Cerebral Cortex May 2009;19:1158--1166
Advance Access publication October 1, 2008
REM Sleep, Prefrontal Theta, and the
Consolidation of Human Emotional
Masaki Nishida1,2, Jori Pearsall1,3, Randy L. Buckner3,4and
Matthew P. Walker1
1Sleep and Neuroimaging Laboratory Department of
Psychology and Helen Wills Neuroscience Institute, University
of California, Berkeley, CA 94702, USA,2Section of Psychiatry
and Behavioral Science, Tokyo Medical and Dental University
Graduate School, 1-5-45 Yushima, Bunkyo, Tokyo, Japan,
3Department of Psychology, Center for Brain Science, Howard
Hughes Medical Institute, Harvard University, Davis, CA 95618,
USA and4Departments of Psychiatry and Radiology, Anthinoula
A. Martinos Center, Massachusetts General Hospital, Boston,
MA 02114, USA
Both emotion and sleep are independently known to modulate
declarative memory. Memory can be facilitated by emotion, leading
to enhanced consolidation across increasing time delays. Sleep also
facilitates offline memory processing, resulting in superior recall the
next day. Here we explore whether rapid eye movement (REM)
sleep, and aspects of its unique neurophysiology, underlie these
convergent influences on memory. Using a nap paradigm, we
measured the consolidation of neutral and negative emotional
memories, and the association with REM-sleep electrophysiology.
Subjects that napped showed a consolidation benefit for emotional
but not neutral memories. The No-Nap control group showed no
evidence of a consolidation benefit for either memory type. Within
the Nap group, the extent of emotional memory facilitation was
significantly correlated with the amount of REM sleep and also with
right-dominant prefrontal theta power during REM. Together, these
data support the role of REM-sleep neurobiology in the consolidation
of emotional human memories, findings that have direct trans-
lational implications for affective psychiatric and mood disorders.
Keywords: consolidation, emotion, memory, REM, prefrontal, theta
Over the last decade, diverse studies spanning descriptive
levels have offered converging evidence that sleep plays
a critical role in memory processing and brain plasticity
(Walker and Stickgold 2006). These findings indicate that
sleep, and its varied stages, contribute to latent processes of
both declarative and procedural memory consolidation (Walker
and Stickgold 2004; Marshall and Born 2007). Aspects of the
relationship between declarative memory and sleep have,
however, been questioned based on earlier studies that were
equivocal—some confirming a role for sleep, others refuting it
(Ellenbogen et al. 2006). Thus, the role of sleep in facilitating
declarative memory remains an active topic of debate.
Independent of the field of sleep, there is a growing
literature demonstrating that memory processing is modulated
by the emotional strength of the material being learned (Cahill
2000; McGaugh 2004; Phelps 2004). Under certain conditions,
memories including affective content persist more strongly
over time than memories lacking emotional tone (Kensinger
2004). Moreover, this behavioral benefit has been related to
specific changes in neurochemical and neurophysiological
states in certain subcortical and cortical networks (Cahill
2000; McGaugh 2000; Pare et al. 2002; McGaugh 2004; Phelps
2004). Most interestingly, considerable overlap exists between
the putative neurobiological mechanisms that orchestrate
emotional memory consolidation (Cahill 2000; McGaugh
? 2008 The Authors
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2004; Phelps 2004) and those that are engaged during rapid
eye movement (REM) sleep, including prominent oscillatory
activity in the theta frequency band range, raised levels of
acetylcholine (ACh), and the re-emergence of coupled
hippocampal and amygdala network activity (Hobson and
Pace-Schott 2002; Pare et al. 2002; Hu et al. 2006).
Despite these parallel lines of evidence, there has been
a paucity of research examining the interaction between sleep
and emotional memory consolidation in the human brain.
Instead, investigations have been limited largely to animal
models, principally focusing on the sleep-dependent sensitivity
of contextual fear and shock avoidance learning. For example,
daytime training on such tasks commonly triggers alterations in
sleep-stage and sleep-architecture characteristics, particularly
REM (e.g., Smith et al. 1980; Hennevin and Hars 1987; Ambrosini
et al. 1988; Mandai et al. 1989; Ambrosini et al. 1993; Sanford et al.
2001, 2003), considered to reflect a homeostatic demand on
REM-dependent consolidation mechanisms. Furthermore, total
as well as selective REM-sleep deprivation after learning disrupts
consolidation and impairs next day memory retention (e.g.,
Pearlman 1969; Fishbein et al. 1974; Shiromani et al. 1979; Smith
and Lapp 1986; Hennevin and Hars 1987; Oniani et al. 1987;
Marti-Nicolovius et al. 1988; Smith and Kelly 1988; Beaulieu and
Godbout 2000; Graves et al. 2003). Such findings suggest that, in
rodents, consolidation of affective learning displays a sensitivity
to, and even dependency on, sleep (and REM in particular).
An alternative explanation for the memory impairments
reported in several of these earlier animal studies has been the
increased stress of prolong wakefulness, rather than the lack of
sleep itself. But more recent studies have demonstrated that
selective deprivation of specific sleep stages, and even specific
sleep-stage time windows (some located many hours to days
after training), still inhibits memory consolidation (Smith and
Butler 1982; Smith and Kelly 1988). Furthermore, Smith et al.
(1991) have shown that administration of protein synthesis
inhibitors (which block cellular consolidation cascades) during
specific REM-sleep windows in rats prevents behavioral
improvement following sleep, without requiring deprivation.
Such findings make arguments of sleep deprivation-induced
effects of stress on memory consolidation far less tenable.
To date, several reports have investigated the influence of
sleep on emotional memory consolidation in humans, demon-
strating a retention advantage across periods containing sleep
relative to equivalent time periods awake (Hu et al. 2006; Payne
et al. forthcoming), and particularly late-night sleep, rich in
REM (Wagner et al. 2001, 2006). However, no study has yet
examined the relationship between specific sleep-stages and
emotional memory consolidation, or the associated underlying
neurophysiological correlates that accompany sleep. Using
a nap paradigm, here we explore the consolidation of neutral
and negative emotional memories, and test the hypothesis that
affective memories are selectively facilitated by REM sleep, and
specifically oscillations in the theta frequency range.
Materials and Methods
Thirty-one subjects between the ages of 18 and 30 were assigned to
either a Nap group (n = 15; 7 males, mean age 24.3 [SD ± 2.0]) or No-
Nap group (n=16, 8 males, mean age 23.1 [SD ± 1.4]). Subjects had no
prior history of drug or alcohol abuse, neurological, psychiatric or sleep
disorders. Subjects were not considered as habitual nappers based on
a sleep habit questionnaire obtained at initial screen, indicating one or
less naps per week on average. Subjects maintained a regular sleep
schedule 1 week prior to the study and abstained from caffeine,
nonexperimental naps, and alcohol throughout the course of the study.
The study was approved by the local human studies committee and
conducted according to the principles expressed in the Declaration of
Helsinki, with all subjects providing written informed consent.
Experimental Design: Nap and No-Nap Groups
Both groups performed 2 study sessions, in which they learned
emotionally negative (unpleasant valence, high arousal) and neutral
(neutral valence, low arousal) picture stimuli, selected from a standard-
ized picture set (Lang 1997). The study sessions occurred 4 h prior and
15 min prior to a recognition memory test (Fig. 1). At the recognition
test, both sets of previously studied items from the 4- and 15-min study
sessions were presented, together with intermixed foils (new
emotional and neutral stimuli not previously seen), with subjects
indicating whether they believed the stimuli to be old (from both study
sessions) or new (not seen before). Offline consolidation was indexed
as the difference in recognition memory score for items from the 4-h
study session compared with items from the 15-min study session
(Fig. 1). Following the first study session, but prior to the second, those
in the Nap group obtained a 90-min sleep opportunity (1:15 PM ± 20
min), recorded with polysomnography (PSG), whereas those in the No-
Nap group remained awake. Thus, items from the first (4 h) study
session transitioned through different brain-states in each group prior
to testing, containing sleep in the Nap group and no sleep in the No-
Nap group, yet experienced identical brain-state conditions following
the second (15 min) study session prior to testing (Fig. 1). During the
interval between the ‘‘study’’ and ‘‘test’’ sessions, subjects were allowed
to leave the lab and go about their normal daily activities, with the
exception of the 90-min sleep opportunity in the Nap group.
The computerized task was composed of pictures selected from the
International Affective Picture System (IAPS), a series of stimuli with
standardized emotional ratings (Lang 1997). A total of 360 picture
stimuli were compiled, matched in terms of visual stimulus character-
istics (including faces, human figures and luminance), and which varied
in arousal and valence strength on a scale from 1 to 9 (Lang 1997). Half
of the stimuli were classified as negatively ‘‘emotional’’ (arousal mean ±
SD 5.77 ± 0.59, valence mean ± SD 3.89 ± 1.98), the other half ‘‘neutral’’
(arousal mean ± SD 3.80 ± 0.67, valence mean ± SD 5.61 ± 1.28). The
360 stimuli were split into 3 sets of 120 balanced pictures: 60 emotional
and 60 neutral stimuli, submatched for arousal and valence strength
according to the above classifications. At each of the 2 study sessions,
subjects viewed a set of the 120 stimuli. At the later recognition test,
that subjects were aware of, the original 240 stimuli were presented
(120 from each of the study sessions), together with the remaining 120
‘‘new’’ stimuli (foils) intermixed (Fig. 1). Subjects viewed the stimuli on
a 17$ CRT monitor at full width and height. The order presentation of
the stimuli was pseudorandom, with no more than 3 stimuli of either
emotional or neutral categories being presented in succession.
Each of the study session trials began with the presentation of an
initial fixation-crosshair (500 ms), followed by the target picture (1000
ms), followed by a blank screen (500 ms), after which a ‘‘respond’’
screen was shown, indicating that subjects had to make a decision as to
whether the picture represented an indoor or outdoor scene. The next
trial began after the keyboard response.
At the subsequent recognition test, each of the 360 trials (240
original pictures, 120 new foils) began with the fixation-crosshair (500
ms), followed by the picture stimulus presentation (1000 ms), after
which a ‘‘respond’’ screen was shown, indicating that subjects had to
make their right-handed recognition keyboard choice of old or new.
The next trial did not begin until subjects made a recognition
judgment. From these choices, 4 response categories were possible:
correct old judgments (‘‘hits’’), incorrect old judgments (‘‘misses’’),
correct new judgments (‘‘correct rejections’’), and incorrect new
judgments (‘‘false alarms’’), with recognition accuracy (d#) calculated
according to signal detection theory (i.e. the difference between the
z-transformed (normalized) probabilities of hit and false alarm rates:
d# = z(hit rate) – z(false alarm rate) where hit rate (HR) and false alarm
rate(FAR)aretheHit andFalseAlarm Rates,respectively (Macmillanand
Creelman 1991). The extent of offline consolidation was indexed as the
difference in recognition memory score (d#) for items from the 4hr
h score--15 min score]).
Figure 1. Experimental design. Subjects in each group viewed a series of picture slides (half emotional, half neutral) at 2 study sessions; 4 h prior (1 PM) and 15 min prior (5 PM)
to a recognition memory test (5:15 PM). Between study sessions, the Nap group was given a 90 min sleep opportunity, whereas subjects in the No-Nap group remained awake.
The nap period was recorded with digitized PSG. Therefore, 2 different ‘‘aged’’ memory sets were examined (4 h old and 15 min old), with stimuli from the first study session (4-h
study) transitioning through different brain-states in each group prior to testing—sleep in the Nap group and no sleep in the No-Nap group—yet experienced identical brain-state
conditions following the second study session (15-min study), prior to testing.
Cerebral Cortex May 2009, V 19 N 5 1159
PSG Recording and Electrophysiological Analysis
PSG recording was performed in accordance with standardized
techniques, using digital electroencephalography (EEG), electromyog-
raphy, and eletrooculography signals acquired with a Grass Colleague
system (sampling rate: 256Hz, high- and low-pass filter 0.3 and 35 Hz,
respectively, notch filter 60 Hz). A mastoid referenced PSG electrode
montage was utilized, composed of EEG sites F3 and C3 (referenced to
A2), and F4 and C4 (referenced to A1). Each sleep epoch was scored
blind to subjects behavioral task performance in accordance with
standard criteria (Rechtschaffen and Kales 1968), with the exception of
epoch length, which was set at 20s to conform with our spectral
analysis window length (see below). The PSG recording was scored
visually, epoch by epoch, as either NREM stages 1-4, REM sleep, awake
or movement time. Slow-wave sleep (SWS) was calculated as NREM
stages 3 and 4 combined.
Quantitative EEG analysis was performed by custom Matlab scripts
(The MathWorks Inc, Natick, MA), built within the EEGLAB toolbox
([http://www.sccn.ucsd.edu/eeglab/]). Following removal of visually
identified epochs containing muscle, cardiac and eye movement
artifacts, spectral analysis was applied to each 4-s EEG epoch from
stage 1, stage 2, SWS and REM sleep. One participant was excluded
from the analysis due to poor quality recording in combination with
excessive artifact components. Spectral power density was estimated
for each epoch using Welch’s averaged modified periodogram (linear
detrending, 50% overlap and Hamming windowing, Matlab, MathWorks,
Inc., MA). The frequency resolution was set at 0.25 Hz, with a frequency
range up to 30 Hz analyzed. Spectral power density of 4 frequency
bands was averaged in accordance with International Federation of
Clinical Neurophysiology digital standards (Nuwer et al. 1998; Cantero
et al. 2003); delta (0.5--3.0 Hz), theta (4.0--7.0 Hz), alpha (9.0--13.0 Hz),
and beta (16.0--30.0 Hz).
Memory Recognition Performance (d#)
There was a significant overall 3-way ANOVA interaction
between Group (Nap, No-Nap) 3 Memory Type (emotional,
neutral) 3 Memory Age (4 h, 15 min); (ANOVA F3,28= 4.49, P =
0.006). There was no main effect of Group ([Nap, No-Nap];
ANOVA F1,29= 1.46, P = 0.24) nor a main effect of Memory Age
([4 h, 15 min]; ANOVA F1,29= 1.56, P = 0.22). However, and in
accordance with our hypothesis, there was a selective offline
sleep facilitation of emotional memory (Fig. 2A), as demon-
strated by a significant Group [Nap, No-Nap] x Memory Age
[4 h, 15 min] interaction ANOVA (F1,29 = 4.33, P = 0.04).
Specifically, in the Nap group, there was superior retention of
emotional items studied 4 h prior to testing (which passed
through the brain-state of sleep) compared with items studied
15 min prior to testing (paired t-test, t(14) = 2.49, P = 0.02).
This significant offline benefit was also evident when quantified
as the subtracted difference in recognition memory ([4 h
memory retention--15 min memory retention]; Fig. 2B). In
marked contrast, no such evidence of an offline emotional
memory benefit was observed in the No-Nap group, with
recognition performance for items from the 4 h and 15 min
study sessions being nearly identical (paired t-test, t(15) = 0.57,
P = 0.58; Fig. 2A,B). Data values for group HR and Correct
Rejection values, forming the basis for the d# scores, are
described in Table 1, with HR similarly showing only a selective
retention benefit foremotional
4 h relative to 15 min in the Nap group (t-test, t(15) = 2.40,
P = 0.03), and not in the No-Nap group (t-test, t(15) = 0.25,
P = 0.80).
Unlike the differential group profiles of offline memory
change for emotional stimuli, there was no significant interaction
observed between the 2 groups, and across time, for neutral
items (Group [Nap, No-Nap] 3 Memory Age [4 h, 15 min]
interaction ANOVA (F1,29= 0.02, P = 0.88; Fig. 3A,B). There was
also no main effect of either Group or Memory Age (ANOVA,
both F1,29< 0.79, P > 0.38). Within-group comparisons further
confirmed this lack of difference between the 4 h and 15 min
offline retention periods for neutral memory in the Nap group
(paired t-test, t(14) = 0.22, P = 0.83) and No-Nap group (paired
t-test, t(15) = 0.03, P = 0.97).
Response times for the 15-min and 4-h study sessions, as well
as for the recognition test sessions, are provided in Tables 2 and
3, and demonstrated no significant differences between groups.
Therefore, a selective offline consolidation benefit for emo-
tional memory was observed in the Nap group; a difference
that was not observed across the simple passage of time, as
items studied at
Figure 2. (A) Recognition memory score (d#) for emotional items studied 4 h or 15 min prior to the test session in the No-Nap and Nap groups. (B) The difference in recognition
memory between the 4-h and 15-min study sessions (4 h score--15 min score) for the No-Nap and Nap groups (i.e., the offline consolidation difference for items studied 4 h vs.
15 min prior to the recognition test). *P \ 0.05; n.s., nonsignificant. Error bars represent standard error of the mean.
Role of REM Sleep in the Consolidation of Emotional Human Memories
Nishida et al.
evidenced by the lack of performance difference for emotional
memory in the No-Nap group. Furthermore, this nap-related
improvement was only observed for emotional and not neutral
It is conceivable that the observed consolidation benefit was
dependent on the brain-state of sleep occurring immediately
following learning (i.e., the sleep period occurring soon after
the first (4 h) study session in the Nap group). To investigate
whether this same sleep-dependent emotion memory effect
would occur following a more prolonged postlearning delay,
a second experiment was performed in an addition group of
subjects (n = 17; 8 males, mean age 22.9 [SD ± 1.4]; screened as
described above). Subjects performed 4 study sessions using
the same task parameters and stimulus set (60 slides at each
study session; half emotional half neutral) across 3 days: 1 PM
day-1 (48 h prior to testing), 1 PM day-2 (24 h prior to testing),
1 PM day-3 (4 h prior to testing) and 5 PM day-3; 15 min prior
to recognition testing at 5:15 PM. Thus, subjects learned the
same total number of picture slides to those in the Nap and No-
Nap groups, except learning occurred across 4 rather than 2
sessions, with 2 of the learned picture sets passing through an
offline consolidation period containing sleep prior to testing
(48- and 24-h study sets), whereas 2 of the picture sets did not
experience sleep in the offline time before testing (4-h and 15-
min study sets). Importantly, the 2 sets of learned information
that did pass through sleep did so many hours after learning (1
PM on each day; an average of 10.5-h postlearning, based on
sleep logs). These data, provided in Supplemental Figure 1,
again demonstrated a specific offline advantage for the
retention of emotional memory following periods of sleep
(either across one or 2 nights), and that this benefit was evident
even when the proximity of learning to the onset of sleep was
delayed by many hours. Thus, the facilitation of emotional
memory observed in the Nap group appears to be related to the
presence of sleep, independent of its proximal relationship to
the initial study session.
To further examine the relationship between the emotional
memory benefit and our experimental REM-sleep hypothesis,
sleep-stage values were correlated with the offline difference in
emotional recognition memory ([4 h retention--15 min re-
tention]; that is, the values represented in Fig. 2B, filled bar) in
the Nap group. Sleep-stage amounts are summarized in Table 4.
Of the 15 subjects, 13 achieved REM sleep. As demonstrated in
Figure 4, and in accordance with our hypothesis, there was
a significant positive relationship between the offline emotional
memory benefit and the amount of REM sleep obtained across
subjects, both REM percent (R = 0.63, P < 0.03) and REM
minutes (R = 0.52, P < 0.05). Furthermore, there was a strong
inverse relationship between the offline emotional memory
benefit and REM latency (R = --0.64, P < 0.03); indicating that
the faster subjects entered REM sleep (shorter latency to REM),
the greater the emotional memory advantage. It should be
noted, however, that these correlations narrowly missed
significance when corrected for multiple comparisons at the
most conservative Bonferroni threshold (P = 0.016).
This latter REM latency association alone did not, however,
differentiate whether it is the time to achieve REM following
the onset of sleep, or the time it takes to achieve REM sleep
following the completion of memory encoding, which includes
time spent awake prior to the onset of sleep. We therefore
correlated total time from the end of the 4 h encoding session
with the extent of emotional memory improvement (i.e., time
awake + REM latency). This analysis revealed a lower and
nonsignificant association (R = 0.35, P = 0.20), suggesting that
the emotional consolidation ‘‘demand’’ for REM begins upon
the initiation of sleep, rather than upon the completion of
encoding. Future studies with greater power will be required
to fully dissect this observed effect.
We further investigated whether the 2 subjects that did not
achieve REM sleep would conform to these correlation
distributions by assigning them a zero percent REM amount,
and a 90-min REM latency (the duration of the nap
opportunity). These REM-absent subjects expressed little
offline emotional memory change across the nap, fitting the
predictive distributions (Fig. 4A,B). Furthermore, with these
subjects added, the strength of the respective correlations only
increased (REM amount R = 0.61, P < 0.03; REM latency R =
–0.63, P < 0.01).
No relationships were evident between the offline improve-
ment in emotional memory and other sleep stages (stage 2, SWS
or total sleep time; all P > 0.23, although insufficient variation
in total sleep time may have precluded adequate correlative
power for the measure of total sleep time). No significant
associations were observed between the offline difference in
neutral memory and any sleep parameter (all P > 0.54).
Rather than the nap affording an offline consolidation
benefit, an alternative explanation is that sleep confers a
detrimental postnap effect on encoding ability at the 15-min
study session, artificially inflating the difference between 4-h
and 15-min test performance. This would appear unlikely
considering that emotional recognition memory performance
(d#) at 15 min in the Nap group was not significantly different
to that of the No-Nap group (P = 0.12), and was similarly true
for the alternative recognition memory measure of HR (P =
0.69; Figs 2A, 3A and Table 1). Nevertheless, to explore this
possibility, we correlated absolute emotional recognition
memory performance for items studied at the 15-min session
(rather than the subtracted difference between 15-min and 4-h
performance) with sleep measures; an analysis which, accord-
ing to the above alternative hypothesis, would predict negative
relationships. No evidence for such a relationship between
prior sleep and recognition memory performance for items
studied at the 15 min session was apparent (stage 2, SWS or
REM; all P >0.18—also note that none of the correlations were
in the negative direction). Therefore, a selective offline
emotional memory benefit was expressed in the Nap group;
the extent of which was strongly correlated with both the
Memory performance in the Nap and No-Nap Group—proportion correct (HR) as a function of
study time prior to testing, together with proportion of false alarms (FA rate)
Note: Corresponding discrimination index (d#) for each category is displayed in Figures 2 and 3.
Cerebral Cortex May 2009, V 19 N 5 1161
amount of REM sleep obtained during the nap, and the speed of
entry into REM sleep.
Spectral EEG Analyses
We finally sought to determine whether unique electrophys-
iological oscillations during REM were as, if not more, accurate
in predicting the amount of emotional memory consolidation.
We focused a priori on REM-sleep theta-band activity (4.0--7.0
Hz) because of the emerging relationship between affective
memory processing and theta oscillations in limbic and
prefrontal regions (Pare et al. 2002; Jones and Wilson 2005).
Based on the right prefrontal-dominant representation of
object versus verbal episodic declarative memory (Tulving
et al. 1994; Kelley et al. 1998; Wagner et al. 1998; McDermott
et al. 1999), we explored local electrophysiological signatures
associated with the relative activity difference between the left
versus right-frontal regions (activity at electrode F4 subtracted
from that at F3, or [F4 – F3]); representing a specific local
measure of sleep oscillatory activity within subjects (Huber
et al. 2004; Nishida and Walker 2007).
The extent of right-lateralized prefrontal theta activity ([F4 –
F3]) demonstrated a significant and positive correlation with
the offline emotional memory benefit (Fig. 5A ; R = 0.61, P <
0.03, but did not reach the conservative Bonferroni corrected
threshold for multiple comparisons; P = 0.013). Indeed, this
right-sided association between theta power and emotional
memory improvement was also evident when examining each
electrode independently (see Supplemental Figs 2 and 3). The
theta correlation was not observed at central electrode sites
([C4 – C3] or either electrode by themselves; all P > 0.20). No
other frequency band at frontal (or central) regions correlated
with the extent of offline improvement in emotional memory
(all P > 0.15), and no association between REM-sleep theta
power was observed with the offline change in neutral memory
at frontal or central regions (all P > 0.14).
Figure 3. (A) Recognition memory score (d#) for neutral items studied 4 h or 15 min prior to the test session in the No-Nap and Nap groups. (B) The difference in recognition
memory between the 4-h and 15-min study sessions [4 h score--15 min score] for the No-Nap and Nap group (i.e., the offline consolidation difference for items studied 4 h vs. 15
min prior to the recognition test). n.s., nonsignificant. Error bars represent standard error of the mean.
Mean reaction times (ms) across different memory categories in the No-Nap and Nap groups for
the 4-h and 15-min study sessions, respectively
Study session (4 h) Study session (15 min)
Emotional NeutralEmotional Neutral
Note: There were no significant differences in reaction time between the 2 groups for any
response type, for either emotional or neutral stimuli (all P [ 0.36).
Mean reaction times (ms) across different memory categories and response types in the No-Nap
and Nap groups at recognition testing
Note: There were no significant differences in reaction times between the 2 groups for any
response type, for either emotional or neutral stimuli (all P [ 0.11).
Nap sleep-stage time (min) and percentage in the nap group (mean ± SEM)
Sleep time (min) Percentage
Total nap time
83.27 ± 4.18
10.92 ± 6.07
59.80 ± 4.76
11.06 ± 3.21
18.18 ± 2.55
14.33 ± 1.92
29.45 ± 3.25
43.78 ± 4.31
10.24 ± 1.77
12.56 ± 4.69
21.77 ± 3.03
17.42 ± 2.85
36.53 ± 4.41
53.95 ± 6.24
11.72 ± 1.99
Role of REM Sleep in the Consolidation of Emotional Human Memories
Nishida et al.
To further examine whether these broad EEG bands may
have been obscuring more discrete spectral frequency corre-
lations outside of the theta range, we performed a fine-grained
separation of the spectrum in 0.5-Hz interval bins. However, as
shown in Figure 5B, only frequency bins in the theta spectrum
displayed significant correlations with the extent of emotional
consolidation, many of which remaining significant following
Bonferroni correction (threshold P = 0.001; see Supplemental
Fig. 3 for individual electrode data).
Using a nap paradigm, here we demonstrate the selective
offline benefit of sleep on the consolidation of negative
emotional memories. Furthermore, this offline emotional
memory advantage correlated with the amount of REM sleep,
and specifically the extent of right-dominant prefrontal theta
power during REM.
An established literature demonstrates that memory pro-
cessing can be modulated by the emotional strength of the
material being learned (for reviews, see McGaugh 2004). These
studies show that memories associated with the evocation of
emotion persist more strongly than memories lacking affective
tone (LaBar and Phelps 1998; Cahill 2000; Kensinger 2004;
McGaugh 2004; Phelps 2004). Most relevant, the effects of
emotion on memory retention are known to paradoxically
increase as the delay between encoding and retrieval increases
(hours/days) (Kleinsmith and Kaplan 1963; Walker and Tarte
1963; Levonian 1972; LaBar and Phelps 1998; Sharot and Phelps
To date, a number of studies have investigated the
interaction between offline time and sleep on affective memory
consolidation. For example, Hu et al. (2006) compared the
offline consolidation of emotionally arousing and nonarousing
picture-stimuli following a 12 h period across the day or across
a night containing sleep. A selective emotional memory benefit
was observed only across a night containing sleep and not
simply across the simple passage of time, as evidenced by
inferior neutral and emotional memory performance across
the day. Wagner and colleagues (Wagner et al. 2001) have also
shown that sleep selectively favors the retention of previously
learned emotional texts relative to neutral texts, and that this
affective memory benefit is only present following late-night
Figure 4. Correlation between the amount of offline emotional memory benefit in the Nap group (i.e. the d# difference expressed in Fig. 2B) and (A) REM-sleep amount (%), and
(B) Speed of entry into REM sleep (REM latency, in minutes). Filled circles represent all subjects that achieved REM sleep during the nap. Gray circles represent subjects that did
not achieve REM during the nap, and were assigned a 90-min REM latency. Person’s r-value and significance (P) displayed in figures, with statistical values and regression lines
pertaining only to subjects that achieved REM.
Figure 5. (A) Correlation strength (Person’s r-value) between offline benefit for emotional memory in the Nap group (i.e., the d# benefit expressed in Fig. 2B) and the relative
right versus left prefrontal spectral-band power ([F4 ? F3]), illustrating a significant positive correlation in the theta-band range with the extent of offline emotional memory
consolidation (R 5 0.61, P 5 0.03), (B) a more fine-grained analysis of this same correlation for incremental power spectrum densities within each band, expressed in average
0.5-Hz bins. Correlation strength is represented by the color range, demonstrating significant correlations within the Theta frequency band, and (C) exhibiting a maximum
significance at the 5.75-Hz bin, displayed on right figure panel.
Cerebral Cortex May 2009, V 19 N 5 1163
sleep (a time period rich in stage-2 NREM and REM sleep), an
effect that can persist for several years (Wagner et al. 2006).
Most recently, it has been shown that sleep preferentially and
selectively consolidates emotional objects embedded within
a scene, rather than the image as a whole (Payne et al. in press).
Here we similarly describe an offline sleep benefit for
emotional memory consolidation but also demonstrate that this
effect is evident even following an interval containing a short
(90 min) sleep epoch, relative to an equivalent time period
awake. Importantly, this effect is revealed when comparing
memory performance at identical circadian study-test time
points. An alternative explanation for these offline improve-
ments could be attributed to interference from continued
waking activities in the No-Nap group, not present during the
sleep period in the Nap group, resulting in a passive rather than
proactive sleep-state favoring consolidation. However, we find
this explanation to be unlikely for several reasons. The lack of
interference in the Nap group should result in global
consolidation benefits for both emotional and neutral memory
categories. Contrary, the sleep benefit was only seen for
emotional stimuli. Indeed, one may predict that affective
stimuli, being more emotional and potent, should be less
susceptible to interference across the day, and result in more
similar consolidation benefits to those observed in the No-Nap
group. Instead, the opposite was found. Furthermore, the
advantage in emotional memory was not proportional to total
sleep duration (indexing the total interference-free time in the
Nap group), but instead, with a specific type of sleep (REM;
incidentally, the stage associated with the greatest amount of
potentially interfering mental activity (Hobson and Pace-Schott
2002). Most compelling, however, was that the emotional
memory benefit correlated with a specific electrophysiological
oscillation, strongly suggesting an active mechanistic role for
sleep in consolidation (and not simply a passive state, lacking
The current findings go beyond demonstrating that emo-
tional memory is preferentially modulated across periods of
sleep, and to our knowledge, provide the first demonstration
that the extent of emotional memory consolidation is
associated with REM-sleep characteristics—both amount and
speed of entry. Importantly, this REM relationship was specific
to emotional memory with no detectable relationship observed
for neutral memory. Furthermore, the emotional memory
benefit was selective to REM, with no other sleep-stage
measure demonstrating an association with offline perfor-
Corroborating these correlations, it has previously been
hypothesized that REM sleep represents a brain-state particu-
larly amenable to emotional memory consolidation, based on its
unique biology (Pare et al. 2002; Hu et al. 2006). Neurochemi-
cally, levels of limbic and forebrain ACh are markedly elevated
during REM (Vazquez and Baghdoyan 2001), reportedly
quadruple those seen during NREM and double those measured
in quite waking (Marrosu et al. 1995). Considering the known
importance of ACh in the long-term consolidation of emotional
learning (McGaugh 2004), this procholinergic REM state may
result in a selective memory facilitation of affective memories,
similar to that reported using experimental manipulations of
ACh (Power 2004). Moreover, by processing such memories in
a brain-state that is largely devoid of aminergic tone (Pace-
Schott and Hobson 2002), particularly noradrenergic input
from the locus coeruleus, the modulation of negative emotional
experiences during REM may help depotentiate and ultimately
ameliorate the autonomic charge originally acquired at the
time of learning, negating a long-term state of chronic anxiety.
Neurophysiologically, these alterations may be reflected in
(or caused by) changes of synchronized oscillatory activity
between limbic (including amygdala and hippocampal) and
neocortical regions during REM sleep (Pare et al. 2002; Jones
and Wilson 2005). Cooperation between these structures plays
a role in the modulation of affective experiences (Pare et al.
2002), leading to the possibility that synchronous activity
within these networks during REM sleep may modulate plastic
changes essential to emotional memory consolidation. Compli-
mentary to such a model, it has also been demonstrated that
learning and later successful recollection of human emotional
episodic memories rely on interactions between the hippo-
campus and amygdala—the degree to which accurately
predicts the extent of latent memory retention (Kilpatrick
and Cahill 2003; Dolcos et al. 2004; Dolcos et al. 2005).
Here we demonstrate that the offline facilitation of
emotional memory is not simply correlated with the amount
and latency of REM sleep, but specifically with an electrophys-
iological signature of REM sleep—spectral activity in the theta-
band range. Furthermore, this relationship was topographically
organized, with the biased extent of right-dominant theta
power being most predictive of the amount of emotional
memory improvement, a relationship consistent with the right-
sided anatomical distribution of object (vs. verbal) memory
(Kelley et al. 1998; Wagner et al. 1998; McDermott et al. 1999)
and also the right-frontal dominant relationship with negative
affective processing (Davidson 2002). Although the functional
association between emotional memory and REM-sleep elec-
trophysiology remains unclear, coordinated theta oscillations
have been proposed to constitute a mechanism allowing
disparate brain regions that initially encoded information to
selectively interact offline, in a coupled relationship, and by
doing so, promote the strengthening of specific memory
representations across distributed networks (Buzsaki 2002;
Jones and Wilson 2005). It is therefore interesting to speculate
whether surface EEG theta correlations observed in the current
study, complimentary to those recorded at a cellular level
(Jones and Wilson 2005), may represent the large-scale
cooperation between connected subcortical limbic structures
and prefrontal regions (Sotres-Bayon et al. 2004; Jones and
Wilson 2005), the extent of which predicts the amount of
offline emotional memory processing and postsleep benefit.
It should be noted, however, that theta activity is not
exclusive to REM sleep, and has been observed during periods
of sleep--wake transition as well as during quite wakefulness
(e.g., Cantero et al. 2003). We did not record EEG activity in the
no-nap group, and therefore do not have an index of theta
activity during wakefulness in these participants. Although it is
likely that an amount of theta activity will have been present, it
does not appear to benefit emotional memory consolidation in
a similar manner to that observed during REM, because no
emotional memory advantage was observed in those that
remained awake. Therefore, although these findings in no way
dismiss the possibility that theta activity may be present across
brain-states, they do suggest that theta activity, in combination
with the REM-sleep state, preferentially facilitates emotional
Although neutral memory was not enhanced following the
nap, we are not suggesting that nonemotional declarative
Role of REM Sleep in the Consolidation of Emotional Human Memories
Nishida et al.
memories do not benefit from sleep. There is now substantial
evidence indicating that a full night of nocturnal sleep
modulates emotion-free declarative memories, and is most
commonly associated with NREM SWS characteristics (Marshall
and Born 2007). Furthermore, our current study focused
principally on a short epoch of sleep (but see data in
Supplemental Fig. 1), which, although containing NREM SWS,
may not have been sufficient to trigger robust neutral memory
In the broader context, this REM-sleep modulation of
negative aversive memories may hold implications for the
mechanistic understanding and treatment of mood disorders,
including major depression. Depression is commonly associ-
ated with alterations in REM sleep, including a faster pro-
gression into REM (reduced REM latency) and an increase in
the amount of REM (Tsuno et al. 2005; Armitage 2007).
Considering the REM association with negative emotional
memory reported here, such REM abnormalities in depression
may represent a maladaptive consolidation process of prior
negative affective experiences, which, due to the increased
REM amount and faster speed of entry into REM, could
selectively and disproportionately reinforce negative memories
at night, thereby potentiating the mood disorder. Likewise,
post-traumatic stress disorder (PTSD) is also associated with
a dysregulation of REM sleep, with reports of increased
sympathetic autonomic tone (Harvey et al. 2003; Mellman
and Hipolito 2006). There may similarly be an adverse
consequence to such trauma-induced REM-sleep changes in
PTSD, which if they persist, could counter-productively
amplify, rather than ameliorate, the acquired affective experi-
ence. Such basic research findings may help the growing
translational appreciation of the interaction between affective
mood disorders and sleep physiology.
material can befound at:http://www.cercor.
National Institutes of Health (MH069935); the Howard Hughes
Medical Institute; and the American Academy of Sleep
Medicine. Funding to pay the Open Access publication charges
for this article were provided by The Berkeley Research Impact
We wish to thank Jose L. Cantero and Elizabeth Kensinger for guidance
and thoughtful insights. Conflict of Interest: None declared.
Address correspondence to Matthew P. Walker, PhD, Department of
Psychology, Tolman Hall 3331, University of California, Berkeley, CA
94720-1650, USA. Email: firstname.lastname@example.org.
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