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The process of awakening: A PET study of regional brain activity patterns mediating the re-establishment of alertness and consciousness


Abstract and Figures

Awakening from sleep entails rapid re-establishment of consciousness followed by the relatively slow (20-30 min later) re-establishment of alertness--a temporal dissociation that facilitates specification of the physiological underpinnings of each of these facets of the awakening process. H(2)(15)O PET was used to assess changes in regional cerebral blood flow (rCBF) upon awakening from stage 2 sleep. Cerebral blood flow (CBF) was most rapidly re-established in centrencephalic regions (e.g. brainstem and thalamus), suggesting that the reactivation of these regions underlies the re-establishment of conscious awareness. Across the ensuing 15 min of wakefulness, further increases in CBF were evident primarily in anterior cortical regions, suggesting that the dissipation of sleep inertia effects (post-awakening performance and alertness deficits) is effected by reactivation of these regions. Concomitant shifts in correlation patterns of regional brain activity across the post-awakening period [in particular, a waning negative correlation between prefrontal cortex and mesencephalic reticular formation (RF) activity, and a waxing positive correlation between prefrontal cortex and ventromedial caudate nucleus (CAUD) activity] suggest that the post-awakening reversal of sleep inertia effects may be mediated by more than mere reactivation--it may also involve the functional reorganization of brain activity. Conversely, stable post-awakening correlations--such as those found between the anterior cingulate cortex (ACC) and most other brain regions--may denote the pattern of functional connectivity that underlies consciousness itself.
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The process of awakening: a PET study of regional
brain activity patterns mediating the
re-establishment of alertness and consciousness
Thomas J. Balkin,
Allen R. Braun,
Nancy J. Wesensten,
Keith Jeffries,
Mary Varga,
Paul Baldwin,
Gregory Belenky
and Peter Herscovitch
Department of Behavioral Biology, Walter Reed Army
Institute of Research, Washington, DC,
Language Section,
Voice Speech and Language Branch, National Institute on
Deafness and Communication Disorders and
PET Imaging
Section, National Institutes of Health, Bethesda, Maryland,
Correspondence to: T. J. Balkin, Department of Behavioral
Biology, Walter Reed Army Institute of Research,
Washington, DC 20307-5100, USA
Awakening from sleep entails rapid re-establishment of
consciousness followed by the relatively slow (20±30 min
later) re-establishment of alertnessÐa temporal dis-
sociation that facilitates speci®cation of the physio-
logical underpinnings of each of these facets of the
awakening process. H
O PET was used to assess
changes in regional cerebral blood ¯ow (rCBF) upon
awakening from stage 2 sleep. Cerebral blood ¯ow
(CBF) was most rapidly re-established in centrencepha-
lic regions (e.g. brainstem and thalamus), suggesting
that the reactivation of these regions underlies the re-
establishment of conscious awareness. Across the ensu-
ing 15 min of wakefulness, further increases in CBF
were evident primarily in anterior cortical regions, sug-
gesting that the dissipation of sleep inertia effects (post-
awakening performance and alertness de®cits) is
effected by reactivation of these regions. Concomitant
shifts in correlation patterns of regional brain activity
across the post-awakening period [in particular, a wan-
ing negative correlation between prefrontal cortex and
mesencephalic reticular formation (RF) activity, and a
waxing positive correlation between prefrontal cortex
and ventromedial caudate nucleus (CAUD) activity]
suggest that the post-awakening reversal of sleep inertia
effects may be mediated by more than mere reactiva-
tionÐit may also involve the functional reorganization
of brain activity. Conversely, stable post-awakening cor-
relationsÐsuch as those found between the anterior cin-
gulate cortex (ACC) and most other brain regionsÐ
may denote the pattern of functional connectivity that
underlies consciousness itself.
Keywords: alertness; consciousness; sleep inertia; rCBF; PET
Abbreviations: ACC = anterior cingulate cortex; CAUD = ventromedial caudate nucleus; CBF = cerebral blood ¯ow;
rCBF = regional cerebral blood ¯ow; RF = mesencephalic reticular formation
The neurophysiological basis of several aspects of human
consciousness has recently been explored using functional
brain imaging techniques. For example, insights into the
regional mediation of brain processes underlying perceptual
awareness have resulted from studies of hallucinations
(Ffytche et al., 1998), subjective perceptual shifts when
dissimilar images are concurrently presented to the two eyes
(Lumer et al., 1998) and implicit versus explicit awareness of
visual stimuli (e.g. by studying patients who exhibit `blind-
sight'; Sahraie et al., 1997). The strategy employed in these
functional brain imaging studies is straightforward; scans
obtained during normal, conscious functioning are contrasted
with those obtained during an abnormal or otherwise altered
state (such as a shift in the level of perceptual awareness).
Thus, functional brain imaging techniques have been used to
highlight the brain regional activation/deactivation patterns
that mediate even the most subtle nuances of human
conscious experience.
In the present study, a comparable strategy was used to
determine the pattern of brain activity that underlies
alertnessÐthe aspect of waking conscious experience that
re¯ects extant sleep/wake tendencyÐin an attempt to distin-
Published by Oxford University Press 2002
Brain (2002), 125, 2308±2319
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guish alertness from consciousness [in its broadest sense, the
amalgamation of the mental processes that distinguish
wakefulness from sleep, i.e. `the ability to perceive, interact
and communicate with the environment and others in an
integrated manner' (Zeman, 2001)].
Prior functional brain imaging studies of sleep deprivation
(e.g. Thomas et al., 2000) suggest that alertness varies
primarily as a function of brain activation levels in the
thalamus and prefrontal corticesÐwith reduced activity in
these regions foreshadowing the more robust pattern of
deactivation that characterizes sleep itself (e.g. Maquet et al.,
1996; Braun et al., 1997).
However, more precise speci®cation of the neurophysio-
logical substrate of consciousnessÐand an enhanced ability
to differentiate those processes mediating consciousness from
those mediating alertness±may be gleaned from functional
brain imaging studies in which the awakening processÐi.e.
the transition from sleep to full alertnessÐis examined. This
is because the ®rst several minutes of wakefulness constitute
a state of reduced alertness like that produced by sleep
deprivation, except that there is an initial mismatch between
alertness level and underlying sleep debt. This mismatch
resolves over the ®rst ~20 min of continuous wakefulnessÐa
time frame that allows characterization of any underlying
changes in regional brain activity using H
O PET methods.
Post-awakening de®cits in alertness (called `sleep inertia
effects'; Lubin et al., 1976) include decrements in psycho-
motor performance and cognitive performance, marked
hypovigilance (Tassi and Muzet, 2000) and sometimes
bewilderment (Kleitman, 1963). Prior behavioural studies
of sleep inertia indicate that the greatest de®cits occur shortly
after awakening, and that post-awakening improvements
accrue in a decelerating, asymptotic manner (Jewett et al.,
These post-awakening de®cits are qualitatively similar to
those resulting from sleep deprivation (Balkin and Badia,
1988)Ðdespite the fact that actual sleep debt should be
lowest immediately upon awakening (since sleep debt should
accumulate with every minute of wakefulness). Therefore, it
is likely that sleep inertia effects re¯ect the intrusion of
residual (and waning) sleep maintenance mechanisms into the
waking state.
The present study is the ®rst to characterize changes in
regional cerebral blood ¯ow (rCBF) during the post-awaken-
ing period. We perform contrasts that capitalize on the
naturally occurring differential time courses for the re-
establishment of consciousness versus alertness, and also
examine functional connectivity in an effort to specify the
patterns of regional brain activity that underlie each.
Material and methods
Subjects were 27 healthy male volunteers (age 21±32 years).
On the basis of medical history, physical examination and
baseline laboratory evaluation, all subjects were free of
neurological and psychiatric illness. Subjects with a history of
sleep disorders or who had used prescription medications
within 30 days preceding the study were excluded. The study
was conducted using a protocol approved by the NIH NINDS
review board and the U.S. Army Surgeon General's Human
Subjects Review Board. Informed consent was obtained from
all subjects in accordance with the Declaration of Helsinki
after all potential risks, discomforts, and hazards had been
Pre-scan sleep schedule
To help ensure that sleep would be obtained in the scanner, all
subjects underwent a 3-day partial sleep deprivation proced-
ure prior to scanning (for details, see Braun et al., 1997).
Ambulatory polysomnographic recorders (Oxford Medilog
9000-II; Oxford Instruments Medical, Hawthorne, NY, USA)
were used to measure and record EEG from C
and C
(Jasper, 1958), submental EMG and electro-oculogram
(EOG) (from the outer canthus of each eye) to verify
wakefulness during the sleep restriction periods. During
scheduled sleep periods, signals from the ambulatory record-
ers were routed through a Nihon Kohden electroencephalo-
graph (Model EEG-4317B; Nihan Kohden America Inc,
Foothill Ranch, CA, USA) for visual monitoring of the
subjects' sleep.
Scanning methods
Scans were performed on a Scanditronix PC2048-15B
tomograph (Uppsala, Sweden), which has an axial and in-
plane resolution of 6.5 mm. Fifteen planes, offset by 6.5 mm
(centre to centre), were acquired simultaneously parallel to
the cantho-meatal line. Prior to placement in the scanner,
indwelling arterial and venous catheters were inserted into the
radial artery and antecubital vein of subjects' right and left
forearms, and a new set of electrodes (EEG, EOG, EMG) for
polysomnographic monitoring in the scanner (using a Grass
Model 8±10D polygraph; Grass Telefactor, West Warwick,
Rhode Island, USA) were attached to the scalp and face at the
same sites described above. Subjects' eyes were patched and
head motion was restricted for the duration of the study with
an individually ®tted thermoplastic face mask that was
af®xed to the frame of the scanner bed. A 30 mCi bolus of
O was injected intravenously and scans were initiated
automatically when the radioactive count rate in the brain
(automatically detected by scanner) reached a threshold value
of 50,000 per s (~20 s after injection) and were continued for
4 min. Sixteen scan frames were collected (twelve 10 s scans
followed by four 30 s scans). Arterial blood was sampled
automatically throughout each scan, and arterial time±activ-
ity data and blood gas measures were used with the scans to
produce quantitative pCO
-corrected rCBF images (see
Braun et al., 1997). Emission data were corrected for
Process of awakening 2309
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attenuation by means of a transmission scan obtained at the
same levels.
As reported previously (Braun et al., 1997), scans were
acquired prior to sleep and during sleep stages 2, 3±4 and
rapid eye movement (REM) (Rechtschaffen and Kales,
As the focus of the present report, scans were also
performed during the post-sleep period as follows. After
~3±5 h of sleep in the scanner, subjects were awakened from
stage 2 sleep by an investigator who entered the scanner room
and spoke the subject's ®rst name. When the subject
responded, he was instructed to remain awake and motionless
until the scanning procedures were completed. There was no
further communication until all scans were completed and
subjects were removed from the scanner. H
O was injected
intravenously following 5 min of continuous, polysomno-
graphically veri®ed wakefulness, and again after 20 min of
veri®ed, continuous wakefulness (i.e. 15 min later).
PET scans were registered, normalized to a common
stereotaxic space (Talairach and Tournoux, 1988) and
smoothed using a Gaussian kernel of 20 3 20 3 12 mm in
the x, y and z axes. Absolute pCO
-corrected global ¯ow rates
were calculated for each subject by averaging grey matter
pixel values. Global ¯ow rates were compared across
conditions. Global cerebral blood ¯ow (CBF) was also used
to proportionally normalize each image on a pixel by pixel
basis, and normalized rCBF rates were compared in the
pairwise contrasts. As reported previously (Braun et al.,
1997), if signi®cant differences in global ¯ow rates were
detected, results of the proportionally normalized contrasts
are reported, but interpreted in context. Thus, if increases in
absolute CBF rates only were observed in comparing scans
from two time points, only those normalized comparisons
revealing regional increases were considered indices of real
change. Decreases in normalized ¯ow rates were interpreted
as identifying brain regions in which absolute values deviated
the leastÐi.e. were associated with absolute invariance or
possibly with minimal, non-signi®cant increases in absolute
rCBF. On the other hand, when signi®cant differences in
absolute pCO
-corrected global ¯ow were not detected,
normalized comparisons are simply reported as indices of
relative change.
Differences between rCBF levels at 5 min post-awakening
versus 20 min post-awakening, during stage 2 sleep versus
5 min post-awakening and during stage 2 sleep versus 20 min
post-awakening were analysed using statistical parametric
mapping (SPM) software (MRC Cyclotron Unit, London,
UK). Of the 27 subjects from whom post-awakening scans
were acquired: 13 had post-awakening scans at both 5 and
20 min; 11 had scans during both stage 2 sleep and at 5 min
post-awakening; and 11 had scans during both stage 2 sleep
and at 20 min post-awakening. The stage 2 sleep-20 min post-
awakening contrast (highlighting the differences in regional
activation that differentiate alert wakefulness from sleep) and
the 5±20 min post-awakening contrast (highlighting the
differences in regional activation that differentiate sleep
inertia from normal, alert wakefulness) were then compared.
Because the stage 2 sleep-20 min post-awakening contrast
revealed that all post-awakening changes in CBF were
increases, results from that contrast were used to mask
those of the 5 min/20 min post-awakening contrast on a voxel
by voxel basis, so that local minima or maxima could be
interpreted in that context.
Correlation analyses were also performed to evaluate
regional interconnectivity patterns at 5 and 20 min post-
awakening. Rather than perform large-scale correlations
using an extended set of brain regions, connectivity patterns
were characterized in three potentially important regions.
These were selected on the basis of their previously
demonstrated involvement in both sleep stage transitions
and sleep/wake transitions, and grounded in ®ndings from the
present study:
(i) The mesencephalic reticular formation (RF) [selected
because the earliest studies point to this region as an
important mediator of arousal (Moruzzi and Magoun, 1949)].
(ii) The ventromedial caudate nucleus (CAUD) [a stage REM
sleep-speci®c disparity between activation levels in the
caudate nucleus and the prefrontal regionsÐwith which
neuronal connections are extensiveÐsuggests a key role for
this region in sleep state mediation (Braun et al., 1997)].
(iii) The anterior cingulate cortex (ACC) [selected because of
its role in the mediation of attention (e.g. Davis et al., 2000)
and its especially robust sleep stage-dependent changes in
activity (Braun et al., 1997)].
Selection of regional coordinates was based on local Z-
score minima or maxima from the present study when these
exceeded threshold (i.e. in the RF and CAUD). When
threshold was not exceeded (i.e. in the ACC), coordinates
selection was based on the results from comparable sleep
stage contrasts reported previously (Braun et al., 1997).
The PET images processed using SPM software were also
used in the correlation analyses. Normalized rCBF values for
voxels throughout these images were correlated across the
cohort of subjects, with values derived from the seed voxels
of interest at 5 and 20 min post-awakening, utilizing software
written in MATLAB (Horwitz et al., 1998). This routine
produces a normalized output image with Pearson product±
moment correlation coef®cients assigned to each pixel in the
image. Coef®cients were transformed to standard scores and
thresholded at Z > 2.0 in absolute value.
Changes in CBF
Global changes
The awakening process was characterized by a global
increase in absolute CBF levels. During stage 2 sleep (the
sleep stage from which all awakenings were initiated), the
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Table 1 Stage 2 sleep versus 5 min and 20 min post-awakening
Stage 2 sleep/5 min post-awakening Stage 2 sleep/20 min post-awakening
Region of interest Brodmann area Z-score xyz Z-score xyz
Heteromodal association
Orbital operculum 47 2.47 26 28 ±12* 4.11 26 28 ±12
Dorsal operculum 45 ± ± ± ± 3.15 38 26 20
Lateral orbital cortex 10 ± ± ± ± 3.92 24 42 ±8
Dorsolateral prefrontal cortex 46 ± ± ± ± 3.18 36 34 16
Medial prefrontal cortex 9 ± ± ± ± 3.00 ±8 48 16
Anterior cingulate 24/32 2.69 ±8 28 16 3.31 ±6 32 20
Anterior insula ± ± ± ± 3.15 30 28 0
Midline 2.59 ±2 ±76 ±20 ± ± ± ±
Midbrain reticular formation 3.03 ±10 ±24 0 2.00 8 ±14 0
Dorsomedial 3.19 ±12 ±22 8 2.51 ±4 ±22 8
Basal ganglia
Caudate 3.65 12 6 8 3.31 ±14 22 8
Basal forebrain
Caudal orbital cortex 25 ± ± ± ± 3.34 18 26 ±12
Regions in which pCO
-corrected rCBF levels at 5 and 20 min post-awakening differ from stage 2 sleep are tabulated along with Z-scores (representing maxima and associated
Talairach coordinates). For tabulation, increases or decreases in CBF exceeding threshold in a single hemisphere were considered truly lateralized only if contralateral values failed to
re¯ect a trend (de®ned as Z > 1.64 in absolute value) in the same direction. *No corresponding increases in contralateral hemisphere.
Process of awakening 2311
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global CBF rate was 39.8 6 2.9 ml/100 mg/min. At 5 min
post-awakening, the global CBF rate had increased signi®-
cantly to 45.5 6 2.5 ml/100 mg/min, with no substantive
further increase at 20 min post-awakening when the global
CBF rate was 45.8 6 2.0 ml/100 mg/min.
Changes in rCBF from stage 2 sleep to 5 min
Awakening-mediated increases in CBF were not homo-
geneous; pairwise contrasts revealed that initial post-awaken-
ing increases in rCBF occurred primarily in centrencephalic
regions: brainstem, thalamus and basal ganglia (see Table 1
and Fig. 1A), whereas few signi®cant changes were evident in
the anterior cortical areas. Since sleep inertia effects are
typically manifest at 5 min post-awakening, this pattern of
regional differences reveals the changes in brain activity
patterns that characterize stage 2 sleep versus wakefulness
with impaired alertness.
Changes in rCBF from stage 2 sleep to 20 min
Pairwise contrasts revealed that regional increases tended to
occur in anterior cortical, paralimbic±limbic and subcortical
regions (see Table 1 and Fig. 1B), whereas no signi®cant
changes were evident in the posterior cortical areas. Since the
awakening process is known to be relatively complete after
20 min of continuous wakefulness (i.e. sleep inertia effects
have typically dissipated to a considerable extent by this
time), the regional differences revealed by these contrasts
constitute the changes in brain activity patterns that distin-
guish stage 2 sleep from normal wakefulness.
Changes in rCBF from 5 min post-awakening to
20 min post-awakening
Although the awakening process was associated with a global
increase in CBF, there were no signi®cant changes in global
CBF over the ®rst 20 min of wakefulness. Therefore, both
increases and decreases in normalized rCBF values are
reported as indices of relative change across the ®rst 20 min
of wakefulness. These specify the pattern of rCBF changes
that underlie dissipation of sleep inertia effectsÐi.e. the
ascent from consciousness with impaired alertness to con-
sciousness with relatively normal alertnessÐand are depicted
in Fig. 2.
Those regions in which CBF increased across the 5±20 min
post-awakening period were primarily heteromodal neocor-
tical areas, i.e. orbital and dorsolateral prefrontal cortices,
frontal opercular cortex, middle temporal gyrus and superior
temporal sulcus. In addition, signi®cant increases in rCBF
from the 5th to the 20th minute were evident in the anterior
Fig. 1 Brain map depicting increases in rCBF between stage 2 sleep and 5 min post-awakening (top row) and between stage 2 sleep and
20 min post-awakening (bottom row). The SPM {z} map illustrating these differences is displayed on a standardized MRI scan, which
was transformed linearly into the same stereotaxic (Talairach) space as the SPM {z} data. Planes of section relative to the anterior
commissural±posterior commissural line are indicated (z-axis coordinates in mm). Values are Z-scores representing the signi®cance level
of changes in proportionally normalized rCBF in each voxel when scans acquired at 5 or 20 min post-awakening are contrasted with those
acquired during stage 2 sleep as baseline. The range of scores is coded in the accompanying colour table, with red designating Z-scores of
>+4.0. Locations of local minima and maxima for Z-scores are summarized in Tables 1 and 2.
2312 T. J. Balkin et al.
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insula and the caudal orbital region of the basal forebrain
(both of which have extensive interconnections with
prefrontal cortices) and in portions of the auditory cortices.
Unlike the stage 2 sleep-20 min post-awakening contrast,
no increases were evident in brainstem, basal ganglia or
thalamus across the 5±20 min post-awakening period. This
indicated that reactivation of these brain regions was
relatively complete by 5 min post-awakening. In fact, as
indicated by negative Z-scores in Table 2, relative decreases
were evident in several of these regions during the post-
awakening period. Changes in relative rCBF across the ®rst
20 min of wakefulness are listed in Table 2 and illustrated in
Fig. 2.
Changes in functional connectivity patterns
Mesencephalic reticular formation (RF)
At both 5 and 20 min post-awakening, activity in the RF (x =
±6, y = ±30, z = ±4; coordinates specifying the maximal
difference between 5 and 20 min; Table 2) was correlated
with activity in a number of cortical and subcortical regions.
Positive correlations were evident with the cerebellar
hemispheres, putamen, thalamus, auditory cortices, ACC,
hippocampus and the parahippocampal gyrus. Negative
correlations were evident with pre- and post-central gyri,
and ventral visual cortices.
In contrast, activity levels in the RF and prefrontal
corticesÐincluding the medial, dorsolateral, lateral orbital
and opercular corticesÐwere negatively correlated at 5 min
post-awakening, but as listed in Table 3 and depicted in
Fig. 3B, these correlations were no longer signi®cant by
20 min post-awakening. This pattern was also evident in
middle temporal gyrus, auditory cortices and insula, but was
especially striking in the operculum, where the correlation
with RF activity was particularly robust at 5 min
post-awakening. This constituted the strongest correlation
between the RF and all other brain regions at this earlier
post-awakening time point and the site of maximal change
between 5 and 20 min (see Table 2).
The dynamic range of rCBF rates did not vary signi®cantly
from 5 to 20 min post-awakening [F(1,19) = 1.33, P = 0.53].
This suggests that the observed differences in correlation
patterns at these two times truly re¯ect different patterns of
functional connectivity rather than relative differences in the
stability of the rCBF rate across the two time points.
At both 5 and 20 min post-awakening, activity in the CAUD
(x = ±14, y =2,z = ±8; coordinates specifying the maximal
difference between 5 and 20 min; Table 1) was signi®cantly
correlated with activity in several cortical and subcortical
brain regions. Positive correlations were evident with activity
levels in midbrain tegmentum, other portions of the basal
ganglia (contralateral caudate, globus pallidus bilaterally,
ipsilateral putamen), ventral precentral gyri, anterior auditory
cortices, portions of the middle temporal gyri bilaterally,
caudal orbital cortices, temporal pole, ACC, hippocampus
and amygdala. Negative correlations with CAUD activity
levels at both 5 and 20 min post-awakening were evident in
the dorsal precentral gyrus, post-central gyri, posterior
auditory association cortices and ventral visual cortices.
In addition, a positive correlation between activity in the
caudate and the inferior insula was evident at 5 min, but not at
20 min post-awakeningÐalthough positive correlations
between the caudate and both the anterior and posterior
insula subsequently emerged at 20 min.
In contrast, activity in the caudate was not correlated with
activity in the majority of prefrontal cortices at 5 min post-
awakening (the single exception being a positive correlation
between CBF rates in the caudate and medial prefrontal
cortexÐwhich was evident at both 5 min and 20 min post-
awakening), nor with activity in the thalamus. Nevertheless,
by 20 min, activity in the caudate was positively correlated
Fig. 2 Brain map depicting changes in rCBF between 5 and 20 min after awakening from stage 2 sleep. Data are processed and displayed
as for Fig. 1. Values are Z-scores representing the signi®cance level of changes in proportionally normalized rCBF in each voxel when
scans acquired at 20 min are contrasted with those acquired at 5 min as baseline. Positive scores represent increases in relative blood ¯ow
from 5 to 20 min; negative scores represent concomitant, relative decreases. The range of scores is coded in the accompanying colour
table, with red designating Z-scores of >+4.0 and purple designating Z-scores of <±4.0. Locations of local minima and maxima for Z-
scores are summarized in Table 3.
Process of awakening 2313
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with activity in a wide array of prefrontal regions including
orbital, medial and dorsolateral cortices, and opercular
cortices (see Table 3, Fig. 3A); as well as in the functionally
related dorsal thalamus.
As in the RF, comparison of the variances in rCBF rates for
the CAUD revealed no signi®cant differences in dynamic
range at 5 versus 20 min post-awakening [F(1,19) = 1.28,
P = 0.59], again reinforcing the assertion that differences in
correlations across these times re¯ect meaningful differences
in the pattern of functional connectivity.
Anterior cingulate cortex (ACC)
Since ACC activity did not vary signi®cantly over the post-
awakening period, selection of coordinates for this region was
based on the peak difference evident during a prototypical
sleep stage contrast [x = ±6, y = 40, z =8,Z = 3.42, stage 3±4
sleep versus REM, as reported previously by Braun et al.
Positive correlations were evident at both 5 and 20 min
between activity levels in the ACC and the midbrain
tegmentum, caudate, putamen, thalamus, medial orbital
cortex, inferior medial and dorsolateral prefrontal cortices,
ventral operculum, anterior auditory association cortices,
caudal orbital cortex, temporal pole, anterior and posterior
insula, other portions of the ACC, hippocampus and
amygdala. Likewise, the negative correlations with ACC
that were evident at 5 min post-awakening persisted at 20 min
post-awakening, including those with superior portions of the
medial prefrontal and dorsolateral prefrontal cortices, dorsal
operculum, pre- and post-central gyri, and visual cortices.
Therefore, unlike the patterns of correlations re¯ecting the
functional connections of the reticular formation and caudate,
correlations between the ACC and other brain regions
Table 2 Changes in rCBF from the 5th to the 20th min after awakening
Region of interest Brodmann
Z-score xyz
Heteromodal association
Orbital operculum 47 3.34 ±18 24 ±16
Dorsal operculum 44/ 45 5.02 44 12 8
Dorsolateral prefrontal cortex 46 3.70 38 36 16
Lateral orbital cortex 11 2.75 ±24 38 ±12
Middle temporal gyrus /STS 21 3.50 56 ±54 12
Unimodal sensory
Posterior superior temporal gyrus 22 3.38 ±54 ±34 16
Fusiform gyrus 19, 37 ±3.72 ±28 ±60 ±8
Lateral occipital cortex 19, 18 ±3.36 ±36 ±86 0
Anterior insula 3.98 40 10 8
Hippocampus ±4.16 ±18 ±30 0*
Midline ±5.04 ±18 ±70 ±16
Midbrain reticular formation ±3.48 ±6 ±30 ±4
Pulvinar ±3.88 ±18 ±28 4*
Basal ganglia
Ventromedial caudate ±2.84 ±14 2 ±8
Basal forebrain
Caudal orbital cortex 25 3.22 ±14 26 ±16
Regions in which normalized rCBF levels differ from the 5th to the 20th min post-awakening are tabulated along with Z-scores,
representing local minima or maxima and associated Talairach coordinates. Positive Z-scores designate increases and negative Z-scores
designate decreases in relative rCBF. For tabulation, increases or decreases exceeding threshold in a single hemisphere were considered
truly lateralized only if contralateral values failed to re¯ect a trend (de®ned as Z > 1.64 in absolute value) in the same direction. *No
corresponding changes in contralateral hemisphere.
2314 T. J. Balkin et al.
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(including prefrontal and opercular cortices) remained rela-
tively stable across the post-awakening period (see Table 3
and Fig. 3C).
Fig. 4 includes brain maps illustrating the functional
connectivity patterns of some frontal cortical regions with the
CAUD, RF and ACC at both 5 and 20 min post-awakening.
Unique changes in the pattern of regional brain activity across
the ®rst 20 min of wakefulness and concomitant changes in
patterns of regional interconnectivity (re¯ected in the correl-
ation analyses) were investigated in an effort to differentiate
the neural substrate of consciousness (the post-awakening
re-establishment of awareness of self and the environment)
from that of alertness (as re¯ected by the post-awakening
dissipation of sleep inertia-related hypovigilance). Since
consciousness and alertness are re-established at differential
rates following awakening from sleep, PET scanning at two
time points shortly following awakening was used to extricate
the physiological underpinnings of these two aspects of the
awakening process.
First, with respect to alertness, the ®nding that global CBF
rates were constant across the ®rst 20 min of wakefulness
indicates that post-awakening improvement does not accrue
simply as a function of generally increasing levels of brain
activation. In this respect, these ®ndings differ from those of
prior functional brain imaging studies during sleep depriv-
ation, from which it could be surmised that sleepiness is
associated with global deactivation (e.g. Thomas et al., 2000).
Rather than increases in global activity, focal differencesÐ
re¯ecting reactivation of critical brain regions and/or re-
establishment of the functional circuitry that typi®es normal
waking brain functionÐmust account for post-awakening
increases in alertness. In the present study (and partially
consistent with the ®ndings during sleep deprivation reported
by Thomas et al., 2000), the most notable regional changes
(in terms of spatial extent and peak differences in activity)
across the post-awakening period were evident in the
prefrontal association cortices. However, unlike prior sleep
deprivation studies, which showed concomitant reductions in
thalamic and prefrontal cortical activity, activity levels in
these two regions were dissociated in the present study:
Reactivation was complete in the thalamus at 5 min post-
Table 3 Correlations between normalized rCBF values in selected regions
5 min post-awakening 20 min post-awakening
Region of interest Z-score xyz Z-score xyz
Medial orbital ±2.66 ±20 38 ±12* 2.17 ±6 36 ±12*
Medial prefrontal ±3.18 ±18 50 20* ± ± ± ±
Dorsolateral prefrontal ±4.00 ±34 42 12*** ± ± ± ±
Ventral opercular ±3.06 ±42 20 4* ± ± ± ±
Dorsal opercular ±4.48 ±48 8 20**** ± ± ± ±
Medial orbital ± ± ± ± 4.67 ±16 42 ±8***
Medial prefrontal ± ± ± ± 3.93 ±22 44 4*
Dorsolateral prefrontal ± ± ± ± 3.29 ±38 40 12*
Ventral opercular ± ± ± ± 3.23 32 22 ±4**
Dorsal opercular ± ± ± ± 2.42 44 22 16*
Medial orbital 3.23 ±8 40 ±8 4.00 ±12 40 ±8
Medial prefrontal 3.93 ±8 46 16 2.52 ±10 46 16
Dorsolateral prefrontal ±2.34 ±34 28 24 ±2.13 ±32 24 28
Ventral opercular 2.25 38 24 0 3.66 40 24 0
Dorsal opercular ±2.43 42 2 28 ±2.62 36 10 28
Correlations of normalized rCBF values in RF, CAUD and ACC with rCBF values in frontal cortical regions at 5 and 20 min post-
awakening. Z-transformed correlation coef®cients, designating local maxima or minima, are tabulated along with associated Talaraich
coordinates. Asterisks signify differences between transformed coef®cients, at the indicated coordinates. *DZ >61.64, **DZ >6 2.33,
***DZ >62.57, ****DZ >63.09.
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Fig. 3 Correlations between rCBF rates in (A) CAUD, (B) RF and (C) ACC (coordinates for each region selected as outlined in the text)
and regions within the prefrontal cortex. Values on the x and y axes represent normalized rCBF rates measured at 5 min (left) and 20 min
(right) post-awakening. Each plotted point therefore represents the activation levels from two voxels (one from each of the two speci®ed
brain regions) in a single subject, at a given point in time (5 or 20 min post-awakening). Regression lines are shown for each statistically
signi®cant correlation. (A) Blood ¯ow in CAUD (Talairach x = ±14, y = ±2, z = ±8) and orbitofrontal cortex (x = ±26, y = 42, z = ±8) was
uncorrelated at 5 min, but positively correlated (r = 0.81, Z = 4.7, P < 0.0001) at 20 min post-awakening. (B) Blood ¯ow in the RF (x =
±6, y = ±30, z = ±4) and dorsolateral prefrontal cortex (x = ±34, y = 48, z = 12) was negatively correlated at 5 min (r = ±0.82, Z = 4.8,
P < 0.0001), but uncorrelated by 20 min post-awakening. However, as shown in C, blood ¯ow in the ACC (x = ±6, y = 40, z = ±4) and
orbitofrontal cortex (x = ±12, y = 52, z = ±8) was positively correlated at both 5 min (r = 0.64, Z = 3.1, P < 0.001) and 20 min (r = 0.70,
Z = 3.6, P < 0.0005) post-awakening.
2316 T. J. Balkin et al.
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awakening (a time when sleep inertia effects are typically
manifest) and thus preceded reactivation of prefrontal
cortices. Therefore, the present ®ndings eliminate thalamic
deactivation as a physiologically necessary component of
hypovigilance. Instead, hypovigilance must ultimately be a
function of reduced prefrontal cortical activity.
Consciousness, on the other hand, must be a function of
activity in those regions (or a subset of those regions) in
which reactivation upon awakening is relatively rapid:
brainstem, thalamus, basal ganglia and ACC.
However, just as it is unlikely that sleep can be distin-
guished from wakefulness solely on the basis of the activation
level of individual brain regions, it is unlikely that any
individual brain region mediates either the re-establishment
of consciousness that accompanies awakening or the reversal
of alertness and performance de®cits that occurs during the
post-awakening period. This is because brain regions do not
function independentlyÐthey typically operate as elements
in a series of networks distributed throughout the CNS.
Accordingly, it is likely that the various sleep/wake states and
consciousness itself are emergent consequences of functional
interactions between brain regions.
The correlational ®ndings from the present study are, for
example, consistent with the notion that increasing alertness
Fig. 4 Brain map illustrating correlations between rCBF values in (A) CAUD, (B) RF, (C) ACC and
frontal cortical regions at 5 and 20 min post-awakening. Maps illustrating Z-transformed correlation
coef®cients are displayed on a standardized MRI scan using the methods outlined for Fig. 1. The ranges
of positive and negative Z-scores are coded in the accompanying colour tables. Locations of local minima
and maxima are summarized in Table 2. In (A), +3 mm relative to the anterior commissural±posterior
commissural (AC±PC) line, positive correlations between rCBF in the caudate (Talairach x = ±14, y = ±2,
z = ±8) and lateral prefrontal cortices and operculum are manifest after a delay of 20 min. In (B), +17 mm
relative to the AC±PC line, blood ¯ow in the RF (x = ±6, y = ±30, z = ±4) and medial and dorsolateral
prefrontal cortices was negatively correlated at 5 min and uncorrelated at 20 min post-awakening. In (C),
+1 mm relative to the AC±PC line, blood ¯ow in the ACC (x = ±6, y = 40, z = ±4) was positively
correlated with that in medial and lateral prefrontal and opercular cortices at both 5 and 20 min post-
Process of awakening 2317
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during the post-awakening period is an emergent product of
orchestrated interregional activation patterns, i.e. these
analyses suggest that, in addition to regional reactivation,
the post-awakening process involves functional reorganiza-
tion. In some instances, the reorganization involves re-
establishment of those functional circuits that are purported to
characterize the coherent and orchestrated activity of the
normal, alert brain. Thus, the correlations between caudate,
prefrontal cortex and thalamus (that were not evident until
20 min post-awakening) may signify re-establishment of
functional coherence in the prefrontal corticostriatal thala-
mocortical circuit (Alexander et al., 1986)Ða circuit centred
upon the caudate that, as previously suggested (Braun et al.,
1997), may be functionally uncoupled during sleep.
The correlational analyses also revealed that post-awaken-
ing re-establishment of normal alertness is sometimes
characterized by functional uncoupling of interregional
activity, as suggested by the disappearance at 20 min post-
awakening of the initially signi®cant correlation between
activity levels in the RF and prefrontal cortices.
In contrast, some inter-regional functional relationships
(again, indicated by signi®cantly correlated regional rCBF
levels) were re-established by 5 min post-awakening and
remained unchanged at 20 min post-awakening. This suggests,
by their relative stability across the sleep inertia period, that
these functional relationships may underlie (and perhaps in
some way constitute) consciousness itself. For example, the
widespread and stable functional connectivity of the ACC,
indicated by numerous and stable correlations between activity
levels inthis region and widespread otherbrain regions atboth 5
and 20 min post-awakening, suggests that it may be part of a
functional circuit or network of brain regions in which inter-
connectivity subserves conscious wakefulness.
Lastly, as Revonsuo (2001) notes, some caution in the
interpretation of functional brain imaging studies of con-
sciousness is warranted since the extent to which current
brain imaging techniquesÐincluding the PET H
O tech-
nique used in the present studyÐprovide measurements at the
critical level of physiological organization is unknown.
To summarize, it is suggested that those brain regions (e.g.
the prefrontal cortices) for which activation levels and/or
connectivity patterns change signi®cantly across the ®rst
20 min of wakefulnessÐwhen sleep inertia effects are known
to dissipateÐmost likely mediate alertness. In contrast, those
brain regions for which reactivation is maximal upon
awakening (e.g. thalamus, caudate, brainstem) or in which
interconnectivity patterns remain stable across the ®rst 20 min
of wakefulness (e.g. ACC) are more likely to participate in
the mediation of consciousness itself.
Further studies of greater scope (e.g. with measures that
include multiple levels of physiological organization) and
involving contrasts of additional altered states of conscious-
ness are needed to identify the full complement of regions,
functional circuits and electrophysiological processes that
subserve consciousness and its nuances.
US Department of Defense disclaimer
Human subjects participated in this study after giving their
free and informed consent. Investigators adhered to AR 70±
25 and USAMRDC Reg 70±50 on the use of volunteers in
research. The opinions or assertions contained herein are the
private views of the authors and are not to be construed as
re¯ecting the views of the Department of the Army or the
Department of Defense.
Alexander GE, DeLong MR, Strick PL. Parallel organization of
functionally segregated circuits linking basal ganglia and cortex.
[Review]. Annu Rev Neurosci 1986; 9: 357±81.
Balkin TJ, Badia P. Relationship between sleep inertia and
sleepiness: cumulative effects of four nights of sleep disruption/
restriction on performance following abrupt nocturnal awakenings.
Biol Psychol 1988; 27: 245±58.
Braun AR, Balkin TJ, Wesenten NJ, Carson RE, Varga M, Baldwin
P, et al. Regional cerebral blood ¯ow throughout the sleep-wake
cycle: an H
O PET study. Brain 1997; 120: 1173±97.
Davis KD, Hutchison WD, Lozano AM, Tasker RR, Dostrovsky JO.
Human anterior cingulate cortex neurones modulated by attention-
demanding tasks. J Neurophysiol 2000; 83: 3575±7.
Ffytche DH, Howard RJ, Brammer MJ, David A, Woodruff P,
Williams S. The anatomy of conscious vision: an fMRI study of
visual hallucinations. Nat Neurosci 1998; 1: 738±42.
Horwitz B, Rumsey JM, Donohue BC. Functional connectivity of
the angular gyrus in normal reading and dyslexia. Proc Natl Acad
Sci USA 1998; 95: 8939±44.
Jasper HH. The ten twenty electrode system of the International
Federation. Electroencephalogr Clin Neurophysiol 1958; 10: 371±5.
Jewett ME, Wyatt JK, Ritz-De Cecco A, Khalsa SB, Dijk DJ,
Czeisler CA. Time course of sleep inertia dissipation in human
performance and alertness. J Sleep Res 1999; 8: 1±8.
Kleitman N. Sleep and Wakefulness. 2nd ed. Chicago: University of
Chicago Press; 1963.
Lubin A, Hord D, Tracy M, Johnson LC. Effects of exercise,
bedrest and napping on performance decrement during 40 hours.
Psychophysiology 1976; 13: 334±9.
Lumer ED, Friston KJ, Rees G. Neural correlates of perceptual
rivalry in the human brain. Science 1998; 280: 1930±4.
Maquet P, Peters J, Aerts J, Del®ore G, Degueldre C, Luxen A,
Franck G. Functional neuroanatomy of human rapid-eye-movement
sleep and dreaming. Nature 1996; 383: 163±6.
Moruzzi G, Magoun HW. Brain stem and reticular formation and
activation of the EEG. Electroencephalogr Clin Neurophysiol 1949;
1: 455±73.
Rechtschaffen A, Kales A, editors. A manual of standardized
terminology, techniques and scoring system for sleep stages of
human subjects. NIH Publication No. 204. Bethesda (MD): U.S.
Dept. of Health, Education and Welfare; 1968.
2318 T. J. Balkin et al.
by guest on June 1, 2013 from
Revonsuo A. Can functional brain imaging discover consciousness
in the brain? J Conscious Stud 2001; 8: 3±23.
Sahraie A, Weiskrantz L, Barbur JL, Simmons A, Williams SC,
Brammer MJ. Pattern of neuronal activity associated with conscious
and unconscious processing of visual signals. Proc Natl Acad Sci
USA 1997; 94: 9406±11.
Talairach J, Tournoux P. Co-planar stereotaxic atlas of the human
brain. Stuttgart: Thieme; 1988.
Tassi P, Muzet A. Sleep inertia. Sleep Med Rev 2000; 4: 341±53.
Thomas M, Sing H, Belenky G, Holcomb H, Mayberg H, Dannals
R, et al. Neural basis of alertness and cognitive performance
impairments during sleepiness. I. Effects of 24 h of sleep
deprivation on waking human regional brain activity. J Sleep Res
2000; 9: 335±52.
Zeman A. Consciousness. [Review]. Brain 2001; 124: 1263±89.
Received December 17, 2001. Revised May 7, 2002.
Accepted May 13, 2002
Process of awakening 2319
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... Arousal (spoken command)-induced brain activations during emergence from anesthesia are mostly localized in deep, phylogenetically old brain structures (hippocampus or limbic cortex or mesial temporal structures) than in neocortex. 1,3 Thus, the emergence of a conscious state precedes the full recovery of neocortical processing required for establishing contact with the surroundings. 2 Brain surgeries, especially, epilepsy surgery may interfere with these structures directly or indirectly. ...
Full-text available
Objective Emergence from anesthesia starts from the limbic structures and then spreads outwards to brainstem, reticular activating systems, and then to the cortex. Epilepsy surgery often involves resection of limbic structures and hence may disrupt the pattern of emergence. The aim of this study was to explore the pattern of emergence from anesthesia following epilepsy surgery and to determine associated variables affecting the emergence pattern. Setting and Design Tertiary care center, prospective observational study. Materials and Methods We conducted a prospective observation pilot study on adult patients undergoing anterior temporal lobectomy and amygdalohippocampectomy for epilepsy. Anesthesia management was standardized in all patients, and they were allowed to wake up with “no touch” technique. Primary outcome of the study was the pattern of emergence (normal emergence, agitated emergence, or slow emergence) from anesthesia. Secondary outcomes were to explore the differences in preoperative neuropsychological profile and limbic structure volumes between the different patterns of emergence. Quantitative variables were analyzed using Student's t-test. Qualitative variables were analyzed using chi-square test. Results Twenty-nine patients completed the study: 9 patients (31%) had agitated emergence, and 20 patients had normal emergence. Among the agitated emergence, 2 patients had Riker scale of 7 indicating violent emergence. Patient demographics, anesthetic used, neuropsychological profile, and limbic structure volumes were similar between normal emergence and agitated emergence groups. However, two patients who had severe agitation (Riker scale of 7) had the lowest intelligence quotient. Conclusion Our pilot study showed that emergence agitation is not uncommon in patients undergoing epilepsy surgery. However, due to smaller sample size, the role of preoperative neuropsychologic profile and hippocampal volumes in predicting the pattern of emergence is inconclusive.
... In this context of constant adaptation, hypersomnolence refers to exceeding the ability to increase the level of arousal when it is required. Hypersomnolence related symptoms are believed to be underpinned by the temporospatial dynamics of sleep/ wake states, with short-term fluctuations (for example microsleep episodes during wakefulness [25][26][27][28]) and/or spatial heterogeneity and asynchrony in local sleep/wake states (local sleep) as demonstrated by high-density electro-encephalography (EEG), intracranial-EEG or imaging studies in healthy individuals [29][30][31][32][33][34][35]. Such transition states might be more frequent, pronounced and prolonged in patients with disorders of hypersomnolence, as a result of different pathophysiological mechanisms in networks involved in sleep/ wake states regulation (see Section 5) [36]. ...
Hypersomnolence is a major public health issue given its high frequency, its impact on academic/occupational functioning and on accidentology, as well as its heavy socio-economic burden. The positive and aetiological diagnosis is crucial, as it determines the therapeutic strategy. It must consider the following aspects: i) hypersomnolence is a complex concept referring to symptoms as varied as excessive daytime sleepiness, excessive need for sleep, sleep inertia, or drowsiness, all of which warrant specific dedicated investigations; ii) the boundary between physiological and abnormal hypersomnolence is blurred, since most symptoms can be encountered in the general population to varying degrees without being considered as pathological, meaning that their severity, frequency, context of occurrence and related impairment need to be carefully assessed; iii) investigation of hypersomnolence relies on scales/questionnaires as well as behavioural and neurophysiological tests, which measure one or more dimensions, keeping in mind the possible discrepancy between objective and subjective assessment; iv) aetiological reasoning is driven by knowledge of the main sleep regulation mechanisms, epidemiology, and associated symptoms. The need to assess hypersomnolence is growing, both for its management, and for assessing the efficacy of treatments. The landscape of tools available for investigating hypersomnolence is constantly evolving, in parallel with research into sleep physiology and technical advances. These investigations face the challenges of reconciling subjective perception and objective data, making tools accessible to as many people as possible and predicting the risk of accidents.
... 7e9 Notably, emergence from dexmedetomidine-and propofol-induced unresponsiveness, and awakening from N2 sleep involve activation of these same areas. 8,10,11 On the neurophysiological level, general anaesthesia and NREM sleep generate similar, although not identical, changes in canonical EEG frequency bands, most notably an increase in slow wave activity and a decrease in highfrequency activity. 12e16 Dexmedetomidine induces a state neurophysiologically closest to NREM sleep: dexmedetomidine sedation shows spindle activity typical for N2 sleep, and deeper, unresponsive dexmedetomidine sedation produces strong delta activity, akin to N3 sleep. ...
Background: Anaesthetic-induced unresponsiveness and non-rapid eye movement (NREM) sleep share common neural pathways and neurophysiological features. We hypothesised that these states bear resemblance also at the experiential level. Methods: We compared, in a within-subject design, the prevalence and content of experiences in reports obtained after anaesthetic-induced unresponsiveness and NREM sleep. Healthy males (N=39) received dexmedetomidine (n=20) or propofol (n=19) in stepwise doses to induce unresponsiveness. Those rousable were interviewed and left unstimulated, and the procedure was repeated. Finally, the anaesthetic dose was increased 50%, and the participants were interviewed after recovery. The same participants (N=37) were also later interviewed after NREM sleep awakenings. Results: Most subjects were rousable, with no difference between anaesthetic agents (P=0.480). Lower drug plasma concentrations were associated with being rousable for both dexmedetomidine (P=0.007) and propofol (P=0.002) but not with recall of experiences in either drug group (dexmedetomidine: P=0.543; propofol: P=0.460). Of the 76 and 73 interviews performed after anaesthetic-induced unresponsiveness and NREM sleep, 69.7% and 64.4% included experiences, respectively. Recall did not differ between anaesthetic-induced unresponsiveness and NREM sleep (P=0.581), or between dexmedetomidine and propofol in any of the three awakening rounds (P>0.05). Disconnected dream-like experiences (62.3% vs 51.1%; P=0.418) and memory incorporation of the research setting (88.7% vs 78.7%; P=0.204) were equally often present in anaesthesia and sleep interviews, respectively, whereas awareness, signifying connected consciousness, was rarely reported in either state. Conclusions: Anaesthetic-induced unresponsiveness and NREM sleep are characterised by disconnected conscious experiences with corresponding recall frequencies and content. Clinical trial registration: Clinical trial registration. This study was part of a larger study registered at (NCT01889004).
... The thalamus is an essential part of the ascending reticular activating system (Moruzzi and Magoun, 1949), which projects to the cortical structure in all directions and serves as an integrative hub for the exchange of information (Basso et al., 2005). Thalamic activity is closely related to relaying sensory and motor signals to the cerebral cortex, and regulating sleep, vigilance and consciousness (Balkin et al., 2002;Falahpour et al., 2018;Långsjö et al., 2012;Zou et al., 2020b). Patients with paramedian thalamic syndromes exhibit impairment in sleep-wake regulation (Montagna et al., 2003). ...
Background: Fatigue is the most common daytime impairment of insomnia disorder (ID). Thalamus is acknowledged as the key brain region closely associated with fatigue. However, the thalamus-based neurobiological mechanisms of fatigue in patients with ID remain unknown. Methods: Forty-two ID patients and twenty-eight well-matched healthy controls (HCs) underwent simultaneous electroencephalography--functional magnetic resonance imaging. We calculated the functional connectivity (FC) between the thalamic seed and each voxel across the whole brain in two conditions of wakefulness--after sleep onset (WASO) and before sleep onset. A linear mixed effect model was used to determine the condition effect of the thalamic FC. The correlation between daytime fatigue and the thalamic connectivity was explored. Results: After sleep onset, the connectivity with the bilateral thalamus was increased in the cerebellar and cortical regions. Compared with HCs, ID patients showed significantly lower FC between left thalamus and left cerebellum under the WASO condition. Furthermore, thalamic connectivity with cerebellum under the WASO condition was negatively correlated with Fatigue Severity Scale scores in the pooled sample. Conclusions: These findings contribute to an emerging framework that reveals the link between insomnia-related daytime fatigue and the altered thalamic network after sleep onset, further highlighting the possibility that this neural pathway is a therapeutic target for meaningfully mitigating fatigue.
Full-text available
Sleep can be distinguished from wake by changes in brain electrical activity, typically assessed using electroencephalography (EEG). The hallmark of nonrapid-eye-movement (NREM) sleep is the shift from high-frequency, low-amplitude wake EEG to low-frequency, high-amplitude sleep EEG dominated by spindles and slow waves. Here we identified signatures of sleep in brain hemodynamic activity, using simultaneous functional MRI (fMRI) and EEG. We found that, at the transition from wake to sleep, fMRI blood oxygen level-dependent (BOLD) activity evolved from a mixed-frequency pattern to one dominated by two distinct oscillations: a low-frequency (<0.1 Hz) oscillation prominent in light sleep and correlated with the occurrence of spindles, and a high-frequency oscillation (>0.1 Hz) prominent in deep sleep and correlated with the occurrence of slow waves. The two oscillations were both detectable across the brain but exhibited distinct spatiotemporal patterns. During the falling-asleep process, the low-frequency oscillation first appeared in the thalamus, then the posterior cortex, and lastly the frontal cortex, while the high-frequency oscillation first appeared in the midbrain, then the frontal cortex, and lastly the posterior cortex. During the waking-up process, both oscillations disappeared first from the thalamus, then the frontal cortex, and lastly the posterior cortex. The BOLD oscillations provide local signatures of spindle and slow wave activity. They may be employed to monitor the regional occurrence of sleep or wakefulness, track which regions are the first to fall asleep or wake up at the wake-sleep transitions, and investigate local homeostatic sleep processes.
Full-text available
Purpose: Sleep inertia (SI) is the transitional state accompanied by compromised cognitive and physical performance and sleepiness. Network analysis offers a potential new framework to conceptualize a complex network of symptom-symptom interactions, and the network structure is analyzed to reveal the core characteristics. However, no previous study examined the network structure of SI symptoms. Thus, this study aimed to elucidate characteristics and compare sex differences of SI symptom networks in the general population. Materials and methods: A total of 1491 participants from China were recruited from 30 May to 17 June, 2021. SI symptoms were assessed by using the Sleep Inertia Questionnaire (SIQ). The network structures were estimated and compared using network analytic methods in the R version 4.1.1. Results: Centrality properties analysis of the expected influence suggested that symptoms of "Feel sleepy", "Groggy, fuzzy or hazy mind", and "Dread starting your day" exerted greatest influences. The weighted adjacency matrix revealed that the "Dread starting your day" and "Anxious about the upcoming day" edge showed the strongest connection (edge weight value = 0.70). The network comparison test found no significant difference in network global strength (p=0.928), distribution of edge weights (p=0.194) and individual edge weights (all p values >0.05 after Holm-Bonferroni corrections) between males and females. Conclusion: Symptoms of "Feel sleepy", "Groggy, fuzzy or hazy mind", and "Dread starting your day" were central in the SI symptom network. Intervention, such as the artificial dawn and change in body temperature, for symptoms of "Feel sleepy", "Groggy, fuzzy or hazy mind", and "Dread starting your day" might be crucial to hasten the dissipation of SI in the general population who may need to perform tasks upon waking.
Conference Paper
Sleep inertia is a transitional state from sleep to wakefulness, accompanied by groggy feelings and cognitive impairment. Previous research on sleep inertia mainly used expensive and cumbersome equipment, and the analysis of physiological signals relied on computers. This work introduces a sleep inertia detection system that consists of a wearable lowpower electroencephalogram (EEG) acquisition module based on STM32WB55 and ADS1299, and a data processing module based on the Xilinx® Zynq®-7000 XC7Z020. This work recorded the EEG signals of ten subjects in the alert and sleep inertia states to extract the delta power, alpha power, beta power, EEG vigilance, and sample entropy. A linear support vector machine (SVM) was then used to classify the two states based on all subjects’ EEG signals, with an accuracy of 72.5%, and the average accuracy based on a single participant was 88.9%. Finally, the feature extraction algorithm and SVM parameters were entered into the Zynq® system-on-chip (SoC) development board to realize onboard processing of the algorithm. The system is capable of evaluating the severity of human sleep inertia, which has reference significance for the practical application of sleep inertia detection.
Full-text available
Purpose Optimal cognitive performance might prevent vehicle accidents. Identifying time-related circadian and homeostatic parameters having an impact on cognitive performance of drivers may be crucial to optimize drivers’ performance. Methods In this prospective study conducted on bus drivers, two drivers alternated driving during a 24-h round trip and were accompanied by an interviewer. Each driver was tested using Karolinska Sleepiness Scale (KSS) and the reversed digit span Wechsler Working Memory test before the start of his shift and then every 6 h during a “work/driving” day. Psychomotor Vigilance Task (PVT) was assessed before and after the journey. Linear mixed model was used to explore the factors affecting cognitive performance and sleepiness in univariate and multivariate analysis. Results Among 35 bus drivers, the effect of time of day on working memories was statistically significant (p = 0.001), with the lowest working memory scores at 04:00 am (± 1). The highest score of subjective sleepiness was also at 04:00 am (± 1). The time on task parameter affected sleepiness significantly (p = 0.024) and sleepiness was significantly associated with decreased working memory. Psychomotor Vigilance Task reaction time mean and the number of minor lapses were significantly increased after the journey, which suggested decreased vigilance. In multivariable analysis, a longer interval between the beginning of working hours and testing time (B (95% CI) = 15.25 (0.49 to 30), p = 0.043) was associated with higher (i.e., slower) PVT reaction time mean. Conclusions These results suggest that optimizing bus drivers’ working schedules may improve drivers’ sleepiness and cognitive performance and thus increase road safety.
Full-text available
Study objectives: Sleep inertia is a frequent and disabling symptom in idiopathic hypersomnia (IH), but poorly defined and without objective measures. The study objective was to determine whether the psychomotor vigilance task (PVT) can reliably measure sleep inertia in patients with IH or other sleep disorders (non-IH). Methods: Sixty-two (51 women, mean age: 27.7±9.2) patients with IH and 140 (71 women, age: 33.3±12.1) with non-IH (narcolepsy=29, non-specified hypersomnolence NSH=47, obstructive sleep apnea=39, insomnia=25) were included. Sleep inertia and sleep drunkenness in the last month (M-sleep inertia) and on PVT day (D-sleep inertia) were assessed with three items of the Idiopathic Hypersomnia Severity Scale (IHSS), in drug-free conditions. The PVT was performed four times (7:00 PM, and 7:00, 7:30 and 11:00 AM) and three metrics were used: lapses, mean 1/Reaction Time (RT), slowest 10% 1/RT. Results: Sleep inertia was more frequent in patients with IH than non-IH (56.5% and 43.6% with severe sleep inertia in the past month, including 24% and 12% with sleep drunkenness). Lapse number increase and slowest 10% 1/RT decrease, particularly at 7:00 and 7:30AM, were proportional with M-sleep inertia severity, but regardless of sleep drunkenness and sleep disorders. Similar results were obtained when PVT results were compared in patients with/without D-sleep inertia, with the largest increase of the lapse number at 7:00 and 7:30AM associated with severe sleep inertia and sleep drunkenness. Conclusion: PVT is a reliable and objective measure of sleep inertia that might be useful for its characterization, management and follow-up in patients with IH.
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Following striate cortex damage in monkeys and humans there can be residual function mediated by parallel visual pathways. In humans this can sometimes be associated with a “feeling” that something has happened, especially with rapid movement or abrupt onset. For less transient events, discriminative performance may still be well above chance even when the subject reports no conscious awareness of the stimulus. In a previous study we examined parameters that yield good residual visual performance in the “blind” hemifield of a subject with unilateral damage to the primary visual cortex. With appropriate parameters we demonstrated good discriminative performance, both with and without conscious awareness of a visual event. These observations raise the possibility of imaging the brain activity generated in the “aware” and the “unaware” modes, with matched levels of discrimination performance, and hence of revealing patterns of brain activation associated with visual awareness. The intact hemifield also allows a comparison with normal vision. Here we report the results of a functional magnetic resonance imaging study on the same subject carried out under aware and unaware stimulus conditions. The results point to a shift in the pattern of activity from neocortex in the aware mode, to subcortical structures in the unaware mode. In the aware mode prestriate and dorsolateral prefrontal cortices (area 46) are active. In the unaware mode the superior colliculus is active, together with medial and orbital prefrontal cortical sites.
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To assess dynamic changes in brain function throughout the sleep-wake cycle, CBF was measured with H2(15)O and PET in 37 normal male volunteers: (i) while awake prior to sleep onset; (ii) during Stage 3-4 sleep, i.e. slow wave sleep (SWS); (iii) during rapid eye movement (REM) sleep; and (iv) upon waking following recovery sleep. Subjects were monitored polysomnographically and PET images were acquired throughout the course of a single night. Stage-specific contrasts were performed using statistical parametric mapping. Data were analysed in repeated measures fashion, examining within-subject differences between stages [pre-sleep wakefulness-SWS (n = 20 subjects); SWS-post-sleep wakefulness (n = 14); SWS-REM sleep (n = 7); pre-sleep wakefulness-REM sleep (n = 8); REM sleep-post-sleep wakefulness (n = 7); pre-sleep wakefulness-post-sleep wakefulness (n = 20)]. State dependent changes in the activity of centrencephalic regions, including the brainstem, thalamus and basal forebrain (profound deactivations during SWS and reactivations during REM sleep) are consistent with the idea that these areas are constituents of brain systems which mediate arousal. Shifts in the level of activity of the striatum suggested that the basal ganglia might be more integrally involved in the orchestration of the sleep-wake cycle than previously thought. State-dependent changes in the activity of limbic and paralimbic areas, including the insula, cingulate and mesial temporal cortices, paralleled those observed in centrencephalic structures during both REM sleep and SWS. A functional dissociation between activity in higher order, heteromodal association cortices in the frontal and parietal lobes and unimodal sensory areas of the occipital and temporal lobes appeared to be characteristic of both SWS and REM sleep. SWS was associated with selective deactivation of the heteromodal association areas, while activity in primary and secondary sensory cortices was preserved. SWS may not, as previously thought, represent a generalized decrease in neuronal activity. On the other hand, REM sleep was characterized by selective activation of certain post-rolandic sensory cortices, while activity in the frontoparietal association cortices remained depressed. REM sleep may be characterized by activation of widespread areas of the brain, including the centrencephalic, paralimbic and unimodal sensory regions, with the specific exclusion of areas which normally participate in the highest order analysis and integration of neural information. Deactivation of the heteromodal association areas (the orbital, dorsolateral prefrontal and inferior parietal cortices) constitutes the single feature common to both non-REM and REM sleep states, and may be a defining characteristic of sleep itself. The stages of sleep could also be distinguished by characteristic differences in the relationships between the basal ganglia, thalamic nuclei and neocortical regions of interest.
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When dissimilar images are presented to the two eyes, perception alternates spontaneously between each monocular view, a phenomenon called binocular rivalry. Functional brain imaging in humans was used to study the neural basis of these subjective perceptual changes. Cortical regions whose activity reflected perceptual transitions included extrastriate areas of the ventral visual pathway, and parietal and frontal regions that have been implicated in spatial attention; whereas the extrastriate areas were also engaged by nonrivalrous perceptual changes, activity in the frontoparietal cortex was specifically associated with perceptual alternation only during rivalry. These results suggest that frontoparietal areas play a central role in conscious perception, biasing the content of visual awareness toward abstract internal representations of visual scenes, rather than simply toward space.
If we assume that consciousness is a natural biological phenomenon in the brain, should we expect the current brain sensing and imaging methods to somehow ‘discover’ consciousness? The answer depends on the following points: What kind of level of biological organization do we assume consciousness to be? What would count as the discovery of this level? What are the levels of organization from which the currently available research instruments pick signals and acquire data? Single-cell recordings, PET, fMRI, EEG and MEG pick different types of signals from different levels of organization in the brain. However, it seems they do not manage to pick signals that would allow the direct visualization and reconstruction of the higher levels of electrophysiological organization that are crucial for the empirical discovery and theoretical explanation of consciousness. The message of the present paper is twofold: On the one hand, we should be aware of the practical limitations of the currently available methods of cognitive neuroscience and not read too much into the images produced by them. On the other hand, the present limitations could be overcome by more sophisticated methods in the future. Therefore, contrary to what several philosophers have argued, the empirical discovery of consciousness in the brain is not impossible in principle.
Alertness and performance on a wide variety of tasks are impaired immediately upon waking from sleep due to sleep inertia, which has been found to dissipate in an asymptotic manner following waketime. It has been suggested that behavioural or environmental factors, as well as sleep stage at awakening, may affect the severity of sleep inertia. In order to determine the time course of sleep inertia dissipation under normal entrained conditions, subjective alertness and cognitive throughput were measured during the first 4 h after habitual waketime from a full 8-h sleep episode on 3 consecutive days. We investigated whether this time course was affected by either sleep stage at awakening or behavioural/environmental factors. Sleep inertia dissipated in an asymptotic manner and took 2–4 h to near the asymptote. Saturating exponential functions fitted the sleep inertia data well, with time constants of 0.67 h for subjective alertness and 1.17 h for cognitive performance. Most awakenings occurred out of stage rapid eye movement (REM), 2 or 1 sleep, and no effect of sleep stage at awakening on either the severity of sleep inertia or the time course of its dissipation could be detected. Subjective alertness and cognitive throughput were significantly impaired upon awakening regardless of whether subjects got out of bed, ate breakfast, showered and were exposed to ordinary indoor room light (≈150 lux) or whether subjects participated in a constant routine (CR) protocol in which they remained in bed, ate small hourly snacks and were exposed to very dim light (10–15 lux). These findings allow for the refinement of models of alertness and performance, and have important implications for the scheduling of work immediately upon awakening in many occupational settings.
Young male Naval volunteers were denied normal noclurnal sleep and maintained on a 60-min lreatment-160-min testing schedule during 40 consecutive hrs. Ten subjects bicycled, 20 subjects controlled EEG activity during bedrest, and 10 subjects napped. Eight measures of addition, auditory vigilance, mood, and oral temperature were obtained. The Bedrest group showed significant impairment on all eight measures, and thus, gave no support to lite forced-rest theory of sleep function. The Exercise group was worse than the Nap and Bedrest groups for all measures. In spite of fragmented, reduced sleep (about 3.7 hrs per 24 hrs), the Nap group had no impairment on six of the measures. The results suggest that exercise increases the impairment due to sleep loss, and naps reduce or remove this impairment. Bedrest is not a substitute for sleep.
Performance deficits are usually evident following both extended wakefulness (sleep deprivation effects) and immediately upon awakening from sleep (sleep inertia effects). In order to determine whether sleep inertia effects are qualitatively different from sleep deprivation effects, performance on addition tests, Stanford Sleepiness Scale (SSS) ratings, and return-to-sleep latencies (RSLs) were assessed during four nights of sleep disruption/restriction. Eight subjects were polygraphically monitored in the sleep laboratory for five consecutive nights, from 2400 to 0700. On the last four nights (after an adaptation night) subjects were awakened at 0040, 0140, 0240, 0340, 0440, and 0540 for a 20-min test session. Sleepiness ratings and performance on 5-min addition tests were measured at 1.5, 7.5, and 13.5 min post-awakening, and RSL was measured at the end of each test session. Analysis of addition test performance across nights revealed that both speed and accuracy of calculations were adversely affected by the sleep disruption/restriction procedure, indicating that increasing sleepiness exacerbates sleep performance deficits upon awakening. Although divergence of SSS ratings and addition test performance across nights was suggestive, there was no conclusive evidence that sleep inertia is qualitatively different from "typical" sleepiness.