-
ergic neurons by cholinergic agonists, in vitro studies have
shown the majority of medial pontine reticular formation
(mPRF) to be depolarized by carbachol (e.g., Greene & Mc-
Carley 1990). This suggests that the exponential self-stimu-
latory activation which can be triggered by cholinergic stim-
ulation in diverse meso- and medial pontine sites (Hobson
et al. 1986; 1993; Hobson & Steriade 1986; McCarley et al.
1995; 1997; Steriade & McCarley 1990a) may involve non-
cholinergic excitatory intermediary neurons. Such choliner-
gic self-regulation combined with cholinergic-noncholiner-
gic mutual excitation is illustrated in Figures 3B and 4.
We conclude that the two central ideas of the model are
strongly supported by subsequent research: (1) noradren-
ergic and serotonergic influences enhance waking and im-
pede REM via anticholinergic mechanisms; and (2) cholin-
ergic mechanisms are essential to REM sleep and come
into full play only when the serotonergic and noradrenergic
systems are inhibited. Because many different synaptic
mechanisms could mediate these effects, we now turn our
attention to some intriguing possibilities.
3.2.3. Other neurotransmitter systems. Beyond the origi-
nally proposed cholinergic and aminergic neuronal popula-
tions, many additional neurotransmitter systems may par-
ticipate in the control of REM sleep (see below). Since
1975, much progress has been made in the identification of
other chemically specific neuromodulatory systems show-
ing differential activation with particular behavioral states
or with specific physiological signs within a behavioral state.
We now discuss these new findings in terms of the way that
they modify and extend the reciprocal interaction model.
In the brain stem and diencephalon, other neuromodu-
latory systems may interact with aminergic and cholinergic
systems in the generation of REM sleep and its signs (for
recent reviews see Jones 2000; Lydic & Baghdoyan 1999;
Mallick & Singh 1999; Pace-Schott & Hobson, in press). In
brief summary, these systems include:
1. GABAergic systems (Datta 1995; 1997b; Datta et al.
1991; Holmes & Jones 1994; Holmes et al. 1994; Jones
1991; 1993; Jones & Muhlethaler 1999; Luppi et al. 1999a;
Nitz & Siegel 1997; Porkka-Heiskanen et al. 1997a; Sanford
et al. 1998a; Steriade et al. 1990; Xi et al. 1997; for a recent
review see Mallick et al. 1999);
2. Nitroxergic systems (Burlet et al. 1999; Datta et al.
1997; Leonard & Lydic 1997; Sippel et al. 1999; Williams
et al. 1997; for recent reviews see Burlet et al. 1999 and
Leonard & Lydic 1999);
3. Glutamatergic systems (Bartha et al. 1999; Datta
1997a; Datta & Siwek 1997; Holmes et al. 1994; Inglis &
Semba 1996; Jones 1994; Lai & Siegel 1992; Onoe & Sakai
1995; Rye 1997; Sakai & Koyama 1996; Sanchez & Leonard
4. Glycinergic systems (Chase et al. 1989; Datta 1997b;
Luppi et al. 1999a; Stevens et al. 1996; Yamuy et al. 1999);
5. Histaminergic systems (e.g., Lin et al. 1996; Saper et
al. 1997; Shiromani et al. 1999);
6. Adenosinergic systems (Mackiewicz et al. 1997;
Marks & Birabil 1998; McCarley et al. 1997; Porkka-
Heiskanen et al. 1997a; 1997b; Portas et al. 1997; Rannie et
al. 1994; 1997; Strecker et al. 1997a; 1997b);
7. A wide variety of neuropeptides such as: galanin
Hobson et al.: Dreaming and the brain
(Saper et al 1997; Sherin et al. 1998); orexin (Chemelli et al.
1999; Lin et al. 1999; Piper et al. 1999); vasoactive intestinal
polypeptide (Bourgin et al. 1997; El Kafi et al. 1994; Murck
et al. 1996; Obal et al. 1989; Prospero-Garcia et al. 1993; for
a review see Steiger & Holsboer 1997) and nerve growth fac-
tor (Yamuy et al. 1995) (for a review of such substances see
Inoue et al. 1999a); as well as numerous hormones includ-
ing growth hormone releasing hormone (Zhang et al. 1999),
prolactin (Morrison et al. 1999), and corticotropin releasing
factor (Lai & Siegel 1999). (For a review of hormonal influ-
ences see Krueger et al. 1999; Obal & Krueger 1999.)
8. Dopaminergic systems (de Saint Hilaire et al. 1995;
Gaillard et al. 1994; Gillin et al. 1973; 1978; 1994; Nichol-
son et al. 1989; Nishino & Mignot 1997; Olive et al. 1998;
Post et al. 1974; 1978; Seidel et al.1997).
Numerous roles have been proposed for these neuro-
modulatory systems in the regulation of REM sleep and its
physiological signs. Among the better known findings and
hypotheses are the following:
1. In the initial stages of PGO wave generation, GABA-
ergic and glycinergic cells may inhibit aminergic cells and
thus release the cholinergic PGO-triggering or transmitting
cells (Datta 1995; 1997b; 1999; Jones 1991; Nitz & Siegel
1997; for recent reviews see Mallick et al. 1999 and Luppi
et al. 1999a; 1999b).
2. GABAergic afferents to the PPT and LDT originating
in the substantia nigra pars reticulata (SNr) may exert direct
inhibitory influences on PGO-related cells of these nuclei
(Datta 1999; Datta et al. 1991; Kang & Kitai 1990; Leonard
& Llinas 1990; Maloney & Jones 1997; Rye 1997) and the
spike-bursting pattern in pontine PGO-burst cells may be the
result of excitatory signals impinging on cells that are tonically
inhibited by GABA (Datta et al. 1991; Sanford et al. 1998a;
Steriade et al. 1990). Such excitatory signals may include
corollary discharge from ocular premotor neurons com-
manding REMs (Steriade et al. 1990). In addition, GABAer-
gic mechanisms may be involved in the medullary control of
muscle atonia during REM (Holmes & Jones 1994).
3. Pontine glutamatergic cells may transmit REM sleep
atonia-related signals to medullary sites (Lai & Siegel 1992;
1999; Rye 1997).
4. Medullary glycinergic cells may then affect the post-
synaptic inhibition of somatic motoneurons during REM
atonia (Chase et al. 1989). Glycinergic neurotransmission is
also involved in the pre-motor functions of the pons (Gottes-
mann 1997; Stevens et al. 1996).
5. Adenosine may exert tonic inhibition over the gluta-
matergic excitatory inputs to the cholinergic cells of the LDT
and PPT (McCarley et al. 1997; Rannie et al. 1994) and may
contribute to the REM-related suppression of serotonergic
raphe neurons (McCarley et al. 1997; Strecker et al. 1997a).
Additionally, extracellular buildup of adenosine may consti-
tute the sleep-promoting factor associated with prolonged
wakefulness (McCarley et al. 1997; Portas et al. 1996).
6. Two very recent findings highlight the importance of
neuropeptides in the regulation of sleep. The first is that in-
hibitory neurons in the ventrolateral preoptic area (VLPO)
of the hypothalamus, a specifically sleep-active area (Sherin
et al. 1996), utilize galanin as well as GABA to inhibit as-
cending arousal systems such as the the locus coeruleus
(Saper et al. 1997). The second finding has come from stud-
ies on the genetic basis of narcolepsy using animal models.
The neuropeptide orexin (or hypocretin), produced only by
neurons in the lateral hypothalamus, may play a key role in
sleep regulation via its modulation of ascending cholinergic
and monoaminergic arousal systems (Chemelli et al. 1999;
Lin et al. 1999).
7. Because dopamine (DA) release does not vary dra-
matically in phase with the natural sleep cycle as do 5-HT,
NE and acetylcholine (ACh) (Mamelak 1991; Miller et al.
1983; Trulson et al. 1981), dopaminergic agents have not
been as extensively studied. It is often found, however, that
REM sleep deprivation appears to enhance DA levels and
DA receptor sensitivities (e.g., Brock et al. 1995; Nunes et
al. 1994; Tufik et al. 1978). The effects of DA on sleep ap-
pear to be variable and are in need of further study. Studies
on the administration of dopaminergic drugs have suggested
that dopamine may play a role in dreaming, especially the
induction and intensification of nightmares (Hartmann
1978; Hartmann et al. 1981; for recent reviews see Hobson
& Pace-Schott 1999, and Thompson & Pierce 1999).
Two recent theories have proposed specific roles for DA
in dreaming. First, Solms (1997a; 1999c) suggests that
dreams are instigated by dopaminergically mediated ap-
petitive drives from the ventral tegmental area (VTA) com-
ponent of the mesolimbic reward system. Second, Gottes-
mann (1999) proposes that, during REM sleep, sustained
dopaminergic modulation of the cortex in the absence of
serotonergic and noradrenergic inhibitory influences but
the renewed presence of cholinergic excitation contributes
to the unique features of dream mentation such as its psy-
chotomimetic quality. In keeping with the cholinergic
hypothesis of REM and dreaming, mechanisms for dopam-
inergic enhancement of dreaming may involve mutual ex-
citation by dopaminergic and cholinergic nuclei such as
dopaminergic enhancement of cortical acetylcholine re-
lease (Moore et al. 1999; Smiley et al. 1999) and/or en-
hancement of mesolimbic dopamine release by cholinergic
mesopontine neurons (Oakman et al. 1999).
Finally, as in much of neuroscience, research on behav-
ioral state control is now beginning to extend its inquiry be-
yond the neurotransmitter and its receptors to the roles of
intracellular second messengers (Capece et al. 1999) as well
as intranuclear events (Bentivoglio & Grassi-Zucconi 1999;
Prospero-Garcia et al. 1999; Schibler & Tafti 1999). Recent
exciting results of a molecular genetic approach to sleep re-
search includes the discovery of the role of orexin in sleep
regulation (see above). In addition, molecular bases for
consciousness are also now being proposed (e.g., Woolf
1996). Undoubtedly such inquiry, though beyond the scope
of the present review, will increasingly enrich our under-
standing of sleep and dreaming.
3.2.4. REM sleep and other brain stem structures. In ad-
dition to this neurochemical diversity, a wide variety of
brainstem structures other than the LDT, PPT, locus
coeruleus, and raphe are crucially involved in the modula-
tion of REM sleep and its distinctive physiological signs.
These include diverse areas in the pontine reticular system
such as noncholinergic areas within the pedunculopontine
region (Rye 1997), the nucleus pontis oralis (Bourgin et al.
1995; Chase & Morales 1990), the locus coeruleus alpha
and adjacent structures (Cespuglio et al. 1982; Sakai 1988;
Shouse & Siegel 1992), peribrachial areas caudal to the
LDT and PPT (Datta 1995; 1997b), as well as the midbrain
central gray area (Maloney & Jones 1997; Sastre et al. 1996)
and the medulla (Chase & Morales 1990; Gottesmann
1997). Figure 5 schematizes the generation of the various
Hobson et al.: Dreaming and the brain
physiological signs of REM at different levels of the CNS.
Adding to the functional complexity of mesopontine cholin-
ergic areas are their roles in other brain mechanisms such as
motor control (Garcia-Rill et al. 1987; Inglis & Winn 1995;
Rye 1997) as well as the cytoarchitectonic, cytochemical,
and functional diversity within the PPT complex itself (Rye
1997). (For recent reviews on this functional neuroanat-
omy, see Datta 1995; 1997b; 1999; Gottesmann 1997; Hob-
son & Steriade 1986; Hobson et al. 1993; Jones 1991;
Koyama et al. 1999; Pace-Schott & Hobson, in press; Rye
1997; Sakai 1988; Semba 1999; Siegel 1994; Steriade & Mc-
Carley 1990a; Vertes 1984.)
Therefore, even within the brainstem itself (i.e., pons,
medulla, and midbrain) a diversity of structures and their
neurochemical products modulate control of the REM
sleep cycle by the aminergic and cholinergic nuclei. Excit-
ing ongoing research in many laboratories now builds upon
early findings summarized in the reciprocal interaction
model and pursues the important goal of a more complete
description of the complex brainstem mechanisms under-
lying REM sleep.
3.2.5. REM sleep and forebrain-brain stem interactions.
Other important contemporary research now extends the
study of sleep-wake and REM sleep control mechanisms
rostrally from the pontine brain stem to diencephalic struc-
tures in a manner consistent with connectivity studies
(Morrison & Reiner 1985; Wainer & Mesulam 1990). In
addition to the well described brainstem-thalamus-cortex
axis, subcortical sleep control mechanisms intercommuni-
cate with each other and with the cortex via an intercon-
nected network of structures extending rostrally from the
brainstem RAS to the hypothalamus, basal forebrain, and
limbic system. Saper et al. (1997) classify three ascending
arousal systems: the brainstem cortical projection system,
the basal forebrain projection system, and the hypothalamic
cortical projection system with the basal forebrain system
projecting to topographically specific cortical areas and the
other two systems projecting diffusely. Woolf (1996) has ad-
vanced an intriguing model of how these networks may in-
teract in modulating memory and cognition. We now briefly
summarize recent findings on this extended subcortical sys-
tem that are pertinent to sleep-wake and REM sleep con-
trol. We will focus here on findings in the hypothalamus,
basal forebrain nuclei, and amygdala. The hypothalamus. Histaminergic neurons origi-
nating in the posterior hypothalamus innervate virtually the
entire brain (Panula et al. 1989) including brain stem struc-
tures such as the mesopontine tegmentum (Lin et al. 1996)
and the vestibular nuclei (Tighilet & Lacour 1996). These
brainstem regions, in turn, innervate both anterior and pos-
terior hypothalamus (Abrahamson et al. 1997; Kumar et al.
1989; Steriade et al. 1980).
Anterior portions of the hypothalamus (preoptic area and
adjacent basal forebrain) are known to be essential to sleep.
Lesions here cause insomnia (Sallanon et al. 1989) while
stimulation of this area promotes sleep (McGinty et al. 1994).
In addition, stimulation of the locus coeruleus inhibits sleep-
active neurons in this area (Osaka & Matsumura 1993).
Tonic firing of histaminergic neurons in the posterior hy-
pothalamus play an important role in cortical arousal and
the maintenance of wakefulness (Khateb et al. 1995; Lin et
al. 1986; 1988; 1993; 1994; McCormick & Williamson 1991;
Hobson et al.: Dreaming and the brain
Figure 5. Schematic representation of the REM sleep genera-
tion process. A distributed network involves cells at many brain lev-
els (left). The network is represented as comprising three neuronal
systems (center) that mediate REM sleep electrographic phe-
nomena (right). Postulated inhibitory connections are shown as
solid circles; postulated excitatory connections as open circles; and
cholinergic pontine nuclei are shown as open circles with darkened
boundaries. It should be noted that the actual synaptic signs of
many of the aminergic and reticular pathways remain to be demon-
strated, and, in many cases, the neuronal architecture is known to
be far more complex than indicated here (e.g., contributions of hy-
pothalamic and basal forebrain systems). During REM, additive
facilitatory effects on pontine REM-on cells are postulated to oc-
cur via disinhibition (resulting from the marked reduction in firing
rate by aminergic neurons at REM sleep onset) and through exci-
tation (resulting from mutually excitatory cholinergic-noncholin-
ergic cell interactions within the pontine tegmentum).
The net result is strong tonic and phasic activation of reticular
and sensorimotor neurons in REM sleep. REM sleep phenomena
are postulated to be mediated as follows: EEG desynchronization
results from a net tonic increase in reticular, basal forebrain, thal-
amocortical, and cortical neuronal firing rates. PGO waves are the
result of tonic disinhibition and phasic excitation of burst cells in
the lateral pontomesencephalic tegmentum. Rapid eye move-
ments are the consequence of phasic firing by reticular and
vestibular cells; the latter (not shown) directly excite oculomotor
neurons. Muscular atonia is the consequence of tonic postsynap-
tic inhibition of spinal anterior horn cells by the pontomedullary
reticular formation. Muscle twitches occur when excitation by
reticular and pyramidal tract motorneurons phasically overcomes
the tonic inhibition of the anterior horn cells. Abbreviations: RN,
raphe nuclei; LC, locus coeruleus; P, peribrachial region; PPT, pe-
dunculopontine tegmental nucleus; LDT, laterodorsal tegmental
nucleus; mPRF, medial pontine reticular formation (e.g., giganto-
cellular tegmental field, parvocellular tegmental field); RAS, mid-
brain reticular activating system; BIRF, bulbospinal inhibitory
reticular formation (e.g., gigantocellular tegmental field, parvo-
cellular tegmental field, magnocellular tegmental field); TC, thal-
amocortical; CT, cortical; PT cell, pyramidal cell; III, oculomotor;
IV, trochlear; V, trigmenial motor nuclei; AHC, anterior horn cell.
(Modified from Hobson et al. 1986.)
Monti 1993; Saper et al. 1997; Shiromani et al. 1999; Szy-
musiak 1995) and neurons in this area may directly influ-
ence REM sleep (Reiner & McGeer 1987; Sallanon et al.
1989; Vanni-Mercier et al. 1984).
The tuberomammillary nucleus (TMN) plays a particu-
larly important role in the posterior hypothalamic hista-
minergic arousal system (Saper et al. 1997; Sherin et al.
1996; Shiromani et al. 1999; Steininger et al. 1996; Vanni-
Mercier et al. 1984). For example, Sherin et al. (1996) have
proposed that a monosynaptic pathway in the hypothala-
mus may constitute a “switch” for the alternation of sleep
and wakefulness. These workers have identified a group of
GABAergic and galaninergic neurons in the ventrolateral
preoptic anterior hypothalamus (VLPO) which are specifi-
cally activated during sleep and constitute the main source
of innervation for the histaminergic neurons of the TMN.
VLPO neurons may, therefore, specifically inhibit hista-
minergic neurons of the TMN in order to preserve sleep
(Saper et al. 1997; Sherin et al. 1996; 1998).
A recent study has demonstrated extensive histaminergic
innervation of the mesopontine tegmentum including the
LDT (Lin et al. 1996). Suppression of slow wave activity and
an increase in waking follows microinjection of histamine
and histamine agonist into these areas (Lin et al. 1996). Re-
cently, histaminergic projections from the TMN to the dor-
sal raphe as well as to areas of the basal forebrain involved
in sleep-wake control have also been demonstrated in the
cat (Lin et al. 1997). VLPO neurons have also been shown
to innervate other components of ascending arousal systems
such as the monoaminergic nuclei of the brainstem and
there they may also exert a sleep-promoting inhibitory influ-
ence (Sherin et al. 1998). Moreover, also innervating most
of the brainstem and diencephalic ascending arousal sys-
tems are the orexinergic cells of the lateral hypothalamus
and these too may play a modulatory role in the sleep-wake
cycle (Chemelli et al. 1999). Tying the hypothalamus to the
pons in this dynamic manner may provide a critical link be-
tween the circadian clock and the NREM-REM sleep cycle
oscillator (see also Liu et al. 1997; O’Hara et al. 1997). In this
regard, it is notable that retinal input to the VLPO itself has
recently been demonstrated (Lu et al. 1999). The basal forebrain. Basal forebrain (BF) nuclei
have close anatomical connections with the locus coeruleus,
raphe, and pontine nuclei (Butcher 1995; Jones & Cuello
1989; Szymusiak 1995) and, in turn, project to more rostral
structures such as the cortex, thalamus, and limbic systems
(Butcher 1995; McCormick 1990; Metherate et al. 1992;
Steriade & Buzsazki 1990; Szymusiak 1995; Woolf 1996). In
addition to its brain stem and cortical connectivity, the basal
forebrain also has close anatomical connections with the
anterior and posterior hypothalamus (Gritti et al. 1993;
1994; Szymusiak 1995), the amygdala, and the thalamus
(Szymusiak 1995). (For a recent review of BF connectivity
see Jones & Muhlethaler 1999.)
Neurochemically, acetylcholine plays a major role in BF
control of behavioral state (Jones 1993; Jones & Muhle-
thaler 1999). For example, magnocellular cholinergic cells
of the BF nuclei promote the activation of those cortical and
limbic structures to which they project (Cape & Jones 1998;
McCormick 1990; Metherate et al. 1992; Szymusiak 1995;
Wainer & Mesulam 1990). For example, those of the Nu-
cleus Basalis of Meynert activate topographically distinct ar-
eas of the cortex (Metherate et al. 1992; Szymusiak 1995;
Woolf 1996). Recent work in rats has also implicated BF
magnocellular cholinergic neurons in the control of high
voltage cortical slow waves such as are observed in NREM
(Kleiner & Bringmann 1996; Nunez 1996). GABAergic BF
cells may also interact with BF cholinergic cells in the reg-
ulation of oscillatory rhythms which accompany cortical ac-
tivation (Jones & Muhlethaler 1999). Other BF cells, ana-
tomically and neurochemically distinct from the cholinergic
magnocellular neurons, function as sleep promoting ele-
ments (Szymusiak 1995), possibly by GABAergic inhibition
of hypothalamic and brain stem arousal systems (Szymusiak
1995), the hippocampus (Mallick et al. 1997), or the cortex
(Jones & Muhlethaler 1999).
There are extensive interactions between the brain stem
structures (locus coeruleus, raphe nuclei, as well as the
LDT and PPT) and the BF in sleep-wake control (Jones &
Cuello 1989; Jones & Muhlethaler 1999; Semba 1999;
Semba et al. 1988; Szymusiak 1995). Bidirectional interac-
tions between the BF and sleep-related areas of the brain-
stem modulate behavioral state utilizing a variety of trans-
mitter substances as illustrated by the following findings:
1. The cholinergic system of the mesopontine tegmen-
tum communicates with the BF cholinergic system in a
manner functionally relevant to sleep (Baghdoyan et al.
1993; Consolo et al. 1990). For example, simultaneous mi-
croinjection of carbachol into cholinoceptive regions of the
BF suppresses the ability of carbachol to induce a REM-like
state when injected into the pons (Baghdoyan et al. 1993).
2. Cholinergic BF structures, which activate the cortex,
can be activated by brain stem glutamatergic cells (Ras-
mussen et al. 1994).
3. Glutamatergic systems of the BF can, in turn, affect
behavioral state via projections to the mesopontine teg-
mentum (Manfridi & Mancia 1996).
4. Aminergic inputs to the BF nuclei from brainstem nu-
clei can influence behavioral state in a manner similar to
their action in the pons. For example, the noradrenergic ag-
onist isoproterenol increases wakefulness and suppresses
REM when infused into the BF (Berridge & Foote 1996).
As in the brainstem, neuromodulatory systems interact
within the BF itself. For example, BF cholinergic neurons may
be under tonic inhibition by adenosine (Porkka-Heiskanen
1997b; Strecker et al. 1997b) while 5-HT can hyperpolarize
cholinergic nucleus basalis neurons and decrease wake-asso-
ciated gamma frequency oscillations in the cortical areas to
which they project (Cape & Jones 1998). The BF nuclei,
therefore, both directly participate in behavioral state-related
functions and modify the activity of other areas involved in
sleep such as the pontine REM generator. The amygdala. Of particular interest in view of the
human neurobiology reviewed above (e.g., Maquet et al.
1996; Nofzinger et al. 1997), the amygdala has reciprocal
connections with pontine regions involved in the control of
REM sleep (Bernard et al. 1993; Calvo & Simon-Arceo 1999;
Morrison et al. 1999; Sanford et al. 1995b; Saper & Loewy
1980; Semba & Fibiger 1992; Wainer & Mesulam 1990) and
receives serotonergic innervation from the dorsal and medial
raphe (Fallon & Ciofi 1992). For a recent thorough review of
the amygdala in sleep regulation see Morrison et al. (1999).
Physiological signs of REM have been shown both to
occur spontaneously and to be modifiable in the amyg-
dala (see Calvo & Simon-Arceo 1999 for a review; see also
Maquet 2000; Maquet & Phillips 1998; 1999 regarding
Hobson et al.: Dreaming and the brain
recent human findings). For example, in the cat, PGO-
like EEG activity has been detected in the basolateral
amygdala (Calvo & Fernandez-Guardiola 1984). More-
over electrical stimulation of the cat amygdala significantly
increased PGO number, spike density, and burst density
(Calvo et al. 1987) as well as the amplitude and rate of
acoustically elicited pontine PGO waves in the waking rat
(Deboer et al. 1997; 1998), and burst firing of pontine cells
in the rabbit (Morrison et al. 1999).
Aminergic and cholinergic stimulation of the amygdala has
been shown to modify sleep in the directions predicted by re-
ciprocal interaction for the action of these neurotransmitters
in the pons. For example, cholinergic stimulation of amyg-
daloid sites in the cat enhanced REM sleep for several days,
an effect akin to the long-term REM enhancement by cholin-
ergic stimulation of the peribrachial pons (Calvo & Simon-
Arceo 1995; 1999; Calvo et al. 1996). Furthermore, seroton-
ergic stimulation of the amygdala in the cat caused short
latency changes of state from either NREM or REM (San-
ford et al. 1995b), while serotonergic antagonism during
NREM increased PGO activity (Sanford et al. 1995a) and the
relative amount of sleep (Sanford et al. 1995b). Similarly,
noradrenergic stimulation of the amygdala suppressed sleep
relative to wakefulness (Fuchino et al. 1996). Interestingly,
the role of the amygdala in REM sleep control may differ be-
tween species (Deboer et al. 1997; Sanford et al. 1997a).
It has been suggested that serotonergic mechanisms in
the amygdala constitute a mechanism whereby emotionally
significant stimuli can influence the state of arousal (San-
ford et al. 1995b). Such a role corresponds well with the
proposed role of amygdala in the processing of emotional
memory during REM (Maquet & Franck 1997). Other subcortical structures. Other diencephalic
structures such as centralis lateralis nucleus of the thalamus
possibly participate in the modulation of REM sleep (Man-
cia & Marini 1997; Marini et al. 1992). In addition, there
are extensive striatal projections to the pedunculopontine
region (Inglis & Winn 1995; Rye 1997) especially to gluta-
matergic cells of the midbrain extrapyramidal area (MEA)
(Rye 1997). Interaction between the MEA and the basal
ganglia may serve to modulate movement to accord with
behavioral state (Rye 1997).
In addition to forebrain structures, brain stem structures
rostral to the pons such as the ventrolateral periaqueductal
gray (Sastre et al. 1996) may also be important in the mod-
ulation of REM sleep. Such rostral brainstem connections
could facilitate ponto-limbic interactions in REM sleep
generation and loss of this mechanism could account for
loss of dreaming when such connections are severed by
clinical lesions (Solms 1997a).
3.2.6. Neurophysiological evidence which supports the
REM-NREM-waking distinction.
While the REM-NREM-
waking distinction was first defined in standardized terms by
the neurophysiological criteria of polysomnography (Recht-
schaffen & Kales 1968), abundant additional physiological
evidence has since accumulated which supports the biolog-
ical differentiation of these three states. Although direct
measurement of human CNS neuromodulators is still in its
infancy, preliminary evidence points to a similar pattern of
fluctuation across the sleep-wake cycle as is seen in animal
models (Wilson et al. 1997). In addition, the following indi-
rect evidence strongly supports the physiological distinction
between REM, NREM, and waking: (1) Autonomic activa-
tion is higher during NREM night terrors than during REM
nightmares (Fisher et al. 1973). (2) While the locus
coeruleus is active during waking and its noradrenergic out-
put is associated with wake state anxiety responses (Brem-
ner et al. 1996; Salzman et al. 1993), this region is quiescent
in REM sleep (Hobson & Steriade 1986) despite the pre-
dominance of anxiety in the emotions of dreaming (Merritt
et al. 1994). (3) Cholinergic activation of limbic structures
probably underlies REM dream anxiety (Braun et al. 1997)
whereas ACh is not prominently involved in waking anxiety
(Salzman et al. 1993). (4) Nielsen (1999; and target article)
notes additional physiological differences between REM
and NREM sleep such as differing ERP patterns and exter-
nal stimulus responses, which suggest differing cognitive
processes taking place during these two sleep states.
3.2.7. Conclusions. All of these findings indicate that the re-
ciprocal interaction of cholinergic and aminergic systems
may operate in areas other than the brain stem in ways that
significantly amplify REM sleep generation or suppression.
As has been hypothesized for learning and cognition (Woolf
1996), a subcortical medial ascending system of multiple nu-
clei, extensive reciprocal interconnections between nuclei,
and system-wide sensitivity to neuromodulation controls be-
havioral state at a hierarchical level above that of specific sub-
component oscillators (e.g., the pontine REM generator).
Furthermore, in view of the recent evidence of selective ac-
tivation of the limbic lobe in human REM sleep (Braun et al.
1997; 1998; Maquet et al. 1996; Nofzinger et al. 1997), these
new basic neurobiological findings have a particularly strong
impact on the neurocognitive theory of dreaming.
We conclude that the essential tenets of the reciprocal in-
teraction model have been strongly confirmed and that the
interaction of the pontine structures with other brain struc-
tures can now begin to be studied in ways that will enrich
our understanding of how the distinctive features of each
conscious state are mediated and how their stereotyped se-
quencing is controlled.
3.3. Contemporary theories of conscious states
We now turn our attention to a review of theories on how
conscious states are mediated. As the inadequacies of the
Freudian model of dreaming have become more evident,
many researchers have increasingly turned toward the es-
tablishment of a cognitive neuroscience of brain-mind states.
Four major cognitive models of dreaming are discussed be-
low. All four of these have been inspired by modern labo-
ratory research but the degree to which they are deeply
brain-based varies dramatically as we hope to make clear.
In section 3.3.5, we address the ongoing debate on the re-
lationship of REM eye movements to dream imagery. We
do so because this controversy exemplifies both the basic
differences between “top-down” (cortically driven) and
“bottom-up” (subcortically driven) views on the origin of
dreaming as well as the added complexity and realism of-
fered by an approach to the biology of dreaming which
takes into account the wide range of perspectives offered
by contemporary neuroscience.
3.3.1. Activation models. In 1970, Zimmerman advanced a
theory in which dreaming (versus thinking or no mentation)
occurred during sleep when “cortical arousal” exceeded a
Hobson et al.: Dreaming and the brain
certain threshold, regardless of sleep stage. We will later
describe various ways to measure cortical activation which
we call factor “A” and take to be one of three critical factors
in determining the probability of dreaming.
Antrobus and his colleagues have proposed an elabo-
rated cortical activation-based model of mentation operat-
ing across all mental states (Antrobus 1986; 1990; 1991;
Fookson & Antrobus 1992; Reinsel et al. 1992). According
to Antrobus, the qualities of mentation in any state result
from an interaction between the activation level of cortex
and the current level of environmental stimulation as gated
by current sensory thresholds. Interaction between cortical
modules subserving various sensory, motor, and associative
modalities create the dream narrative and integrate any
cortical, subcortical or peripheral inputs via a “top-down”
cortically controlled process (Antrobus & Bertini 1992).
Antrobus and his colleagues describe the dynamics of this
process in terms of parallel distributed process neural net-
work models (Antrobus 1991; Fookson & Antrobus 1992).
In our terms, the greater the value of “A,” the greater the
production and retrieval of associative trains of thought.
The Antrobus team theorizes that the high sensory
thresholds of REM prevent interruption of ongoing men-
tation. In our terms, this process is measured as factor “I”
which we see as shifted away from external sensory input,
and correspondingly favoring internal, fictive sensory input.
For Antrobus, the result is a more ongoing, story-like qual-
ity of REM mentation compared with wake mentation
which, though similarly activated, is continually interrupted
by external stimuli (Reinsel et al. 1986; 1992; Wollman &
Antrobus 1986). In his model, dream bizarreness results
when cortical networks, which are attempting to accurately
reconstruct reality based on probabilities learned during
waking, fail to fully integrate all of the various constructions
being generated (Antrobus & Bertini 1992; Fookson &
Antrobus 1992).
Antrobus implicitly rejects the role of aminergic-cholin-
ergic neuromodulation (our model’s factor M) in controlling
the nature of dream mentation. Instead, he argues that since
waking mentation can be dreamlike, this neuromodulatory
shift is not necessary for dream mentation to occur and fac-
tor M of our three dimensional model is discarded. We in-
vite Antrobus to explain the paradoxical memory defect and
loss of self-reflective awareness and volition during dream-
ing on the basis of activation and sensory gating alone.
3.3.2. The cognitive psychological model of Foulkes.
Foulkes has advanced a cognitive, information processing
model of dream production which questions the brain basis
of conscious states and dream mentation (e.g., Foulkes
1982a; 1985; 1990; 1993b; 1997; Foulkes & Cavallero 1993).
Instead, Foulkes describes dreams as resulting from the ac-
tivation of mnemonic “systems” or “units.” In his model, “ac-
tivation” is conceived as the combination of both excitatory
processes and the disinhibition of mnemonic systems previ-
ously inhibited by voluntary self-control (Foulkes 1985).
With the exception of general excitatory processes such
as the cerebral activation of REM, Foulkes’s model is ex-
plicitly a psychological, mentalistic construct which does
not attempt to link psychological to physiological phenom-
ena (Foulkes 1985; 1990). A similar position has been taken
by Bosinelli (1995) and by Mancia (1995). Each of them as-
serts that mentalistic and physiological sleep phenomena
cannot be explained from the same epistemological refer-
ents. As such, these models share with Freud’s model a de-
cision not to attempt to explain these mental functions in
terms of brain actions.
Instead, Foulkes’s earlier cognitive models emphasized
similarity between the intermediate steps of a psycholin-
guistic model of language production and a “psychoneiric”
model of dream production with the differences between
the two processes occurring mainly at input and output
stages of production (Foulkes 1982a). In more recent writ-
ings, Foulkes (1990) specifically equates the high level cog-
nitive constructive processes which organize waking expe-
rience with those processes which organize dreaming. For
example, he explains the consonance of dream emotion
with dream plot as resulting from the primary narrative de-
mands of the dream (Foulkes 1997; Foulkes et al. 1988b).
Further, he specifically eschews any possible information-
bearing role for subcortical stimuli in dream form or narra-
tive. In his own words, “subcortical structures . . . simply
turn on the light switch upstairs. They don’t tell any of the
creatures upstairs what to do or how to do it; they simply
arouse them, enabling them to do whatever it is they char-
acteristically do” (Foulkes 1997, p. 3).
Foulkes goes on to assert that if such higher level (and
implicitly cortically based) cognitive processes cannot con-
sciously construct an organized, episodically integrated,
self-reflective account of waking (as in the case of an ani-
mal or a pre-operational child), they also cannot uncon-
sciously construct a coherent dream narrative (Foulkes
1990). As previously noted, this model constrains the dream
to adult human sleep mentation and does not account for
conscious experiences during sleep which may be possible
at a much lower level of integration. For example, given
Foulkes’s (1990) position, one might argue that severely
cognitively regressed adults (e.g., with severe dementia or
delirium) should lose much of their capacity to dream.
However, this prediction is not supported by clinical find-
ings (e.g., Cipolli et al. 1992; Doricchi & Violani 1992;
Kramer et al. 1975). Instead, we see loss of dreaming asso-
ciated with lesions to specific brain areas (for reviews see
Doricchi & Violani 1992 and Solms 1997a), a finding which
would be expected if specific circuits with a great degree of
localization form the neural substrate of dreaming.
Although Foulkes’s model cannot be specifically viewed
in the context of our physiological AIM model, some hints
of these concepts can be found in his work. For example,
he does make a generalized claim that cortical activation by
the brain stem (the “A” dimension of the AIM model) must
be relatively high in dreaming (Foulkes 1997). In addition,
he argues that the origin of dream scenarios comes from the
quasi-random activation of a “mnemonic focus” (Foulkes
1985, p. 151), and specifically not from external stimuli.
This corresponds to a value of low sensory input and high
value of internal input on the “I” dimension. No position on
the “M” dimension of our AIM model, however, can be in-
ferred from his studies. We invite Foulkes to explain the
several robust deficiencies of dream cognition, and espe-
cially the amnesia, in terms of his model.
3.3.3. The neuropsychological-psychoanalytic model of
Combining the clinical lesion studies described
above in section 3.1.6 and the classical psychoanalytic the-
ory of dreaming, Solms (1997a; 1999c) builds a neuropsy-
chological model of normal dreaming, which is illustrated
in Figure 6. Frontal dopaminergic mesolimbic reward cir-
Hobson et al.: Dreaming and the brain
cuits produce an instigating impetus for dreaming when
activated by arousing stimuli (e.g., ascending brainstem
arousal in REM). The passage of this subcortical stimulus
to posterior heteromodal association areas in the inferior
parietal lobe is gated by a reality monitoring process medi-
ated by anterior limbic areas. These anterior limbic areas
also prevent this subcortical stimulus from activating the
motor cortex as well as facilitating back projection of this
stimulus to the posterior cortex. Back projection continues
from the inferior parietal lobe (which contributes the ca-
pacity for spatial cognition) to visual association areas in
medial occipito-temporal cortex (which contribute visual
imagery) but not as far back as primary visual cortex. Solms
speculatively assigns to the resultant network the sleep-
protective function of Freud’s classical dream work: appet-
itive subcortical impulses are “censored” by the anterior
limbic system and then safely back-projected to posterior
cortical representational mechanisms.
In support of the neuroanatomical details of this net-
work Solms cites his findings on lesion-induced changes in
dreaming. Loss of dream imagery (visual anoneria) is ac-
companied by an analogous waking deficit, visual irremi-
niscence, which involves the highly processed visual mem-
ory functions of unimodal association cortex and not the
perceptual functions of the primary visual cortex. Since cor-
tical area V1 lesions do not cause visual anoneria, Solms hy-
pothesizes that any back projection processes involved in
dreaming do not extend all the way to primary visual cor-
tex. On the basis of the findings that lesions in Brodmann
areas 39 and 40 in either hemisphere appear to be the most
restricted damage causing the posterior variant of global
anoneria, he proposes that these heteromodal areas are the
source of back projection to visual association areas. In sup-
port of this network’s sleep-protective function, he notes
that global anoneric patients report poorer sleep quality
than non-cerebrally injured controls (Solms 1997a).
3.3.4. The activation-synthesis model The original-activation synthesis model.
dant studies in the 1960s and 1970s on the cellular neuro-
physiology of the sleep cycle as well as the functional reor-
ganization of the visual system during sleep suggested a
new conceptual approach to brain-mind states. First ex-
pressed as the activation-synthesis hypothesis of dreaming
(Hobson & McCarley 1977), this model proposed the
global mapping of brain states to mind states. This was the
position taken by Freud in his famous Project for a scien-
tific psychology (1895) but ostensibly abandoned in the In-
terpretation of dreams (1900). For a detailed discussion of
this subject, see McCarley and Hobson (1977).
Enunciating the general principle of brain-mind iso-
morphism, the activation-synthesis model placed emphasis
Hobson et al.: Dreaming and the brain
Figure 6. Forebrain processes in dreaming based upon a model proposed by Solms (1997a). Solms proposes that the dopaminergic
mesolimbic reward circuits (region 5 in Fig. 6) produce an instigating impetus for dreaming when activated by arousing stimuli such as
environmental input, ascending brainstem arousal in REM (region 6a in Fig. 6) or epileptiform discharge (region 6b in Fig. 6). He fur-
ther hypothesizes that the posterior passage of this subcortical stimulus is gated by a reality monitoring process in anterior limbic areas
(region 4 in Fig. 6) which both interrupt voluntary motor activity and facilitate back projection processes from the inferior parietal cor-
tex (region 2 in Fig. 6) to medial temporal-occipital visual association areas (region 3 in Fig. 6). During this process, premotor and mo-
tor cortices (region 1 in Fig. 6) remain quiescent due to the combined effects of limbic blockage (region 4 in Fig. 6) of ascending im-
pulses as well a sleep-related inhibition.
on such aspects of the form of dreams which might be ex-
pected to have their roots traced to isomorphic forms of
brain activity. In so doing, the new theory proposed some of
the cellular and molecular mechanisms by which changes in
activation, in stimulus origin and in neuromodulation could
explain the state-dependent changes in perception, think-
ing and memory seen in shifts from waking to NREM and
REM sleep (Flicker et al. 1981). The activation-synthesis
hypothesis proposed that formal aspects of dream menta-
tion reflected the outcome of attempts by sensorimotor and
limbic regions of the forebrain to produce a coherent ex-
perience from the incomplete and chaotic inputs received
from the brain stem. The specific formal features of dream
mentation, it was proposed, could best be explained by ex-
amining the unique configuration of brain activity that oc-
curs during REM sleep.
To illustrate how this global brain-to-mind mapping con-
cept is articulated, we considered the probable conse-
quences of a shift in visual system input source from the
formed visual images on the retina in waking to the chaotic
brain stem stimulation of REM sleep (Bizzi 1966a; 1966b;
Callaway et al. 1987; Nelson et al. 1983; Pivik et al. 1977).
This shift in input source occurs in the context of a concur-
rent cessation of activity in brain stem noradrenergic and
serotonergic neurons (Hobson & Steriade 1986; Steriade &
McCarley 1990a). The quiescence seen in these aminergic
modulatory neurons results in the demodulation and disin-
hibition of the visual cortex (Evarts 1962), the lateral genic-
ulate bodies (Bizzi 1966b) and brain stem oculomotor net-
works (Mouret et al. 1963).
As a result of the aminergic disinhibition, cholinoceptive
peribrachial neurons become hyperexcitable and fire in
bursts, causing phasic activation of the lateral geniculate
bodies and visual cortex. This phasic activation is recordable
in the REM sleep of cats as the PGO waves which, in turn,
correlate with the direction of the rapid eye movements
(Monaco et al. 1984; Nelson et al. 1983). We have speculated
that this cholinergically mediated stimulation conveys infor-
mation to the visual system about the direction of the eye
movements which have become, in REM sleep, uncoupled
from external sensory stimuli (Callaway et al. 1987).
The net result of these shifts is an activated brain stem
and visual system which are (1) deafferentated, (2) aminer-
gically demodulated, and (3) cholinergically auto-stimulated.
But the brain stem signals still convey information about
the direction of rapid eye movements to the deafferen-
tated, demodulated forebrain. According to the activation-
synthesis hypothesis, these changes in sensory input source
and neuromodulation could contribute to such cognitive
features of dreaming as (1) the hallucinatory visual imagery,
(2) the frequent shifts and reorientations of attention, (3)
the loss of voluntary control of both motor action and in-
ternal attention, (4) the emotional intensification especially
of anxiety, elation, and anger, and (5) the memory loss
within and after dreaming (Mamelak & Hobson 1989a). Evolution of the activation-synthesis model. The
original formulation of the activation-synthesis model of
dream construction (Hobson & McCarley 1977) proposed
that the phasic signals arising in the pontine brain stem dur-
ing REM sleep and impinging upon the cortex and limbic
forebrain led directly to the visual and motor hallucinations,
emotion, and distinctively bizarre cognition that character-
ize dream mentation. In doing so, these chaotically gener-
ated signals arising from the brain stem acted as a physio-
logical Rorschach test, initiating a process of image and nar-
rative synthesis involving associative and language regions
of the brain and resulting in the construction of the dream
scenarios. Thus, it was the combination of this chaotic, bot-
tom-up activation process and its resultant semi-coherent,
top-down synthetic process which made up the overall
process of dream construction.
Anticipating activation-synthesis by almost a decade,
Molinari and Foulkes’s (1969) application of Moruzzi’s
physiological tonic-phasic model to dream psychology first
introduced the concept that the phasic events of sleep con-
tribute hallucinatory raw material that was then secondarily
elaborated during dream production. Using neurobiological
data to support these concepts, the activation-synthesis
model hypothesized that dreaming resulted from the in-
terpretation by the cortex of information concerning eye
movements and activated brain stem motor pattern gener-
ators. Seligman and Yellen (1987) added the consideration
of emotional evaluation to the concepts of primary visual
activation and secondary cognitive elaboration to generate
a cognitive model of dream production, a suggestion strongly
supported by recent PET studies showing preferential ac-
tivation of limbic structures and adjacent cortices (Braun et
al. 1997; Maquet et al. 1996; Nofzinger et al. 1997).
We have recently proposed that both cortical and limbic
regions, when cholinergically activated by REM sleep events
such as PGO waves, may synthesize their own information
(Hobson 1988b; 1990; 1992a; 1997a; Hobson & Stickgold
1994a; 1994b; Mamelak & Hobson 1989a). For example,
dream hallucinosis, while probably incorporating eye-move-
ment information coded in PGO bursts, must also incorpo-
rate visual material from a variety of memory sources in an
otherwise activated cortex. This aspect of the theory is very
similar to Solms’s suggestion of a “back projection” toward
the visual cortex from the limbic forebrain (Solms 1997a) as
the brain synthetically fits image to affect. Informing recent
presentations of the activation-synthesis hypothesis are con-
cepts from neural net modeling (Mamelak & Hobson 1989a;
Sutton & Hobson 1994), self-organization theory (Kahn &
Hobson 1993; Kahn et al. 1997), graph theory (Sutton et al.
1994a; 1994b), cognitive neuroscience (Hobson & Stickgold
1994a; 1994b) and, most recently and influentially, the new
findings described above in section 3.3 on the functional neu-
roimaging of sleep and the clinical neuropsychology of
dreaming (Hobson et al. 1998a; 1998b; 2000). Activation synthesis updated: An integrated
model of REM sleep dreaming.
Integration of the original
activation-synthesis model with new neuroimaging (Braun
et al. 1997; 1998; Maquet et al. 1996; Nofzinger et al. 1997)
and lesion (Solms 1997a) data allows the development of
a more detailed activation-synthesis model of REM sleep
dreaming (Hobson et al. 2000). Although the original acti-
vation synthesis model was necessarily weighted toward ac-
tivation processes (e.g., PGO activation of thalamocortical
circuits), these new findings allow us to begin to speculate
on the neuroanatomical bases of the synthesis aspect of the
model. In doing so, we present a neuropsychological model
of dreaming differing substantially from that of Solms (pre-
sented above), which was based on lesion studies alone.
This model is presented in Figure 7 and its components are
described in more detail below.
In this model, dreaming consciousness results from pro-
Hobson et al.: Dreaming and the brain
cesses of arousal impinging upon selectively facilitated, dys-
facilitated or input/output-blockaded forebrain structures.
The various elements of normal dreams are contributed by
brain networks that include structures known to contribute
to analogous processes in waking although, as the model
suggests, dreaming is characterized by a deletion of certain
circuits active in waking and, perhaps, the accentuation of
others. The following text uses the enumerated brain areas
in Figure 7 to present a model of the neuropsychological
bases of dream phenomena.
Ascending arousal systems (zones 1 and 2 in Fig. 7): As in
waking, activation of the forebrain occurs through ascend-
ing arousal systems located in the brainstem reticular acti-
vating system (Steriade 1996), the basal forebrain (Szymu-
siak 1995) and possibly the hypothalamus (Saper et al. 1997).
Together these structures form an integrated ascending
midline network (Woolf 1996) which includes ascending
cholinergic systems. Braun et al. (1997) suggest that the as-
cending reticular activation of REM sleep may proceed rel-
atively more via a ventral cholinergic route from the brain-
stem to the basal forebrain rather than via the dorsal route
through the thalamus which is preferred in waking. This
suggestion and the related idea of Solms (1997a), recall the
early speculation of Jouvet (1962) that forebrain activation
might proceed via the limbic midbrain circuit of Nauta.
The forebrain stimulation arising from such intrinsic
arousal systems allows “consciousness” (as opposed to un-
consciousness) to exist in dreaming. Such consciousness
may be detected by the desynchronization of the tradition-
ally measured cortical EEG frequencies (Hobson 1988b) as
well as by the appearance of gamma frequency oscillatory
rhythms (Llinas & Ribary 1993; for reviews, see Hobson et
al. 1998a; 2000; Kahn et al. 1997). Brainstem and dien-
cephalic structures also contribute information in specific
modalities via specific circuitries (such as the PGO network)
resulting in distinctive dream features such as directionality
of eye movement, distinctive motor pattern automata, and
instinctive behavior and feelings such as rage, terror, or sex-
ual arousal (Hobson & McCarley 1977).
Thalamocortical relay centers and thalamic subcortical
circuitry (zone 6 in Fig. 7): The release of corticothalamic
intrinsic oscillatory rhythms suppresses the experience of
perception and mentation during NREM sleep (see above).
During REM sleep, this process is reversed and the acti-
vated thalamic nuclei, which occupy key sites in sensori-
motor relay as well as other brain circuits, contribute to the
pseudosensory perceptual aspects of dream consciousness.
For example, the lateral geniculate nucleus transmits PGO
waves from the brainstem to the visual cortex. As an inter-
nal stimulus, PGO waves bear such information as the di-
rectionality of gaze shifts encoded in the form of corollary
discharge from brainstem oculomotor nuclei (Hobson &
McCarley 1977). Recent dipole tracing techniques in hu-
mans have shown PGO wave-like activity involving the
pons, midbrain, thalamus, hippocampus, and visual cortex
(Inoue et al. 1999b). Moreover, it has recently been shown
that information encoded in the pattern of activation of
geniculate neurons in the cat is sufficient to represent ba-
sic elements of natural scenes (Stanley et al. 1999).
As in waking, corollary discharge information from pro-
Hobson et al.: Dreaming and the brain
Figure 7. Forebrain processes in normal dreaming: an integration of neurophysiological, neuropsychological and neuroimaging data.
Regions 1 and 2: ascending arousal systems; 3: subcortical and cortical limbic and paralimbic structures; 4: dorsolateral prefrontal exec-
utive association cortex; 5: motor initiation and control centers; 6: thalamocortical relay centers and thalamic subcortical circuitry; 7: pri-
mary motor cortex; 8: primary somatosensory cortex; 9: inferior parietal lobe; 10: primary visual cortex; 11: visual association cortex; 12:
cerebellum. This figure serves as a visual model for section (“Activation-synthesis updated: An integrated model of REM sleep
dreaming”) and each element of the figure is explained in detail in that section. Abbreviations: RAS, reticular activating system; PGO,
ponto-geniculo-occipital waves; LGN, lateral geniculate nucleus; BA, Brodmann area. (From Hobson et al. 2000).
grammed instinctual motion commanded by brainstem
motor pattern generators is transmitted rostrally via the
thalamus (Hobson & McCarley 1977). In addition, nuclei
within the thalamus participate in the subcortical circuitry
of various motor pathways (Braun et al. 1997). Moreover,
thalamic nuclei participate in the control of the sleep cycle
itself (Mancia & Marini 1997) and recent findings have
shown the ventrolateral thalamus may mediate the interac-
tion of arousal and attention in humans (Portas et al. 1999).
Subcortical and cortical limbic and paralimbic structures
(zone 3 in Fig. 7): As suggested by PET studies, medial fore-
brain structures, both cortical and subcortical, are selec-
tively activated during REM sleep dreaming (Braun et al.
1997; 1998; Hobson et al. 1998b; 2000; Maquet et al. 1996;
Nofzinger et al. 1997). Among these, limbic and paralimbic
structures are consistently found to be active in REM and
these contribute distinctive emotion-related dream fea-
tures as follows.
As in waking (LeDoux 1996), amygdalar activation con-
tributes emotional features, especially anxiety, to dreaming.
Maquet emphasizes that those cortical areas activated in
REM are rich in afferentation from the amygdala (anterior
cingulate, right parietal operculum) while those areas with
sparse amygdalar afferentation (prefrontal cortex, parietal
cortex, and precuneus) were deactivated in REM (Maquet
1997; Maquet et al. 1996).
As in waking (Devinsky et al. 1995), anterior cingulate ac-
tivation contributes additional emotional features to dream-
ing such as valence biases, the assessment of motivational
salience, and the integration of dream emotion with fictive
actions. Interestingly, in some PET studies, other elements
of the rostral limbic and perilimbic circuits such as the ven-
tral striatum and the orbitofrontal, insular, and medial pre-
frontal cortices have also been found to be activated during
REM (Braun et al. 1997; Nofzinger et al. 1997). Such me-
dial areas have the most abundant limbic connections in the
prefrontal cortex (Barbas 1995; Braun et al. 1997) and their
disruption is often associated with confabulatory or dream-
wake confusional syndromes (Braun et al. 1997; Solms
1997a). Several recent findings also suggest the importance
of medio-frontal, limbic-associated cortical areas to dream-
ing. First, during sleep, a scalp-recorded decrease in frontal
alpha power and the persistence of waking frontal alpha
asymmetry between hemispheres has been suggested to be
linked to activation of underlying limbic structures during
REM (Benca et al. 1999). Second, magnetic resonance spec-
troscopy has shown a sleep-related elevation of medial pre-
frontal glutamine (a glutamate precursor) to the unusually
high levels seen in awake schizophrenics (Bartha et al.
1999). These authors go on to suggest that this elevation is
linked to brain activity during dreaming.
Activated limbic circuits underlie the phenomenology of
recalled dream emotion with its predominance of anxiety
over other emotions (Domhoff 1996; Merritt et al. 1994;
Nielsen et al. 1991). The finding that dream emotion is
usually consistent with the dream narrative (Foulkes et al.
1988b) and that bizarre incongruities between emotion and
narrative are rarer than incongruities among other dream
elements (Merritt et al. 1994) can now be explained by
viewing dream emotion as a primary shaper of plots rather
than as a reaction to them (Seligman & Yellen 1987). Thus
in a classic anxiety dream, the plot may shift from feeling
lost, to not having proper credentials, adequate equipment
or suitable clothing, to missing a train. These plots all sat-
isfy the driving emotion – anxiety – while being only very
loosely associated with one another in a category that we
call “incomplete arrangements.”
Two concerns arise when predicting that REM sleep
dreaming is hyperemotional in comparison to other behav-
ioral states. The first involves early findings of maximal gal-
vanic skin response (GSR), an indicator of peripheral auto-
nomic activity, in Stage 4 NREM rather than REM (Johnson
& Lubin 1966) as well as the complementary findings of an
“autonomic storm” accompanying Stage 4 night terrors
(Fisher et al. 1973). It must be noted, however, that periph-
eral autonomic activity may be uncoupled from central au-
tonomic activity in deep sleep. Thus we would not expect
GSR to correlate with felt emotion in deep sleep. Moreover,
if GSR did so correlate, it would constitute the sleep equiv-
alent of the James-Lange hypothesis that emotion is the per-
ception of peripheral autonomic changes, a hypothesis now
felt to be inaccurate even in waking when the peripheral
measures may themselves more faithfully reflect central au-
tonomic activation. A second concern is the often reported
lack of emotion-related physiological arousal accompanying
dream events (e.g., violence) which would easily elicit such
arousal in waking (Perlis & Nielsen 1993). Such emotional
“numbing” in dreams could result both from a sleep-related
dissociation of peripheral and central autonomic activity (as
with peripheral arousal in Stage 4) combined with REM-
related blockade of central readout to the periphery and
peripheral sensory feedback to the CNS.
The amygdala is known to influence memory storage
processes in the hippocampus (Cahill & McGaugh 1998).
Such circuits could thus underlie the role of REM sleep and
dreams in the processing of emotional memories that is
often hypothesized by dream psychology theorists and by
neuroimaging groups (Braun et al. 1997; Cartwright et al.
1998a; Hobson et al. 1998b; Kramer 1993; Maquet et al.
1996; Maquet & Franck 1997; Nofzinger et al. 1997; Perlis
& Nielson 1993). For example, Nofzinger et al. (1997) sug-
gest that an important function of REM sleep is the inte-
gration of neocortical function with basal forebrain hypo-
thalamic motivational and reward mechanisms.
Motor initiation and control centers (zone 5 in Fig. 7): As
in waking movement (Kolb & Whishaw 1996), the basal
ganglia play a role in initiating fictive dream movement and
their strong activation in REM relative to both waking and
NREM (Braun et al. 1997) contribute to the ubiquity of hal-
lucinated motion in dreams (Hobson 1988b; Porte & Hob-
son 1996). The cerebellum (zone 12 in Fig. 7) modulates
these fictive movements and adds specific features such as
vestibular sensations (Hobson et al. 1998c; Leslie & Ogilvie
1996; Sauvageau et al. 1998) via cerebellar connectivity
with brainstem vestibular nuclei. It is interesting that pon-
tine cholinergic neurons have recently been shown to pro-
ject to the cerebellar vermis (Cirelli et al. 1998), a region of
the cerebellum which has been found to be activated in
REM (Braun et al. 1997). Moreover, the pons serves as a key
intermediary structure in cortico-cerebellar and cerebello-
cortical pathways (Schwartz & Thier 1999).
Braun et al. (1997) suggest a role for the basal ganglia in
ascending thalamocortical activation (via their connectivity
with the brainstem through the intralaminar thalamic nu-
clei) as well as a role for the basal ganglia in the rostral
transmission of PGO waves (via their back-projections to
the pedunculopontine tegmentum). Notably, the basal gan-
glia show extensive connectivity with regions of the pontine
Hobson et al.: Dreaming and the brain
brainstem also known to regulate REM sleep phenomena
(Inglis & Winn 1995; Rye 1997).
Motor input from cerebral levels rostral and caudal to the
basal ganglia also contribute to the experience of movement
in dreaming. Brainstem motor pattern generators (in zone 1
of Fig. 7) are stimulated along with the widespread pontine
reticular activation of REM sleep and they could contribute
to the frequent experience of programmed movement such
as running in dreams (Hobson & McCarley 1977). The mo-
tor cortex (zone 10 in Fig. 7) also commands movement in
dreaming as evidenced by the pathological expression of
dreamed action in REM sleep behavior disorder (Schenck
et al. 1993), although its output is normally blocked by the
motor atonia of REM sleep (Chase & Morales 1990; Pom-
peiano 1967a). The premotor function of the anterior cin-
gulate cortex (Devinsky et al. 1995) may also contribute to
the experience of fictive movement in dreaming particularly
in regard to emotionally motivated actions.
Visual association cortex (zone 11 in Fig. 7): Areas of the
medial occipital and temporal cortices involved in higher or-
der visual processing, as opposed to primary visual cortex,
generate the visual imagery of dreams (Braun et al. 1998;
Solms 1997a). Specific visual features of dreaming are gener-
ated by the same areas of the visual association cortex involved
in their higher order processing during waking. For example,
areas of the fusiform gyrus are both selectively activated in
REM (Braun et al. 1997; 1998; Nofzinger et al. 1997) and are
the portion of the ventral object recognition stream involved
in face recognition (Kanwisher et al. 1997; McCarthy et al.
1997) which is a common, although often bizarrely uncertain
and altered dream feature. Furthermore, in a very important
recent finding, the same extrastriate ventral occipital areas
are activated during waking hallucinations in patients with
Charles Bonnet syndrome (Ffytche et al. 1998).
REM sleep combines the activation of visual association
(e.g., Brodmann areas 37 and 19) and paralimbic cortices
with the deactivation of primary visual and dorsolateral pre-
frontal cortices (Braun et al. 1997; 1998). The far lesser role
of primary visual cortex (zone 10 in Fig. 7) in REM activa-
tion (Braun et al. 1997; 1998) and dream generation (Solms
1997) combines with the known sensory input and motor
output blockade of REM sleep (Hobson 1988b; see zones 7,
8, and 10 in Fig. 7) to reinforce the concept that sensory in-
formation processing in dreaming may begin at levels down-
stream from primary sensory cortices (Braun et al. 1998).
Inferior parietal lobe (zone 9 in Fig. 7): The inferior pari-
etal lobe, especially Brodmann’s area 40, may generate the
perception of a fictive dream space necessary for the global
experience of dreaming (Solms 1997a). This is a brain re-
gion thought to be important for spatial imagery construc-
tion. Even with visual systems intact, destruction of this
area in either hemisphere causes global cessation of dream-
ing (Solms 1997a). Other neuropsychological studies have
suggested a vital role for this area in dreaming (Doricchi &
Violani 1992). Turning to PET data, Maquet et al. (1996)
note activation of the right parietal operculum despite gen-
eral deactivation in much of the parietal cortex. Interesting
to note, both lesion (Solms 1997a) and PET studies (Ma-
quet et al. 1996) suggest a greater importance to dreaming
of this area in the right versus the left hemisphere.
Dorsolateral prefrontal executive association cortex (zone
4 in Fig. 7): Neuronal modeling (Mamelak & Hobson 1989a)
as well as neuroimaging (Braun et al. 1997; Maquet &
Franck 1997) have suggested a possible origin of dream-
associated executive deficiencies in the REM-associated
changes in frontal lobe functioning. The REM-associated
activation of medial paralimbic frontal cortex contrasts with
the prominent deactivation in the executive portions of the
frontal cortex. The deactivation of the dorsolateral pre-
frontal cortices during sleep and their failure to then reacti-
vate along with medial and parietal cortical structures in
REM sleep underlies the prominent executive deficiencies
of dream mentation.
The left dorsolateral prefrontal cortex has been shown to
be selectively activated during human reasoning tasks (Goel
et al. 1998). Its deactivation could account for the illogical ad
hoc explanations offered for bizarre occurrences (Williams et
al. 1992). Similarly, the dorsolateral prefrontal cortices have
been consistently shown to activate during episodic and
working memory tasks (Brewer et al. 1998; Cohen et al. 1997;
Courtney et al. 1997; Fletcher et al. 1997; Tulving et al. 1996;
Wagner et al. 1998); their deactivation in REM may con-
tribute to the prominent mnemonic deficits in dreaming
noted above in section 2.3.4. The other area found by PET
to deactivate in REM compared to waking was the posterior
cingulate cortex (Braun et al. 1997; Maquet et al. 1996;
Nofzinger et al. 1997). This cortical area, especially its pos-
terior-most retrosplenial portion, has been consistently im-
plicated in episodic memory function with lesions to it re-
sulting in episodic memory deficits (Maddock 1999).
Similarly, the dorsolateral prefrontal cortex is a structure
specialized for the central executive function of working
memory (Baddely 1998; Goldman-Rakic 1996); its deactiva-
tion in REM would thus result in the disorientation and
bizarre uncertainties (Hobson et al. 1987) characteristic of
dream mentation. Failures of working memory are promi-
nent in dreaming. For example, scene shifts are experienced
without reflection (Hobson et al. 1998b). In this sense, the
dreamer could be seen as experiencing a frontal lobe dys-
function similar to “goal neglect” (see Baddely 1998; Dun-
can et al. 1996). Notable also is a recent PET study showing
reduced working memory (WM) task-related activity in the
right midfrontal gyrus in response to cholinergic enhance-
ment with physostigmine (Furey et al. 1997). However,
in this study, improved WM performance also resulted
from cholinergic enhancement (Furey et al. 1997). Finally,
Doricchi et al. (1993) present a convincing argument for an
attenuation of frontal eye field inhibition of reflexive sac-
cades during REM.
Interesting to note, hypoperfusion of the frontal cortex
has been associated with pathological temporal limbic acti-
vation in epilepsy (Rabinowicz et al. 1997) and reciprocal
inhibition between frontal and limbic areas has been hy-
pothesized in theories on the etiology of schizophrenia
(Weinberger 1995). REM sleep dreaming could thus be
seen to involve a normal physiological state of the brain
analogous to psychopathological conditions (Hobson 1994;
1997b; 1999b) in which limbic hyperactivation is combined
with frontal hypoactivation.
Hypothetical dynamic interactions of brain regions
during normal dreaming: In the view of modern cognitive
neuroscience, component subsystems of global states of
consciousness like dreaming are physically instantiated in
networks or circuits each consisting of several to many dis-
crete brain regions (e.g., Cummings 1993; Mesulam 1998;
Nadel 1994).
Mesulam (1998) hypothesizes five global circuits each
subserving a broad cognitive domain: spatial awareness;
Hobson et al.: Dreaming and the brain
language; explicit memory and emotion; face and object
recognition; and working memory-executive function. In
Mesulam’s “selectively distributed processing” model of
these networks, numerous brain regions participate in each
cognitive function as opposed to there being functional
brain “centers” for different aspects of cognition. The same
individual brain region might participate in several func-
tional networks which are differentiated by their compo-
nent nodes (Mesulam 1998).
In a particular network, Mesulam suggests that certain
multimodal nodes or “epicentres” serve to coordinate the
functioning of (or to “bind”) subsidiary nodes and are,
therefore, key to determining this network’s unique cogni-
tive function. For example, epicenters in the transmodal
posterior parietal cortex (e.g., Brodmann area 40) and the
prefrontal cortex (e.g., Brodmann area 46) may coordinate
nodes of a working memory-executive function network
(Mesulam 1998). The same network can affect subcompo-
nents of a more global cognitive function (e.g., explicit
memory) by varying the relative levels of activation in the
component nodes (Mesulam 1998).
We propose that during dreaming relative to waking,
there is a relative dysfacilitation of the working memory-ex-
ecutive function network combined with relative facilitation
of networks subserving emotional and memory consolida-
tion processes. This echoes Braun et al.’s (1997) suggestion
that “the ‘limbic’ loop connecting ventral striatum, anterior
thalamus and paralimbic cortices, appears to be activated
during REM sleep . . . However the prefrontal or ‘associa-
tion’ loop, connecting the caudate, dorsomedial thalamus
and prefrontal cortices . . . appears to be activated only in a
partial or fragmentary way” (p. 1191). Given the sensory
phenomenology of dreaming relative to waking (sect. 2), it
might also be hypothesized that, during dreaming, the effi-
cient functioning of spatial awareness and object recognition
may be better preserved than the language networks result-
ing in predominance of visual versus auditory hallucinosis.
Flow of information between the regions localized by
neuroimaging or lesion studies as crucial to dreaming is un-
doubtedly multidirectional with abundant re-entrant feed-
back and feedforward loops. At present, we propose three
generalizations regarding this information flow: (1) As-
cending arousal systems activate the forebrain regions
involved in dream construction and do so in a manner
chemically and anatomically different from that subserving
waking arousal processes. (2) Cortical circuits activated in
dreaming favor more medial circuits linking posterior asso-
ciation and anterior and posterior paralimbic areas (repre-
sented by central crescent in Fig. 7) versus circuits includ-
ing the primary sensory cortex and/or frontal executive
regions (see Braun et al. 1998). Such a predominance of
medial circuitry in REM may underlie findings from lesion
studies that features of dreaming are only weakly lateralized
(Antrobus 1987; Doricchi & Violani 1992; Solms 1997a). (3)
Subcortical circuits involving the limbic structures, basal
ganglia, diencephalon, and the brainstem contribute
strongly to regional brain activation in REM and, therefore,
probably to the physiological substrate of dreaming.
Very promising new technologies, such as functional
magnetic resonance imaging (e.g., Huang-Hellinger et al.
1995; Portas et al. 1999), transcranial magnetic stimulation
(e.g., Cohrs et al. 1998), magnetic resonance spectroscopy
(e.g., Bartha et al. 1999), receptor radio ligand PET (e.g.,
Sudo et al. 1998), near infrared spectroscopy (e.g., Tagaya
et al. 1999) and dipole tracing (e.g., Inoue et al. 1999b) are
just now being applied to sleep science. Further research
with such tools will undoubtedly further specify the key
brain circuits and systems involved in the global experience
and component elements of dreaming.
Accommodation of NREM dreaming in an updated acti-
vation synthesis model: As explained in detail in section 4,
the AIM model of conscious state control predicts numer-
ous gradations between states as well as possible dissocia-
tions of state characteristics during such transitions. This
occurs because activation, input source, and modulation
can, to some extent, vary independently.
Increased vividness of Stage 2 NREM dreaming near the
end of the normal sleep period has been attributed to cir-
cadian increases in brain activation occurring at this time
(Antrobus et al. 1995; Cicogna et al. 1998). Toward morn-
ing, activation (and perhaps also input source and modu-
lation) may differ the least between Stage 2 periods and
their adjacent REM periods compared to the other times
of the night. Therefore, admixture of REM-like phenom-
ena within Stage 2 NREM (including the brain activation
accompanying REM) may be maximal late in the sleep bout
and may sustain much longer and more vivid NREM
dreaming. In other words, late night Stage 2 NREM dream-
ing may occur during a time when cortical and subcortical
areas linked to dreaming (see Figs. 6 and 7) are becoming
reactivated in anticipation of the next REM period. Alter-
natively, the activation of these areas may not as greatly di-
minish with the transition from late REM to late Stage 2 as
it does earlier in the night during the descent from waking
into slow wave sleep. (For a complete discussion of these
possibilities see Nielsen’s target article.)
Such transitional states might include the human equiv-
alent of the well documented sleep stage termed SP (slow
wave sleep with PGO waves) which heralds REM periods
in the cat (Callaway et al. 1987; Datta 1995) and which has
recently been hypothesized to occur in humans (Gottes-
mann 1999). In humans, recent experimental evidence has
shown enhancement of visual imagery in Stage 2 NREM by
acoustic stimuli below the threshold of awakening but of an
intensity comparable to those triggering PGO waves in an-
imals (Conduit et al. 1997; Drucker-Colin et al. 1983; Mor-
rison et al. 1999). Therefore REM-like tonic (enhanced ac-
tivation) as well as phasic (SP PGO waves) features may
accompany late NREM and enhance dreaming at this time
without in any way contradicting the assumption that REM
sleep phenomena reflect the fullest expression of the phys-
iological substrate of dreaming.
Nielsen (1999; and this volume) has recently proposed a
very similar mechanism for the ubiquity of NREM dream-
ing which he terms “phantom” or “covert” REM sleep. Ac-
cording to this concept, elements of REM-like activation
may commonly occur during NREM without, however,
producing the full complement of signs necessary to score
REM by Rechtschaffen and Kales’s (1968) criteria. Nielsen
suggests several examples of such partial expressions of
REM physiology such as “missing” first REM periods with
EEG desynchrony but lacking REMs or atonia, or NREM
erections occurring with ultradian periodicity. Indeed, re-
cent evidence has shown that the transition from NREM to
REM sleep shows a typical order of appearance of the car-
dinal physiological signs of REM sleep as follows: atonia,
saw-tooth waves, REMs (Sato et al. 1997).
Further candidate markers of “phantom REM sleep” in-
Hobson et al.: Dreaming and the brain
clude the numerous NREM events which investigators
have correlated with mental phenomena ever since the lack
of an exclusive sleep stage correlate to dreaming led them
to seek physiological correlates of dreaming among the dis-
crete phasic physiological events of sleep (Foulkes & Pope
1973; Molinari & Foulkes 1969; Ogilvie et al. 1980; Pivik
1991). For example, within NREM, phasic spinal reflex in-
hibition was associated with greater recall, auditory imagery,
and hostility (Pivik 1991); PIPs (phasic integrated poten-
tials) with enhanced recall (Rechtschaffen et al. 1972); and
sleep onset theta bursts with discontinuity (Foulkes & Pope
1973). Such potential correlates continue to be identified
and include the very rapid eye movements (VREMs) asso-
ciated with K-complexes (Serafetinides 1991) as well as
NREM imagery envoked by external stimuli (Conduit et al.
1997). As psychophysiological techniques in sleep research
become increasingly sophisticated, it is likely that addi-
tional tonic and phasic correlates of sleep mentation will
emerge in studies of both REM and NREM (e.g., Germain
et al. 1999; Miro et al. 1999; Paiva & Guimaraes 1999;
Rochlen et al. 1998; Takeuchi et al. 1999a; 1999b).
3.3.5. Comparison of activation-only to activation-synthe-
sis models’ explanations for the origin of dream imagery
in relation to REM saccades and attentional processes.
Perhaps the greatest disagreement between “activation-
only” models (sect. 3.3.1 above) and the activation-
synthesis model (sect. 3.3.4 above) regards the origin of
dream imagery in relation to REM sleep saccades and
the dreamer’s attentional processes. While the original
activation-synthesis model argues that visual imagery and
eye movements are largely initiated by chaotic brain stem
activity transmitted to the cortex via ascending signals such
as PGO waves (Hobson & McCarley 1977), Antrobus has
argued for a primarily cortical origin for the visual imagery,
REMs and even the PGO waves during dreaming (Antro-
bus 1990; Antrobus et al. 1995). A similar model for a cor-
tical attentionally driven origin of REM saccades is pre-
sented as a revised scanning hypothesis (see below) by
Herman (1992). We will address this controversy by inte-
grating data from studies of neuroimaging, the neurophys-
iology of saccadic eye movement control and attentional
processes. We will show that the relationship of dream im-
agery to REM saccades must involve the integrated activity
of heterogenous brain mechanisms only some of which are
initiated by exclusively top-down or bottom-up processes.
Before launching into this discussion it is important to
situate its significance in a historical context. When REM
sleep was first discovered and assumed to be a unique neu-
rophysiological substrate of dreaming, it was logical to pos-
tulate a one-to-one correlation between the eye movements
and the direction of hallucinated gaze in dreams. This “scan-
ning hypothesis” (Roffwarg et al. 1962) was the strongest
and most specific of the many theories of brain-mind iso-
morphism. In detailing the many difficulties that this the-
ory has encountered, our goal is twofold: first, we want to
emphasize that the field of dream research foundered be-
cause of its overinvestment in still unresolved arguments
about scanning, and second, that promising alternative ap-
proaches to the psychophysiology of dreaming were over-
looked because of this overinvestment. We will conclude
our discussion by an appeal to keep the question of eye
movement and dream imagery open until methods more
adequate to its investigation are developed. Activation-only theories of a cortical origin for
REMs and PGO waves.
Antrobus (1990) and Herman
(1992) interpret the work of Herman et al. (1981; 1983; 1984)
which shows partial confirmation of the scanning hypothesis
(Roffwarg et al. 1962) as supportive of a largely cortical ori-
gin for the neural signals which initiate processes leading to
dream imagery. Antrobus (1990) suggests that when cortical
activation reaches a certain level due to the RAS-mediated
arousal of REM sleep, the frontal eye fields are activated and
begin to attempt to direct the eyes toward the virtual images
being generated in a similarly activated posterior cortex.
In this model, REM saccades are the frontal eye fields’
attempt to foveate on such fictive images and these cortical
signals are transmitted to brainstem oculomotor nuclei via
the same cortico-cerebellar pathways used in the fine-
tuning of waking saccades (Antrobus 1990; Antrobus et al.
1995). PGO waves, in this model, are conceived as being
similarly cortically evoked via cortico-cerebellar pathways
connecting with the brachium conjunctivum, which, in
turn, connects the cerebellum to pontine PGO elements
(Antrobus 1990). In the Antrobus model, PGO waves may
then provide secondary feedback to the frontal eye fields
which remain the original instigator of both REMs and
PGO waves (Antrobus 1990; Antrobus et al. 1995).
The failure of others (e.g., Jacobs et al. 1972; Moskowitz
& Berger 1969) to replicate Roffwarg’s original finding as
well as the dissimilarities between waking and REM sac-
cades are explained in various ways by current proponents
of the scanning hypothesis. Herman (1992) emphasizes that
early studies failed to take into account the dreamer’s fic-
tive head movements which, in dreaming, may coincide
with cortically directed saccades and modify such saccades
via the vestibuloocular reflex. Others suggest that visually
guided, cortically initiated REM eye movements, in con-
trast to waking REMs, are saccadic movements toward sta-
tionary hallucinatory versus moving real targets (Hong et al.
1997). Although such explanations are plausible and are
supported by some data (Herman 1992; Hong et al. 1997),
much more work will be required to fully resolve the con-
flicting findings and daunting methodological challenges
imposed by the various versions of the scanning hypothesis. Contributions from neuroimaging studies of REM
Recently, some investigators have suggested that
neuroimaging technologies can shed new light on the scan-
ning hypothesis. In particular, Antrobus et al. (1995) and
Hong et al. (1997) cite a recent
(FDG) PET study (Hong et al. 1995) as supporting their re-
vised scanning hypothesis. Hong et al. (1995) showed that
REM period eye movement number was positively corre-
lated with glucose uptake in frontal cortical areas associated
with saccadic eye movement control, the midline executive
attentional system, and the visuospatial attentional system.
Other authors have since interpreted these results as gen-
erally supporting visual scanning of the hallucinatory dream
scene (e.g., Gottesmann 1997).
The major drawback of the Hong et al. (1995) study is
that the measured variable was not REM activation relative
to waking or NREM but rather the within REM and within
waking correlations between eye movements and glucose
uptake. Therefore, the only state-dependent comparison
here involves comparing the degree of covariation between
REM counts and cerebral metabolism in regions of inter-
est during waking as compared to during REM. In an ear-
Hobson et al.: Dreaming and the brain
lier analysis of the same data set, this group had compared
actual regional glucose metabolic rate between REM and
waking reporting relatively fewer differences than did later
PET studies (see below) although they did observe rela-
tively greater activation of the anterior cingulate in REM
(Buchsbaum et al. 1989).
Unlike the Hong study, later
O PET studies found
state-specific negative correlations between REM and
cerebral blood flow in the dorsolateral prefrontal cortex
with the positive correlations found instead in pontine
tegmental, thalamic, and subcortical and cortical limbic
structures (Braun et al. 1997; Maquet et al. 1996). Using the
FDG PET method, Nofzinger et al. (1997) also found this
thalamic, amygdala, and cingulate activation. Significantly
for the scanning hypothesis, the
O PET studies (Braun et
al. 1997, 1998; Maquet et al. 1996) did not find relative ac-
tivation during REM, as compared to waking or to NREM,
in many of the saccade and attention-related cortical areas
where Hong et al. (1995) found their positive correlations
between eye movement number and glucose uptake (e.g.,
frontal eye fields, dorsolateral prefrontal cortex, left pari-
etal operculum, precuneus).
It is important to note the significant methodological dif-
ferences between the two PET imaging techniques (see
Braun et al. 1997 and Nofzinger et al. 1997 for discussions).
For example,
FDG techniques integrate cortical activity
over a much longer time than
O PET (30 minutes versus
5 minutes) and thus
O may better characterize shorter,
more discrete PSG-defined sleep conditions (Braun et al.
1997). Therefore, although conclusions from both PET
methods must acknowledge the limitations described above
(sect. 3.1.1), activation of broader areas may be inherent to
FDG compared to
O PET. This difference is evidenced
here by the greater area activated in
FDG studies (Nof-
zinger et al. 1997) compared to
O PET studies (Braun et
al. 1997; Maquet et al. 1996) (see Table 2).
The utility of both methods for testing the scanning hy-
pothesis is, therefore, limited because: (1) neither method
can distinguish between tonic and phasic changes associ-
ated with REM sleep, and (2) neither can provide informa-
tion on whether cortical activation precedes or follows
REMs. Moreover, human PET studies could support either
frontal eye fields and attentional systems being activated in
response to brain stem activity or vice versa.
It seems quite likely to us that both possibilities will prove
to be true. In other words, we suggest that some REM sleep
eye movements are initiated in the brain stem, some in the
frontal eye fields and, possibly, some in other nodes in the
saccade-generation network (e.g., superior colliculus). More-
over, being elements of a network, these loci will robustly
interact. Therefore, in the Hong et al. study, the similar pat-
terns of correlation between metabolic activation and eye
movement counts in both REM sleep and waking is not sur-
prising given the approximately 30 minutes of
FDG up-
take during REM and waking saccade generation. Over this
extended period, many nodes in saccade-generation net-
works may become activated in rough proportion to total
eye movement counts. Contributions from the neurophysiology of sac-
cadic eye movement control.
A heterogeneity among the
brain mechanisms controlling waking saccades in primates is
a widely documented finding (Brooks 1999; Tehovnik et al.
1994) and certain of these circuits are independent of the
frontal eye fields (Tehovnik et al. 1994). Heterogeneity of
REM saccadic eye movement control mechanisms was first
suggested by an extensive series of lesion experiments in Jou-
vet’s laboratory which showed that various forebrain struc-
tures add complexity to eye movements arising in the pons of
cats (Jeannerod et al. 1965). Even the pontine cat, which
lacked all the forebrain structures involved in eye movement
control, still had some eye movements in REM (Jeannerod
et al. 1965; Jouvet 1962). (For a thorough review and inter-
pretation of these lesion studies see Doricchi et al. 1993.) Al-
though citing those studies showing persistence of REMs
and PGOs in decerebrate animals, Herman (1992) and
Antrobus (1990) suggested that the decreased number, loss
of bursting patterns, and stereotyped repetitiveness of REMs
in such preparations indicates that the cortex controls the
phasic components of REMs (presumably directing them to-
ward internal hallucinatory stimuli). In their opinion, such
purely pontine-generated REMs reflect only a tonic, repeti-
tious baseline activation of the oculomotor nuclei while the
cortex controls all potentially information-bearing REMs.
But additional findings must also be explained. For exam-
ple, in the decerebrate cat, Pompeiano has been able to in-
crease the frequency and clustering of REMs simply by in-
creasing the cholinergic drive on the brain stem with
physostigmine (Pompeiano 1980). Recent work in the cat
has further demonstrated a diversity in neural mechanisms
generating the saccades of REM and waking (Vanni-Mercier
& Debilly 1998; Vanni-Mercier et al. 1994) with a specific re-
gion of the pons being implicated in the synchronization of
REMs and PGO waves (Vanni-Mercier & Debilly 1998;
Vanni-Mercier et al. 1996). This proves that the pons is not
only necessary for all REM sleep eye movements but suffi-
cient to generate many of them on its own. Under normal
conditions, however, REM saccades, like those of waking,
are very likely controlled by the final common pathway pon-
tine generator whose output is modified by interactions with
forebrain structures (Goldberg et al. 1991; Hepp et al. 1989;
Ito 1987; Pierrot-Deseilligny et al. 1995), especially interac-
tions between reflexively orienting attentional systems in the
parietal cortex and superior colliculus as has been recently
discovered and elucidated by Doricchi et al (1993). The heterogeneity of attentional mechanisms.
The diversity of attentional mechanisms (see Posner 1994a
and Kinchla 1992) further argues for a heterogeneity of
attentional-oculomotor interaction among behavioral states.
A widely distributed network of interconnected structures
is known to participate in both attentional processes and
the oculomotor control of saccades in waking (see, for ex-
ample, Corbetta et al. 1993; Paus et al. 1993; Petit et al.
1996; Pierrot-Deseilligny et al. 1995; Sweeny et al. 1996;
Wurtz & Munoz 1994). Such structures include those
found by neuroimaging (e.g., Maquet et al. 1996) to be ac-
tivated in REM such as the anterior cingulate cortex (Paus
et al. 1993) as well as those shown to be deactivated in REM
such as the prefrontal cortex (Boch & Goldberg 1989). An
important dissociation between the frontally based atten-
tional modulation of waking saccades and the lack of such
frontal modulation in REM has been described by Doric-
chi et al. (1993; 1996) via the study of hemineglect patients. Systems producing REM saccades with and with-
out participation of cortical attentional structures.
the above-documented diversity and connectivity within
Hobson et al.: Dreaming and the brain
functional brain networks, it is likely that complex, reentrant
interplay between cortical and subcortical structures will de-
termine the relationships between REM saccades, dream im-
agery, and attentional processes (see Doricchi et al. 1993). In
contrast, Antrobus’s theory of an autogenous cortical origin of
REM saccades predicts that phasic activity of the pontine
generator, which must occur to produce any saccade (Gold-
berg et al. 1991), should always follow an initiating event in
the cortex (the hallucinated, attended-to and then “saccaded-
to” dream image). This can be termed a “top-down-only”
mechanism. Contrary to this prediction, we now show that
there are data indicating that pontine brain stem cells fire
prior to REM saccades (a “bottom-up-only” mechanism) as
well as simultaneously with REM saccades (a “mixed bottom-
up and top-down” mechanism) in addition to after a saccade
(as predicted by Antrobus’s “top-down-only” mechanism).
Evidence for bottom-up only mechanisms: In the cat, pon-
tine gigantocellular tegmental field (FTG) cells increase
their firing rate 150 to 100 msec before eye movement (EM)
onset in REM sleep (Pivik et al. 1977). Additional evidence
for subcortical potentials anticipating REMs has recently
been reviewed in Gottesmann (1997). Therefore, pontine
PGO-triggering or transmitting cells may directly excite
paramedian pontine reticular saccade burst cells within the
pons and thereby initiate horizontal saccades whose direc-
tionality is conveyed to the occipital cortex by PGO waves to
elicit visual imagery following the saccade (Hobson & Mc-
Carley 1977). The fact that the primary PGO wave is con-
sistently ipsilateral to the directionality of a REM suggests
that PGO waves can convey eye movement directional in-
formation to the posterior cortex (Datta & Hobson 1994;
Monaco et al. 1984; Nelson et al. 1983). In this regard, it is
also notable that, at the level of the pontine generation sys-
tem, burst cells trigger saccades which are ipsiversive while
at the level of the superior colliculus and above, control is
contralateral (Goldberg et al. 1991). The impingement of
ocular premotor excitatory corollary discharge on PGO
bursting cells in the pons provides a mechanism whereby
such directional information can be transferred from oculo-
motor neurons to rostral structures (Callaway et al. 1987;
Nelson et al. 1983; Steriade et al. 1990).
A collicular intermediary allows mixed bottom-up and
top-down control of REMs: The hypothesis that the supe-
rior colliculus can generate REM saccades independently
of the frontal eye fields was first proposed and elaborated
by Doricchi et al. (1993; 1996). Efferents from the PPT pro-
ject to the superior colliculus (Beninato & Spencer 1986;
Krauthamer et al. 1995; Rye 1997) and most cortical saccade-
generating commands communicate with the brain stem
saccade-generating system via the superior colliculus (Gold-
berg et al. 1991; Sparks & Hartwich-Young 1989). More-
over, the superior colliculus is able to initiate saccades even
when frontal eye fields are damaged (Henik et al. 1994;
Rafal et al. 1990; Tehovnik et al. 1994).
The potential importance of collicular mechanisms to the
generation of REM sleep saccades is further suggested by
the following three findings: (1) In REM sleep of the cat,
superior colliculus damage decreases amplitude of sac-
cades (Jeannerod et al. 1965). (2) In the albino rat, the su-
perior colliculus is essential to the initiation of REM by the
“lights-off” stimulus (Miller et al. 1997). (3) In humans, an
extrageniculate or retinotectal orienting system centered in
the superior colliculus has recently been extensively docu-
mented (Henik et al. 1994; Rafal & Robertson 1994; Rafal
et al. 1990; 1991; Sparks & Groh 1994; Wurtz & Munoz
1994). The failure of leftward hemineglect (i.e., right hemi-
sphere parietal damage) patients to generate leftward
REM-sleep saccades despite preserved (and rehabilitatively
improvable) waking leftward saccades has led Doricchi et al.
(1993; 1996) to propose the predominant involvement of re-
flexively orienting parieto-collicular circuits in the genera-
tion of REM saccades. Doricchi et al. (1993) go on to sug-
gest that subcortically generated impulses (such as PGO
waves) may constitute the endogenous stimuli to which the
parieto-collicular system reflexively responds in REM.
If pontine PGO-triggering or transmitting cells directly
excited collicular cells, then paramedian pontine reticular
saccade burst cells could be excited and produce saccades
without the involvement of cortical saccade-related cen-
ters. Under such conditions, PGO activation of the occipi-
tal cortex via the LGB and PGO-related initiation of sac-
cades could occur simultaneously.
Evidence for top-down only mechanisms: At least some
of the saccades of REM may be commanded by preceding
activity of cortical structures (e.g., frontal eye fields), al-
though even this possibility does not require that the
dreamer is specifically orienting to hallucinated imagery
from the posterior cortex. For example, although the Hong
et al. (1995) PET data suggests that activation of certain
cortical areas is temporally coincident with REM periods
containing a high eye movement density, this correlation
could either indicate causality or simply be secondary to in-
tense PGO-associated activation of multiple cortical foci
(see Amzica & Steriade 1996).
Additional evidence, however, suggests that cortical ini-
tiation of REM sleep saccades is in fact possible. For ex-
ample: (1) REM density is reduced in patients with parietal
damage (Greenberg 1966). (2) Hemi-inattention patients
lose most REM-sleep saccades that are directed toward the
visual field contralateral to their lesion (Doricchi et al. 1991;
1993; 1996) indicating the importance of parietal but not
frontal cortices. (3) Directional eye movements can be vol-
untarily made during lucid REM dreaming (LaBerge et al.
1981). Again, however, none of these findings argue for an
exclusively cortical initiation of REM saccades.
The robust heterogeneity of mechanisms for REM sleep
saccade generation suggests that REM sleep saccades might
differ from waking saccades: Behavioral state-related differ-
ences in saccade generation could arise either from an actual
differential activation of brain regions or from differential
contributions among the multiple cerebral saccade mecha-
nisms (networks) in different behavioral states. And in fact
such differences have frequently been described in both hu-
mans and in animal models (see Doricchi et al. 1993 and
Gottesmann 1997 for recent reviews). For example, in hu-
mans, REM sleep saccades have been shown to be slower
than those occurring during waking (Aserinsky et al. 1985;
Fukuda et al. 1981; Jeannerod & Mouret 1963; Porte 1996).
Moreover, saccades in the two states have been shown to
possess a different velocity/amplitude relationship (Aserin-
sky et al. 1985; Fukuda et al. 1981). Studies of human eye
movements in sleep predating the discovery of REM (re-
viewed by Gottesmann 1997) also revealed eye movements
atypical in comparison to waking eye movements. In hu-
mans, another suggestion of neural control differences be-
tween REM and waking saccades in addition to their disso-
ciation in hemi-inattention patients (Doricchi et al. 1991;
1993; 1996) are the amplitude-related constraints in a re-
Hobson et al.: Dreaming and the brain
ported complementary relationship between experimentally
controlled waking saccades and subsequent saccades in
REM (DeGennaro et al. 1995). One final argument that
REM-sleep saccades do not require the scanning of halluci-
nated dream imagery is the fact that such saccades are ubiq-
uitous in the REM sleep of the congenitally blind who gen-
erally lack all visual dream imagery (Amadeo & Gomez 1966;
Gross et al. 1965; see Weinstein et al. 1991 for a review).
In cats, REM saccades show a differing maximum veloc-
ity/amplitude (main sequence) relationship from that ob-
served in waking (Vanni-Mercier et al. 1994). Moreover, in
monkeys, REM saccades are disjunctive between the two
eyes (Zhou & King 1997) and otherwise unlike those of wak-
ing (Fuchs & Ron 1968) while, unlike wake saccades, the
REM saccades of cats are directionally asymmetrical (Vanni-
Mercier et al. 1994). These results have led the authors of
these three animal studies to argue against the scanning hy-
pothesis. Studies such as these lead Vanni-Mercier et al.
(1994) to conclude that REM and wake saccades do not
share the same neural control circuits and that “eye move-
ments of paradoxical sleep rather represent a stereotyped
repeated pattern which is independent of dream content”
(p. 1301). Authors of one cat study have, however, suggested
that the REM saccades they observed are suggestive of scan-
ning hallucinated imagery (Soh et al. 1992). Conclusion. In conclusion, although some authors
have interpreted the findings of Hong et al. (1995) as evi-
dence for the scanning hypothesis (Antrobus et al. 1995;
Hong et al. 1995; 1997), considerable improvement in tem-
poral and deep structural resolution will be necessary before
such evidence can be considered to be definitive. Such ag-
nosticism is shared by the originator of the scanning hy-
pothesis, Roffwarg (Roffwarg & Belenky 1996), who also
emphasizes the need to visualize both cortical and subcorti-
cal structures simultaneously before assigning the initiation
of REM sleep eye movements to either region. We therefore
regard the question of exactly how the specific visual imagery
of dreams is generated and attended to as being still entirely
open at this time. One way to close this gap would be to com-
pare cerebral blood flow patterns in subjects making di-
rected visual images in waking with directed visual image-
making in lucid REM sleep dreaming. In addition, it may
soon be possible to temporarily deactivate specific cortical
areas with transcranial magnetic stimulation during REM.
4. A new state space model: AIM
As the activation-synthesis model has evolved, it has meta-
morphosed into the three-dimensional framework of the
AIM model. We now update the activation-synthesis con-
cept as follows: (1) high levels of cortical activation (high
values of “A”) are a correlate of the mind’s ability to access
and manipulate significant amounts of stored information
from the brain during dream synthesis; (2) the blockade of
external sensory input and its functional replacement by in-
ternally generated REM sleep events such as PGO waves
(internal sources of “I”) provide the specific activation of
sensory and affective centers that prime the cortex for
dream construction; and (3) the shift of the brain from
aminergic to cholinergic neuromodulation (low ratios of
aminergic to cholinergic neuromodulation, “M”) alters the
mnemonic capacity of the brain-mind and reduces the re-
liability of cortical circuits, increasing the likelihood of
bizarre temporal sequences and associations which are un-
critically accepted as waking reality when we are dreaming.
As the brain shifts from alert waking through drowsiness
to NREM and REM sleep, a concerted set of physiological
and chemical changes occur in the brain and periphery.
Global changes are seen in all major physiological systems,
including the nervous, respiratory, cardiac, renal, immuno-
logical, endocrine, and motor systems (Gottesmann 1997;
Hobson 1989; Orem 1980; 2000). The changes in central
neurophysiology include changes in gating of sensory input,
inhibition of motor output and neuromodulation of wide-
spread regions of the cortex (Gottesmann 1997; Hobson
1988b; Hobson & Steriade 1986; Steriade & McCarley
1990a). More specific neurophysiological changes involve
both tonic and phasic activation of numerous brain regions,
including, but not limited to, the medullary bulbar reticu-
lar formation, the pontine reticular formation, the hypo-
thalamus, the lateral geniculate nucleus, the amygdala, the
hippocampus, and the limbic and unimodal visual associa-
tive cortex, as well as regional deactivation of the dorsal
raphe, locus coeruleus, and multimodal association cortices
(Amzica & Steriade 1996; Braun et al. 1997; Hobson & Ste-
riade 1986; Maquet et al. 1996; Nofzinger et al. 1997; Ste-
riade & McCarley 1990a). (See Table 2 and Fig. 7.) Not sur-
prisingly, these changes are accompanied by dramatic shifts
in the activity of the mind.
In the past, there has been a tendency to describe these
shifting brain-mind states along a single axis, from wide
awake to deeply asleep. The changes in mental state were
perceived as dependent on variations in a single underlying
parameter such as activity of the reticular activation system
or overall brain activity as reflected in the EEG (e.g.,
Moruzzi & Magoun 1949). While conceptually useful at the
time, it was clear from the outset that this activation con-
cept was inadequate. And nowhere was this inadequacy
more evident than in REM sleep, otherwise known as
“paradoxical” sleep specifically because of the dissociation
between level of behavioral arousal (low) and level of brain
activation (high) (e.g., Jouvet & Michel 1959).
In response to this problem, researchers have recently
suggested that the source of inputs for the brain-mind be
considered a second dimension of brain-mind state (e.g.,
Antrobus 1991; Hobson 1990; 1992a). In their analysis of
waking and dreaming, the neurophysiologists Llinas and
Pare (1991) have ascribed all of the differences in subjective
experience to the off-line status of the brain in REM. Like-
wise, the psychologist Antrobus has argued that sensory de-
privation in the wake state produces dreamlike mentation
because: (1) the brain is highly activated as it is in REM sleep
(indicated by high frequency, low amplitude EEG patterns);
and (2) the brain-mind has lost external sensory inputs and,
again as in REM sleep, must turn to internal sources of in-
put (Antrobus 1991; Reinsel et al. 1992). Although these two
parameters tend to shift in concert, with brain activation and
external input sources both decreasing as one moves from
alert waking to deep sleep, such states as REM sleep (high
brain activation and low external inputs) and sleep walking
(low brain activation with some degree of preserved exter-
nal inputs as evidenced by sleep walkers’ ability to navigate)
point out the potential independence of these two axes.
To this two-dimensional model we have added a critical
third dimension which reflects the “mode” of information
processing carried out by the brain-mind, a mode deter-
mined by the action of cortical neuromodulators (Hobson
Hobson et al.: Dreaming and the brain
1990; 1992a; 1997a). Within the brain, widespread cortical
neuromodulation is effected by at least five specific neuro-
transmitters acetylcholine, serotonin, norepinephrine,
dopamine, and histamine (Cooper et al. 1996; Hobson & Ste-
riade 1986; Saper et al. 1997; Steriade & McCarley 1990a)
and probably others such as adenosine (McCarley et al. 1997)
and orexin (Chimelli et al. 1999; Lin et al. 1999). With the ex-
ception of adenosine, each of the above neuromodulatory
substances is produced by a highly localized group of sub-
cortical neurons which project directly to widespread areas
of the forebrain and are known to have powerful effects on
mental state. Three of these acetylcholine, serotonin, and
norepinephrine are known to play critical roles in the tran-
sitions from waking to NREM and then to REM sleep (Hob-
son & Steriade 1986; Steriade & McCarley 1990a).
Histamine and orexin also appear to be involved in sleep-
wake transitions (Saper et al. 1997; Shiromani et al. 1999;
Chimelli et al. 1999). Although dopamine does not appear
to be a prime mover of normal conscious state regulation
(Miller et al. 1983; Steinfels et al. 1983), it probably plays a
major if perhaps secondary role in sleep regulation as evi-
denced by its interactions with other neuromodulatory sys-
tems (e.g., Kapur & Remington 1996; Mamelak 1991), its
effects on normal sleep (Gillin et al. 1973; Olive et al. 1998;
Post et al. 1974; Python et al. 1996; Trampus et al. 1993),
and the effects of REM sleep deprivation on dopaminergic
neurotransmission (Brock et al. 1995; Nunes et al. 1994; Tu-
fik et al. 1978). It is thus not surprising that most of the psy-
chopharmacological drugs used today which directly affect
this neuromodulatory mode (Function M), often alter sleep
and dreaming as well (e.g., Armitage et al. 1995; Lepkifker
et al. 1995; Markowitz 1991; Pace-Schott et al. 1998; 1999;
2001; Sharf et al. 1978; Silvestri et al. 1998; in press; Vogel
1975; Vogel et al. 1990).
We have described this three-dimensional model of
brain-mind state in our “AIM Model” (Hobson 1990; 1992a;
1997a; Hobson & Stickgold 1994b; Kahn et al. 1997). AIM
makes three major claims:
1. AIM proposes that conscious states are in large part
determined by three interdependent processes, namely the
level of brain activation (“A”), the origin of inputs (“I”) to
the activated areas, and the relative levels of activation of
aminergic (noradrenergic and serotonergic) and choliner-
gic neuromodulators (“M”). While these variables tend to
vary in concert with one another, many paradoxical and dis-
sociated mental states, both normal and abnormal, arise
from the sometimes strikingly independent variation of
these parameters as we will shortly illustrate.
2. The AIM Model proposes that the universe of possible
brain-mind states can be construed as a three-dimensional
state space, with axes A, I, and M (activation, input, and
mode), and that the state of the brain-mind at any given in-
stant of time can be described as a point in this space. Since
the AIM model represents brain-mind state as a sequence
of points, time is a fourth dimension of the model.
3. The AIM model proposes that while stable and re-
producible mental states reflect the tendency of the brain-
mind to occupy a small number of fixed locations in this
state space, corresponding to such identified brain-mind
states as alert wake or vivid REM sleep dreaming (see Kahn
et al. 1997), all three parameters defining the state space
are continuous variables, and any point in the state space
can in theory be occupied. In the remainder of this section,
we will discuss each of these three claims in detail.
4.1. The three dimensions of the state space
Experimental testing of the AIM Model requires that each of
the three parametric axes of the brain-mind state space be di-
rectly measured and, ideally, manipulated. Toward this end,
we have attempted to define the underlying parameters as
well as to indicate how they can best be measured (see again
Fig. 1). As we shall show below, reasonable measures of A and
I can be readily obtained in both humans and animals. At the
present time, M can only be measured directly in animals, but
because its value can be manipulated experimentally in hu-
mans with pharmacological agents, its role in human con-
scious state determination can be indirectly assessed.
4.1.1. Activation. Conscious states show a clear-cut depen-
dence on brain activation level. The production of con-
scious experience, as reflected in the length, intensity, and
complexity of subjective reports of mental activity, as well
as in levels of arousal and alertness, is generally greater in
waking and in REM sleep than it is in deep NREM sleep
and greater in alert waking than in quiet resting. The AIM
model predicts that this physiological measure, “A,” reflects
the rate at which the brain-mind can process information
regardless of its source (measured as “I”) or its mode of pro-
cessing (“M”). This activation parameter is based upon
Moruzzi and Magoun’s concept of a reticular activating sys-
tem (Moruzzi & Magoun 1949; Steriade et al. 1980). Broad
consensus already exists for the importance of this first di-
mension of the AIM Model.
In its simplest form, brain activation is defined as the mean
firing frequency of brain stem neurons. It can be approxi-
mated in both humans and animals from the EEG spectrum,
with increasing activation reflected by relatively high power
in the high frequency range and relatively low power at low
frequencies. In animals, the activity of the reticular activat-
ing system can be precisely quantified from the frequency of
firing of neurons in the midbrain reticular formation (Hut-
tenlocher 1961; Kasamatsu 1970; Steriade et al. 1980).
In humans, an alternative measure of overall brain acti-
vation might be the level of gamma frequency (3070 Hz)
oscillation in the brain (Llinas & Ribary 1993; Llinas et al.
1994). Although some recent work questions the associa-
tion of gamma oscillation with REM sleep (Germain &
Nielsen 1996), other work appears to confirm it (Uchida et
al. 1997). Such gamma activity in humans has been shown
to correlate with discrete cognitive events (Lutzenberger et
al. 1995; Muller et al. 1996; Tallon-Baudry & Bertrand
1999; Tallon-Baudry et al. 1996; 1997; 1998) and to be mea-
surable with depth electrodes in the human medial tempo-
ral lobe (Hirai et al. 1999).
4.1.2. Input source. Waking, NREM sleep and REM sleep
represent states in which the sources of information
processed by the brain differ dramatically. The second pa-
rameter of our AIM Model, input source (I), is a measure of
the extent to which the brain-mind is processing external
sensory data impinging upon receptors (as it is in waking) or
from internal data sources (as in day dreaming or REM
sleep). Because one component of sensory input is proprio-
ceptive feedback reflecting the extent of motor activity, we
also include the efficacy of such feedback in parameter I. In-
ternally generated pseudosensory data can be produced by
brain stem mechanisms (e.g., via PGO stimulation of visual
cortex in REM sleep), it can be recalled from memory, or it
can be intentionally created by directed mental imagery.
Hobson et al.: Dreaming and the brain
In alert waking, the contents of our conscious experience
(e.g., our thoughts and our feelings) tend to be driven by ex-
ternal stimuli and are predictive of subsequent motor be-
havior. During sleep, in contrast, conscious experience is
normally driven by internally generated stimuli and has no
apparent behavioral consequence. In the AIM Model, wak-
ing is characterized as both more exteroceptive and ex-
teroeffective than either NREM or REM sleep, while
REM sleep is markedly more interoceptive than NREM
sleep but less exteroeffective than either waking or NREM
This second dimension of our AIM Model, though ro-
bust, has not been specified by many cognitive theorists
who tend to regard internally generated signals as simply
the phasic intensification of activation level. Such a view ig-
nores what to us are very significant differences in such
mental functions as vision, visual imagery, and visual hallu-
cination. But while some seem to consider it an irrelevant
factor, Llinas and Pare (1991) have suggested that this di-
mension by itself could be an adequate explanation of the
phenomenological differences between such high activa-
tion states as waking and REM sleep (Llinas & Pare 1991).
We agree with Llinas and Pare that both in waking and in
sleeping, input source represents a major determinant of
the nature of conscious experience. However, we do not re-
gard the differences in input source to be an adequate ex-
planation of the phenomenological distinction between
waking and dreaming. How, for example, could it account
for dream forgetting or the relatively low visual intensity
and bizarreness of daydreams?
Physiologically, the input source axis of the AIM Model
reflects both input-output gating and nonsensory activation
of sensorimotor cortices. The activation of these cortical re-
gions by external sensory stimuli can be directly measured
in humans using evoked potential (ERP) techniques (e.g.,
Niiyama et al. 1997; Sallinen et al. 1996) or using stimulus
threshold studies (see Arkin & Antrobus 1978 and Price &
Kremen 1980 for reviews). In this regard, it is notable that
Price and Kremen (1980) measured a rise in auditory stim-
ulus threshold and Sallinen et al. (1996) observed a de-
creased ERP response in human phasic compared to tonic
REM sleep. Similarly, the H-reflex can be used to measure
motor blockade (Hodes & Dement 1964). In animals the
same measures can be obtained and complemented by
more refined assessments. For example, the amount of
presynaptic inhibition of 1A afferent terminals (Bizzi &
Brooks 1963; Pompeiano 1967b) specifically measures the
sensory gate function while the amount of motoneuronal
hyperpolarization (Chase & Morales 1990; Pompeiano
1967a) measures gating of motor activity. (For a recent re-
view of such measurements see Gottesmann 1997.)
In humans and animals, eye movement density in REM
sleep provides an estimate of the amount of internally gen-
erated pseudosensory data because eye movement density
reflects brain stem PGO and motor pattern generator ac-
tivity. In addition, the frequency of PGO waves (or the burst
intensity of PGO waves) can be measured in animals to
determine this parameter more directly. Currently, PGO
waves cannot be easily or confidently recorded from hu-
mans although numerous suggestive EEG findings have
been reported (McCarley et al. 1983; Miyauchi et al. 1987;
1990; Niiyama et al. 1988; Salzarulo et al. 1975 ) and new
dipole tracing techniques show promise in identifying hu-
man PGO waves (Inoue et al. 1999b).
4.1.3. Modulation. The third major and clear-cut physio-
logical difference among waking, REM, and NREM is in
the neuromodulation of the brain. In the AIM Model, we
focus on the marked shift in modulatory balance seen from
aminergic (noradrenergic and serotonergic) predominance
in waking to cholinergic predominance in the REM sleep
of animals. We call this modulatory factor M and define it
as the ratio of aminergic to cholinergic chemical influence
upon the brain.
It is our contention that this shift of neuromodulatory
balance underlies the similar modal shifts in information
processing (data processing, storage, and retrieval) seen as
the brain shifts from one wake-sleep state to another. We
propose that this modulatory factor M is involved in the reg-
ulation of such conscious state functions as directed atten-
tion, deliberate thought, self reflective awareness, orienta-
tion, emotion, memory, and insight. All of these functions
are altered in the transition from waking to NREM sleep as
a function of the diminished activation and sensory input
level. But their even more marked dramatic alteration in
dreaming, when the activation level is as high as in waking,
must have another brain basis, which we think the changes
in input-output gating alone are inadequate to explain. This
element of our model has found little support among sleep
psychologists who, we believe, either have failed to fully ap-
preciate the extent of the alteration of cognitive features
(such as the defective memory of REM sleep) or have sim-
ply rejected the concept of a neurophysiological description
of psychological phenomenology (for one exception see
Hartmann 1982).
Measurement of “M” is based on comparing the rates of
firing or amounts of transmitter released by norepinephrine-
containing locus coeruleus neurons and serotonin-contain-
ing raphe neurons to that of putatively cholinergic, PGO
burst cells in the peribrachial region. State-dependent shifts
in this parameter have been extensively documented in an-
imal models (Datta 1995; 1997b; Foote et al. 1983; Hobson
1992b; Hobson & Steriade 1986; Hobson et al. 1986; Jacobs
& Azmita 1992; Lin et al. 1994; Sanford et al. 1995b; Sherin
et al. 1996; Steriade & Biesold 1990; Steriade & Hobson
1976; Steriade & McCarley 1990a; Szymusiak 1995). A
more accurate measure of this parameter may be obtained
by the simultaneous measure of release of the two classes
of modulator using microdialysis techniques (e.g., Kodama
& Honda 1996; Lydic et al. 1991b; Portas et al. 1998; Wil-
liams et al. 1994). Unfortunately, methodological constraints
have so far largely prevented the measurement of this pa-
rameter in humans (although see Bartha et al. 1999; Sudo
et al. 1998; Wilson et al. 1997). Evidence that such changes
occur, and are significant, in humans is indirect but consis-
tently confirmatory.
The role of this parameter in human conscious experi-
ence has been extensively studied in waking experiments
using drugs known to alter neuromodulatory balance (see
Perry & Perry 1995; Perry et al. 1999). In addition, cholin-
ergic stimulation has been found to potentiate REM sleep
(Berger et al. 1989; Gillin et al. 1991; Sitaram et al. 1976;
1978b) and dreaming (Sitaram et al. 1978a) while many
aminergic agents are known to have REM suppressive and
alerting effects (Gaillard et al. 1994; Nicholson et al. 1989)
as well as effects on dreaming (Hobson & Pace-Schott
1999; Thompson & Pierce 1999). Reviews of psychophar-
macological evidence suggests that the role of modulation
in humans is homologous to that in experimental animals
Hobson et al.: Dreaming and the brain
(e.g., Everitt & Robbins 1997; Hasselmo 1999; Perry &
Perry 1995; Robbins & Everitt 1995).
An important aspect of the AIM model is its effort to mir-
ror cognition’s psychological features in its three physiolog-
ical dimensions. Thus, “Activation” has a specific meaning
at both the neurobiological and cognitive levels (see An-
derson’s ACT* model; Anderson 1983). Cognitivists also
speak of information processing and thus share the concept
of “input source” with neurobiologists, who express this di-
mension in terms of sensory thresholds, the excitability of
motor pattern and efferent copy circuits, and the threshold
for motor output. Finally, the mode concept is important to
cognitivists as a memory/amnesia dimension (as well as,
possibly, an attention/inattention axis) while neurobiolo-
gists represent mode as the ratio of aminergic to choliner-
gic neuromodulator release. It is by these formal homolo-
gies between neurobiology and the cognitive sciences that
the AIM model attempts to produce an integrated picture
of the brain-mind.
An initial attempt to model the neuroanatomical struc-
tures participating in REM-state-dependent changes in ac-
tivation, input source and neuromodulation is illustrated in
Figure 8.
4.2. The AIM state space
The AIM model proposes that conscious states can be de-
fined and distinguished from one another by the values of
three parameters. These parameters can be considered as
the axes of a three-dimensional state space. This state space
can be represented visually as a cube where normal values
for the parameters range along the three axes (Figs. 1 and
9). The model is not only useful in representing normal
states but is also helpful as a heuristic tool to illustrate sev-
eral critical issues in sleep research.
In quantitative renditions of the model (Hobson 1990;
1992a) the activation parameter (A) was derived from ei-
ther the mean rate of firing of reticular formation neuronal
populations that varies in animals from a low of 25/second
in NREM sleep to 50/second in REM or from the inverse
of the voltage amplitude of the EEG which varies from 25
50 mV in waking to 150200 mV in Stage IV NREM sleep
in humans. A four-fold range of values is assumed in visual
representations of the model. The input source parameter
can be derived from arousal threshold or H-reflex ampli-
tude in humans or PGO wave frequency in animals. The
range of these values is roughly the same order of magni-
tude as factor A. The modulatory parameter, M, is derived
from the mean rate of neuronal population discharge of the
aminergic populations (24 cycles/second in waking, 12
cycles/second in NREM, 0.010.1 cycles/second in REM)
or from the concentration of norepinephrine, serotonin or
acetylcholine in microdialysis studies which vary over a
range of about 10-fold (Hobson & Steriade 1986; McCar-
ley & Steriade 1990; Steriade & Hobson 1976).
All the parameters of the model are known to vary over the
sleep cycle in a nonlinear manner. For example, factor M has
a clearly exponential deceleration in the NREM-REM tran-
sition. Some aspects of this nonlinearity are embodied in ear-
lier mathematical modeling of the reciprocal interaction
model using the Volterra-Lotka equations (McCarley & Hob-
son 1975; McCarley & Massaquoi 1986) which yield ellipses
as the graphical representation of the sleep cycle.
We acknowledge the tentative and necessarily specula-
tive nature of our assumption of homology across mam-
malian sleep mechanisms, but point out that it is supported
by abundant indirect evidence. And we recognize one im-
portant exception to this homology assumption: the relative
complexity of the human forebrain gives rise to a greater
complexity of EEG patterns in human NREM sleep com-
pared to animals. We believe that this complexity is un-
derestimated by currently available measures and that ac-
tivation models of cognition likewise underestimate the
differences between NREM states.
We do not pretend to have solved the problem of model-
ing conscious states, only to have proposed more realistic and
Hobson et al.: Dreaming and the brain
Figure 8. Physiological signs and regional brain mechanisms of
REM sleep dreaming separated into the activation (A), input
source (I) and modulation (M) functional components of the AIM
model. Dynamic changes in A, I, and M during REM sleep dream-
ing are noted adjacent to each figure. Note that these are highly
schematized depictions which illustrate global processes and do
not attempt to comprehensively detail all the brain structures and
their interactions which may be involved in REM sleep dreaming
(see text and Table 2 for additional anatomic details).
heuristically valuable approaches to this problem. AIM con-
stitutes only a simplified framework for modeling the physi-
ology underlying changes of behavioral state and we in no
way claim that it can fully account for the wide variety of hu-
man subjective experience, which includes thought, imagery,
fantasy, and altered or pathological states as well as dream-
ing. Moreover, we recognize that the axes of the AIM state
space are not independent. For example, at sleep onset a de-
cline in general activation is likely to parallel a decline in
aminergic modulation and a decline in the strength of exter-
nal stimulus drive. Likewise at REM sleep onset the steep
rise in cholinergic activity is likely to parallel the rise in in-
ternal stimulus drive and a rise in general activation level. But
the axes of the model are uniquely capable of accounting for
just the kinds of paradoxes that arise from an interactive sys-
tem that changes its states paradoxically: that is, has high lev-
els of activation in both waking and REM sleep; shifts from
external to internal stimulus processing; and processes infor-
mation differently in two equally activated states.
Current developments in basic and clinical neurobiology
suggest the exciting possibility that the M dimension may
become measurable in behaving (i.e., waking, thinking, per-
forming, sleeping, dreaming) human beings. Already, mi-
crodialysis techniques with depth electrodes implanted to
localize epileptic foci have shown fluctuations in serotonin
across the wake-NREM-REM cycle paralleling those seen
in animals (Wilson et al. 1997). Moreover, the newest PET
techniques for radiolabeling receptor ligands as well as
magnetic resonance spectroscopy (Rauch & Renshaw 1995)
may yield further possibilities for the localization and quan-
titation of neuromodulatory dynamics in the human CNS.
One use of the AIM model is to depict the highly dy-
namic and variable nature of human consciousness, and
thus to visually plot specific “states” of consciousness within
the state space. As an example, normal consciousness, at the
coarsest level, can be divided into the states of waking,
REM, and NREM sleep. Each of these states can be char-
acterized both by distinct physiologies and by distinct dif-
ferences in mentation. To help the reader orient to the AIM
state space, the positions of these three states in the AIM
state space, as well as the trajectory from waking through
NREM into REM sleep, are shown in Figure 9.
In this figure, the fully alert, wake state is depicted in the
upper-right corner of the back plane of the cube. This cor-
responds to maximal levels of brain activation (right surface
of cube), maximal external input sources with minimal in-
ternal sources (back surface), and maximal aminergic and
minimal cholinergic neuromodulation (top surface). Cog-
nitively, this corresponds to alertness with attention focused
on the outside world.
In the center of the cube lies deep NREM sleep, with
low levels of brain activation, intermediate levels of both
aminergic and cholinergic neuromodulation, and minimal
levels of both external and internal input. In this state, the
mind tends towards perseverative, non-progressive think-
ing with minimal hallucinatory activity, and this is reflected
in the brevity and poverty of NREM sleep reports.
As cholinergic modulation increases and aminergic mod-
ulation decreases, the modulatory function falls to its low
point. The brain-mind, however, regains waking levels of
activation and moves from NREM into REM sleep. AIM
(now referring to the brain’s location in the AIM state
space) moves to the bottom front edge of the cube, with in-
put now internally driven (front surface) and neuromodu-
lation predominantly cholinergic (bottom surface). We em-
phasize the paradox that instead of moving to the left
surface of the cube to a position diametrically opposed to
waking (dotted line) – brain activation returns to waking
level. This forces AIM to the right surface of the cube. As a
result the mind is alert, but because it is demodulated and
driven by powerful internal stimuli, it becomes both hallu-
cinatory and unfocused. REM sleep’s deviation from the
main diagonal axis provides a visual representation of the
distinctively unique phenomenology of REM sleep and
shows why that state favors dreaming.
A second function of the AIM state space model is as a
tool to clarify the concept of substates. While consciousness
can be coarsely divided into waking, REM, and NREM
sleep, these are only a few of many possible brain-mind
states. For example, NREM sleep can be subdivided on
physiological bases into substates: sleep onset, Stage II of
NREM sleep, and deep Stages III and IV NREM sleep.
Presumably, sleep mentation changes in concert with these
physiological changes. Similarly, REM sleep can be subdi-
vided physiologically into phasic and tonic REM or psy-
chologically into lucid and nonlucid dreaming substates.
Finally, the waking state can be subdivided into a vast mul-
tiplicity of substates, defined by attentive parameters (alert,
attentive, vigilant vs. drowsy, inattentive, day dreaming),
emotional parameters (calm, angry, sad, afraid), or even
by information processing strategies (focused and goal di-
rected vs. creative and freely associating). Other substates
of waking can be produced by specific induction proce-
dures, such as trance, hypnosis, sleep deprivation, and by
the ingestion of psychoactive drugs.
For each of these substates, a subregion of AIM state space
could, in theory, be defined which would characterize its
physiological and psychological nature. However, as the dis-
tinctions between states become more subtle, these regions
necessarily begin to overlap and blur. At the same time, the
three dimensions of the AIM model quickly become inade-
quate. For example, the model is strained to account for dif-
ferences between various emotional substates of waking.
This could be partially resolved by adding a regional activa-
tion dimension to our model, such as the ratio of limbic to
neocortical activation as suggested by neuroimaging studies
(e.g., Maquet et al. 1996; Nofzinger et al. 1997).
Could the changes in regional activation of the brain be
related to the shift in neuromodulatory balance that we have
Hobson et al.: Dreaming and the brain
Figure 9. Normal transitioning within the AIM state space from
wake to NREM and then to REM.
Hobson et al.: Dreaming and the brain
described? It seems likely to us that the changes in regional
activation (A
) are a combined function of changes in I and
M so that, for example, it is the cholinergic pathway from
pons to amygdala that is responsible for the selective activa-
tion of the limbic brain in REM sleep. Similarly, it could be
that the deactivation of the frontal lobe is caused by the with-
drawal of aminergic inputs to that region in REM sleep.
These suggestions are not simply ways of saving the model’s
relative simplicity. Rather they demonstrate the capacity of
the model to generate new, testable hypotheses about the
cellular and molecular basis of regional brain activations.
4.2.1. Dissociated states. Given the multiplicity of param-
eters contributing to conscious states and the complex dy-
namics of their interaction, it is to the credit of evolution-
ary tinkering that the cardinal states of wake, NREM, and
REM sleep appear so discrete and that their temporal se-
quence is normally so canonical. But this discreteness and
canonical sequencing is only approximate. As the AIM
state-space model attempts to make clear, any point within
the state space can be occupied, and the parametric values
which define the canonical states of waking, NREM, and
REM sleep can be dissociated from one another. As a re-
sult, the appearance of dissociated states states in which,
for example, some parameters match their canonical NREM
values while others match canonical REM or wake values
should be considered both natural and inevitable. Ac-
knowledging this propensity of the conscious state system
to dissociate enriches our view of both normal and abnor-
mal neurological and psychiatric conditions.
These dissociations occur most commonly during the tran-
sition from one stable state to another as exemplified by state
carry-over phenomena tapped by neurocognitive and psy-
chological testing following the awakening of human subjects
from NREM and REM sleep (Bonnet 1983; Doricchi et al.
1991; 1993; Fiss et al. 1966; Gordon et al. 1982; Lavie 1974b;
Lavie & Giora 1975; Lavie & Sutter 1975; Rittenhouse et al.
1993; Rosenblatt et al. 1992; Stickgold et al. 1999b; Stones
1977), with perhaps the best known of these being the per-
sistent lethargy termed as “sleep inertia” (Achermann et al.
1995; Dinges 1990). In such cases, the transitions of some pa-
rameters lag behind those of others and the dissociations are
usually quite transient. But in other cases, they are more sta-
ble, as in sleep walking (Broughton 1968; Guilleminault
1987), where waking values of locomotor output are reached
in NREM sleep. Interesting to note, recent PET data have
shown persistence of selective deactivation, especially in the
prefrontal and posterior inferior cortices, for more than 5
minutes post awakening from Stage 2 sleep (Balkin et al.
1999). Many of these dissociated states can be represented
using the AIM state space model.
Thus, another function of the model is to organize and vi-
sually represent some of the conscious state dissociations seen
in normal subjects, in patients with neurological and psychi-
atric symptoms, and in both groups when treated with drugs
that affect brain neuromodulatory systems. The basic concept
that we wish to convey is that while the three dimensions of
AIM state space usually change synchronously as the brain-
mind shifts between the three stable canonical states, genetic
bias, life events, and pharmaceutical intervention can all con-
spire either to desynchronize the shifts occurring along the
three axes or to create new stable states in which one or an-
other dimension takes on an unexpected value.
The net result is a departure from the usual trajectory
(shown in Fig. 9) or the creation of normal-hybrid states
with mixtures of wake, NREM, and REM features as sug-
gested in Figures 1018. In these examples, dissociations
along each of the three axes of the state space are examined.
It should be emphasized that the discussion that follows is
speculative and is intended to be heuristic rather than de-
finitive. Although we have chosen examples that we believe
to be realistic and have made assumptions that we hold to
be reasonable, empirical tests of these hypotheses remain
to be conducted.
4.2.2. Activation. To illustrate the vicissitudes of the activa-
tion function, we consider two normal phenomena, quiet
waking and sleep onset, which are related to each other in
ways that have a critical bearing on the issues discussed ear-
lier in our target article. We will show how both quiet waking
and the transition from wake to sleep may vary significantly
depending upon the current level and the rate of change of
the activation function. The transitional state of sleep onset
has been extensively studied because of the unique mentation
reports that can be obtained on arousal from this state. Yet the
exact position of sleep onset in AIM state space is critically de-
pendent on the precise temporal pattern of sleep onset.
Quiet waking: We first consider the period of quiet wak-
ing preceding sleep onset. Before lying down and closing
his eyes, a subject is usually in an alert state (see again Fig.
9, “Wake”). Normally, on lying down and closing his eyes,
he will shift into an alpha wave EEG pattern, reflecting a
decrease in “A” and, because visual stimulation has been
shut off, a decrease in “I” as well. At the same time, neuro-
modulatory shifts may begin to decrease aminergic output.
Thus, he will begin to move along the main axis from Wake
toward NREM, as indicated in Figure 9.
But when examined in detail, each individual will take a
unique path through the state space from waking to NREM,
depending on both the relative and absolute rates of decline
of each of the three state space parameters. For example, if
an individual is drowsy before retiring (Fig. 10, “Drowsy”),
Figure 10. Quiet rest: Movement within the AIM state space
prior to sleep onset depends on how sleepy the subject is as well
as the extent of external sensory input.
Hobson et al.: Dreaming and the brain
values for “A” and perhaps also “M” will begin to drop well
before the subject even goes to bed, while “I” remains high,
placing one in the center of the back surface of the cube. In
contrast, if an individual is quite alert when going to bed, “I”
might drop before either “A” or “M” (not shown), followed
by a small drop in “A” as alpha patterns appear in the EEG.
Under other conditions of quiet waking, such as when sub-
jects were placed in a darkened, sound attenuated room by
Antrobus in his “waking controls” for dream mentation
(Reinsel et al. 1992), “I” would immediately shift because of
the elimination of external sensory stimulation, and we ex-
pect that “M” would then slowly shift to relatively low values
while “A” stayed high, placing one in the center of the right-
hand surface of the cube (Fig. 10, “Sensory Restriction”).
Under these conditions, the brain-mind state moves to a po-
sition midway between waking and REM sleep (cf. Fig. 9),
rather than between waking and NREM. It is therefore not
surprising to us that Reinsel et al. (1992) found that menta-
tion became more dreamlike under these waking conditions.
We can use the AIM state space model to investigate the
implications of Antrobus’s paradigm. Since “I” falls virtually
instantaneously upon being placed in the dark, AIM should
initially occupy a position in the state space just in front of
normal waking, with only “I” decreased. Then, over time,
neuromodulatory shifts would move AIM lower in the state
space, to the position shown in Figure 10 (“Sensory Re-
striction”). Because the AIM model hypothesized that “M”
plays an important role in modulating cognitive processes,
we would expect reports to become more and more dream-
like over the first 5 to 10 minutes in this condition. In con-
trast, Antrobus’s activation-only model would seem to pre-
dict that reports should become less dreamlike with time,
since activation would be expected to drop during quiet
wake as EEG alpha increases. In fact, hallucinosis has been
shown to increase over time as arousal diminishes during
sensory deprivation protocols (Rossi et al. 1964). Indeed, it
would be quite surprising to find mentation becoming more
wakelike and less dreamlike with an increased period of
waking sensory deprivation.
Sleep onset: As the subject moves from wake to sleep on-
set, further movement occurs within the state space (Fig.
11). The box labeled “Rapid” in Figure 11 represents a pos-
sible initial sleep onset state when the transition from wak-
ing to sleep is precipitous following sleep deprivation. In
this case, the transition occurs before there is time for amin-
ergic neuromodulatory levels to decrease. As a result, the
“M” function remains on the top surface of the cube (mod-
ulation highly aminergic) while brain activation and exter-
nal inputs diminish. In contrast, the box labeled “Slow”
(Fig. 11) represents a gradual transition from waking to
sleep as might be seen in situational insomnia. In this case,
decreases in aminergic neuromodulation and external in-
puts might occur prior to the decrease in brain activation.
In both cases, AIM would then move into the standard
Stage NREM position (Fig. 9).
Lucid dreaming: Another dissociation along the “A” axis of
the AIM cube may arise during lucid dreaming. Under nor-
mal circumstances, dreamers believe themselves to be awake
but occasionally individuals become aware that they are
dreaming. In this state of “lucid dreaming” (Laberge 1990;
1992) waking insight combines with dream hallucinosis in
an intriguing and informative dissociation. We assume that
for lucidity to occur, the normally deactivated dorsolateral
prefrontal cortex (DLPFC) must be reactivated but not so
strongly as to suppress the pontolimbic systems signals to it.
This dissociation is represented in the AIM model by split-
ting AIM so the portion representing the DLPFC can take a
position dissociated from that of the rest of the brain (Fig.
12). When this partial reactivation of the DLPFC occurs, in-
ternally generated images are seen for what they are and are
not misinterpreted as coming from the outside world.
The fact that lucidity can arise when the DLPFC is de-
activated can also be explained using AIM. Lucid dreaming
occurs spontaneously or can be cultivated by pre-sleep au-
tosuggestion. Spontaneous lucidity indicates that the re-
duced amount of reflective self-awareness during dreaming
is sometimes enhanced enough for the subject to recognize
the dream state for what it is. Autosuggestion probably
increases this probability by priming the brain circuitry
presumably in prefrontal areas that subserves self-re-
flective awareness. In both cases, the phenomenon of lu-
cidity clearly illustrates the always statistical and always dis-
sociable quality of brain-mind states. AIM accommodates
Figure 11. Sleep onset: With more rapid sleep onset, lowered
activation precedes aminergic demodulation; with slow onset, the
order is reversed.
Figure 12. Lucid dreaming: Prefrontal cortical systems, which
are normally inactive in REM sleep, shift toward higher, wake-like
levels of activation, permitting conscious awareness of the dream
these features very well by proposing that lucid dreaming is
a hybrid state lying across the wake-REM interface.
4.2.3. Input source. During waking, internal inputs are used
mainly in the service of the ongoing sensorimotor integration
of external signals. If, for any reason, internal signals became
unusually strong, they could come to dominate the system
with resulting hallucinosis. In this case, mentation would be
driven by a combination of undifferentiated internally and
externally driven imagery (see Mahowald et al. 1998).
Hypnagogic and hypnopompic hallucination: From the
perspective of the AIM model, hypnagogic and hypnopom-
pic hallucinations, associated with transitions into and out
of sleep respectively, result from the REM-like enhance-
ment of internal stimuli coupled with an activated, aminer-
gically modulated waking brain (Figs. 13 and 14).
With internal and external inputs in an unstable balance
(as occur during the hypnagogic period), AIM moves to a
position half-way between the front and back surfaces of
the cube (Fig. 13). But unlike NREM sleep, which is also
at this midpoint of input source (with minimal internal and
external inputs), both sources are being powerfully driven
in hallucinosis. It is this unexpected combination of high in-
ternal and high external inputs that defines the functional
dissociation of these hallucinoid states. The frequency of
this combination may be elevated by the abnormal physiol-
ogy of narcolepsy, a condition in which the frequency of hyp-
nagogic hallucinations is likewise elevated (Broughton et al.
1982; Mignot & Nishino 1999; also see Fasse 2000).
We can approximate a representation of the hypnopom-
pic hallucinoid state by hypothesizing that while the brain-
stem signals continue to evoke internal representations in
the cortex in the hypnopompic period, the blockade of ex-
ternal stimuli has broken down. As a result, the dissociated
state results from a dissociation of the forebrain from the
brainstem. This dissociation is represented in the AIM
model by splitting the cube representing the brain-mind
into forebrain (F) and brainstem (B) sections and showing
their relative positions in AIM space (Fig. 14).
A more extreme example of this kind of dissociation is tem-
poral lobe epilepsy in which abnormal phasic activation sig-
nals of limbic origin commandeer the cortex and force it to
process external world data on limbic terms (e.g., Rabinowicz
et al. 1997). Given the new findings on selective limbic acti-
vation in REM sleep (Braun et al. 1997; 1998; Maquet et al.
1996; Nofzinger et al. 1997), it seems reasonable to suppose
that a similar, though normal, process may also drive the
dreaming brain. By this we mean that the cortex of the dream-
ing brain is compelled to process internal signals arising from
the pons and amygdala, as was originally suggested by the ac-
tivation synthesis hypothesis. This epilepsy analogy is also co-
gent because the internal signals of REM sleep are spike and
wave complexes arising in the pons and amygdala (Elazar &
Hobson 1985). The limbic lobe may then direct the forebrain
to construct dreams in a manner similar to that by which it
creates the dreamy states of temporal lobe epilepsy (see Ep-
stein 1995). Indeed, a recent study has shown more unpleas-
ant and higher intensity emotions in the dreams of epileptics
as compared to normals (Gruen et al. 1997).
Hobson et al.: Dreaming and the brain
Figure 15. REM sleep behavior disorder: Brainstem inhibition
of motor output is dissociated from other brain systems during
REM sleep, moving toward waking values of the “I” parameter
and leading to disinhibited motor output.
Figure 14. Hypnopompic hallucinosis: Forebrain (F) and brain-
stem (B) regions occupy different locations in the state space, with
the brainstem initiating internal inputs while the forebrain con-
tinues to process external stimuli.
Figure 13. Hallucinosis: Internal stimuli shift the brain/mind
forward along the “I” axis in AIM state space, with both internal
and external inputs high. This condition may prevail during hyp-
nagogic hallucinosis.
REM sleep behavior disorder: A particularly dramatic ex-
ample of sensorimotor dissociation is seen in the REM
sleep behavior disorder, in which the normal inhibition of
motor output during REM fails (Mahowald & Schenck
1999; Schenck & Mahowald 1996; Schenck et al. 1993).
Motor behaviors normally seen only in waking now arise
completely involuntarily and automatically during REM,
and patients physically act out their dreams (Mahowald et
al. 1998). The historically oriented reader will recognize the
similarity between this disorder and the dissociative phe-
nomena that interested Charcot, Janet, and Freud.
During REM sleep, the motor cortex activation produces
outputs similar to those seen in waking, but in response to
exclusively internal inputs. Since the inhibition of spinal
motorneurons usually occurs in concert with motor cortex
activation, our single “I” parameter normally reflects the
net inhibition of motor output. But in this case (as in the
case of lucid dreaming) we represent this regional dissoci-
ation by a fragmenting of the AIM icon. In this case, the
lower back quarter of the icon, representing brainstem out-
put systems, has moved back in the state space toward a
waking level of output (Fig. 15). It is this dissociation which
produces the REM sleep behavior disorder.
4.2.4. Modulation. If aminergic modulatory power is weak-
ened, as it is in narcolepsy (Mamelak 1991) and depression
(Berger & Riemann 1993), and if cholinergic modulatory
power is enhanced as it also appears to be in these two con-
ditions (Berger & Riemann 1993; Mamelak 1991), then the
value of M will decline. As a consequence, the ability of sub-
jects to maintain alertness may be compromised producing
excessive daytime sleepiness. This would lead to a minor
shift in the normal “alert” position in state space (Fig. 16A,
“Narcoleptic Wake”). Moreover, REM sleep may be en-
tered more rapidly or even directly from waking as in nar-
colepsy (Mitler et al. 1979). This shift in baseline values of
M may also produce shortened REM latency (as in some
forms of depression) or difficulty awakening fully from
REM (as in narcolepsy).
These transitional abnormalities represent some of the
clearest demonstrations of conscious state dissociation in
sleep disorders medicine but they also instruct us about the
normal phenomena, which they exaggerate. For example,
narcoleptic subjects (Kayed 1995; Roth 1978) may halluci-
nate at sleep onset (Fig. 16A, striped arrow from Wake to
NREM) as they move down and forward in the state space
(more cholinergic modulation and hence more internal in-
puts) prior to sleep onset and its associated decrease in ac-
tivation. This can be followed by normal entry into NREM
sleep (striped arrow) or immediate entry into REM sleep
without passing through NREM (gray arrow from wake to
At the other end of the night, an inability to move, termed
sleep paralysis (Mignot & Nishino 1999), which sometimes
compounds the terror of hypnopompic hallucinations, rep-
resents a carry-over of the inhibition of spinal motorneurons
into waking. This dissociation during narcoleptic awakening
can be represented as a dissociation of brainstem motor ac-
tivity along the “I” dimension secondary to a shift in “M”
(Fig. 16B) as AIM moves toward the waking corner of the
Hobson et al.: Dreaming and the brain
Figure 16A. Sleep onset in narcolepsy: the brain shifts down and
forward in the AIM space prior to sleep onset, thereby inducing
sleep onset hallucinations and direct entry into REM sleep at
sleep onset.
Figure 16B. Sleep paralysis in narcolepsy: Enhanced aminergic
demodulation in narcolepsy increases inhibition of motor outputs,
leading to dissociation of brainstem functions and continued mo-
tor inhibition after waking.
state space. This is the inverse of the dissociation seen in
REM sleep behavior disorder (Fig. 15). The sleep abnor-
malities of narcolepsy, as well as those of depression, are re-
lieved by drugs (e.g., tricyclic antidepressents and SSRIs)
which enhance aminergic efficacy and suppress the cholin-
ergic system (Gaillard et al. 1994; Nishino & Mignot 1997).
Other drugs that influence the M parameter produce “al-
tered states of consciousness.” Thus drugs which, like LSD,
interfere with serotonergic neuromodulation (Aghajanian
1994), create dreamlike distortions of imagery and inhibit ex-
ecutive prefrontal cortical functions during waking, while an-
ticholinergics (e.g., scopolamine) produce a delirious waking
state with dream-like hallucinosis, disorientation, anxiety, and
confabulation (Perry & Perry 1995). As seen in Fig. 17, scopo-
lamine pushes AIM above the normal state space, pharmaco-
logically reducing the levels of cholinergic neuromodulation
below any normal physiological levels. At the same time, AIM
splits as both external and internal inputs are activated.
4.2.5. Dissociations. In most of the cases described above,
we have hypothesized that dissociation results from a frag-
mentation of normally unified neuromodulatory states. In
short, the forebrain, midbrain, and brainstem fail to occupy
a single position in the AIM state space. Instead, there is a
split along the Activation or Input axis, with different brain
regions occupying different positions in AIM space. Insight
into how these dissociations might arise comes from the ex-
ample of delirium associated with alcohol withdrawal.
Chronic alcohol usage blocks REM and upon withdrawal
there is a REM rebound, marked by increased amounts and
intensity of REM sleep (Pokorny 1978). It is during this pe-
riod of REM rebound that delirium occurs. Presumably,
the brain reacts dynamically to the alcohol-induced REM
deprivation with an increased pressure towards REM sleep.
We imagine this as pressure to move the brain lower in the
AIM state space, towards lower aminergic and higher cho-
linergic neuromodulation. But while this pressure is ex-
erted by the brain, the alcohol blocks the actual movement
through the state space (Fig. 18).
When alcohol is withdrawn, the REM pressure forces
AIM down in the state space causing increased REM sleep,
but also causing hallucinations and delirium during waking
(Fig. 18B). These symptoms of psychosis are caused by the
release of brain systems which are normally inhibited ex-
cept in REM sleep. In this case, it is an abnormal shift
downward along the “M” axis of the state space which pro-
duces the splitting of AIM and causes its dissociation along
the “I” axis. The net result is to move the brain-mind close
to a position of REM sleep in waking.
4.3. Discrete conscious states and the continuous
state space model
It is common, when discussing consciousness, to speak of
“states” of consciousness. In doing so, it is often assumed
that these are discrete brain-mind states with clearly defin-
able boundaries; it is also assumed that at any given mo-
Hobson et al.: Dreaming and the brain
Figure 17. Scopolamine inhibition of REM sleep: Cholinergic
inhibitors force the brain-mind to abnormally high ratios of amin-
ergic to cholinergic n