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Diekelmann S, Born J. The memory function of sleep. Nat Rev Neurosci 11: 114-126


Abstract and Figures

Sleep has been identified as a state that optimizes the consolidation of newly acquired information in memory, depending on the specific conditions of learning and the timing of sleep. Consolidation during sleep promotes both quantitative and qualitative changes of memory representations. Through specific patterns of neuromodulatory activity and electric field potential oscillations, slow-wave sleep (SWS) and rapid eye movement (REM) sleep support system consolidation and synaptic consolidation, respectively. During SWS, slow oscillations, spindles and ripples - at minimum cholinergic activity - coordinate the re-activation and redistribution of hippocampus-dependent memories to neocortical sites, whereas during REM sleep, local increases in plasticity-related immediate-early gene activity - at high cholinergic and theta activity - might favour the subsequent synaptic consolidation of memories in the cortex.
| Memory re-activation during slow wave sleep (sWs). a | In awake rats running on a circular track (Run), neurons in the sensory cortex and hippocampus fire in a characteristic sequential pattern. Each row represents an individual cell and each mark in the upper parts of the diagrams indicates a spike; the curves in the lower parts indicate the respective average firing patterns of the cells. During subsequent slow wave sleep (SWS) (Sleep), temporal firing sequences observed in the cell assemblies during running re-appear both in the cortex and in the hippocampus 72 . b | Human subjects learned a two-dimensional object location task on a computer while an odour was presented as a context stimulus. Re-exposure to the odour specifically during subsequent SWS enhanced retention performance (recalled card locations) when tested the next day. There was no enhancement in retention when no association was formed between object locations and odour (that is, odour presentation during SWS but not during learning) or when odour re-exposure occurred during rapid eye movement (REM) sleep or waking 15 . c | When participants slept in an fMRI scanner after learning in the presence of odour, re-exposure to the odour during SWS activated the left anterior hippocampus (left) and neocortical regions like the retrosplenial cortex (right), which was not observed without odour presentation during prior learning 7 . Part a is modified, with permission, from Ref. 72 © 2007 Macmillan Publishers Ltd. All rights reserved; part b is modified, with permission, from Ref. 15 © 2007 American Association for the Advancement of Science; part c modified, with permission, from Ref. 7 © 2007 Elsevier.
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Although sleep is a systems-level process that affects
the whole organism, its most distinctive features are the
loss of behavioural control and consciousness. Among
the multiple functions of sleep1, its role in the establish-
ment of memories seems to be particularly important:
as it seems to be incompatible with the brain’s normal
processing of stimuli during waking, it might explain the
loss of consciousness in sleep. Sleep promotes primarily
the consolidation of memory, whereas memory encoding
and retrieval take place most effectively during waking.
Consolidation refers to a process that transforms new
and initially labile memories encoded in the awake state
into more stable representations that become integrated
into the network of pre-existing long-term memories.
Consolidation involves the active re-processing of ‘fresh
memories within the neuronal networks that were used
for encoding them. It seems to occur most effectively
off-line, i.e. during sleep, so that encoding and consoli-
dation cannot disturb each other and the brain does not
‘hallucinate’ during consolidation2.
The hypothesis that sleep favours memory consolida-
tion has been around for a long time3. Recent research
in this field has provided important insights into the
underlying mechanisms through which sleep serves
memory consolidation4–7. In this Review, we first discuss
findings from behavioural studies regarding the specific
conditions that determine the access of a freshly encoded
memory to sleep-dependent consolidation, and regard-
ing the way in which sleep quantitatively and qualitatively
changes new memory representations. We then consider
the role of slow-wave sleep (SWS) and rapid eye move-
ment (REM) sleep in memory consolidation (BOX 1). We
finish by comparing two hypotheses that might explain
sleep-dependent memory consolidation on a mechanis-
tic level, that is, the synaptic homeostasis hypothesis and
the active system consolidation hypothesis.
Behavioural studies
Numerous studies have confirmed the beneficial effect
of sleep on declarative and procedural memory in various
tasks8–10, with practically no evidence for the opposite
effect (sleep promoting forgetting)11. Compared with a
wake interval of equal length, a period of post-learning
sleep enhances retention of declarative information3,1216
and improves performance in procedural skills13,17–24.
Sleep likewise supports the consolidation of emotional
information25–27. Effects of a 3-hour period of sleep on
emotional memory were even detectable 4 years later28.
However, the consolidating effect of sleep is not revealed
under all circumstances and seems to be associated with
specific conditions29 (see below).
Sleep duration and timing. Significant sleep benefits
on memory are observed after an 8-hour night of sleep,
but also after shorter naps of 1–2 hours14,19,23,30, and even
an ultra-short nap of 6 minutes can improve memory
retention16. However, longer sleep durations yield greater
improvements, particularly for procedural memo-
ries18,21,31. The optimal amount of sleep needed to benefit
memory and how this might generalize across species
showing different sleep durations is unclear at present.
Some data suggest that a short delay between
learning and sleep optimizes the benefits of sleep on
memory consolidation. For example, for declarative
University of Lübeck,
Department of
Haus 50, 2. OG, Ratzeburger
Allee 160, 23538 Lübeck,
Correspondence to J. B.
Published online
4 January 2010
Declarative memory
Memories that are accessible
to conscious recollection
including memories for facts
and episodes, for example,
learning vocabulary or
remembering events.
Declarative memories rely on
the hippocampus and
associated medial temporal
lobe structures, together with
neocortical regions for
long-term storage.
Procedural memory
Memories for skills that result
from repeated practice and
are not necessarily available
for conscious recollection, for
example, riding a bike or
playing the piano. Procedural
memories rely on the striatum
and cerebellum, although
recent studies indicate that the
hippocampus can also be
implicated in procedural learning.
The memory function of sleep
Susanne Diekelmann and Jan Born
Abstract | Sleep has been identified as a state that optimizes the consolidation of newly
acquired information in memory, depending on the specific conditions of learning and the
timing of sleep. Consolidation during sleep promotes both quantitative and qualitative
changes of memory representations. Through specific patterns of neuromodulatory activity
and electric field potential oscillations, slow-wave sleep (SWS) and rapid eye movement
(REM) sleep support system consolidation and synaptic consolidation, respectively. During
SWS, slow oscillations, spindles and ripples — at minimum cholinergic activity — coordinate
the re-activation and redistribution of hippocampus-dependent memories to neocortical
sites, whereas during REM sleep, local increases in plasticity-related immediate-early gene
activity — at high cholinergic and theta activity — might favour the subsequent synaptic
consolidation of memories in the cortex.
Nature Reviews Neuroscience
AOP, published online 4 January 2010; doi:10.1038/nrn2762
© 20 Macmillan Publishers Limited. All rights reserved10
REM sleep
Nature Reviews | Neuroscience
Slow oscillation Spindle Sharp wave-ripple PGO wave Theta activity
Field potential oscillations
Slow oscillations
Stage 4
Stage 3
Stage 2
Stage 1
23:00 0:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00
Late sleep
Early sleep
Acetylcholine Acetylcholine
Cortisol Cortisol
Field potential
Single cell
1 s
Serial reaction time task
A task in which subjects are
required to rapidly respond to
different spatial cues by
pressing corresponding
buttons. This task can be
performed implicitly (that is,
without knowledge that there is
a regularity underlying the
sequence of cue positions) or
explicitly (by informing the
subject about this underlying
information, sleep occurring 3 hours after learning
was more effective than sleep delayed by more than
10 hours32,33. However, these studies did not control for
the confounding effects of forgetting during the wake
interval before the onset of sleep. For optimal benefit
on procedural memory consolidation, sleep does not
need to occur immediately18,19 but should happen on
the same day as initial training17,22,24.
Explicit versus implicit encoding. Whether memories
gain access to sleep-dependent consolidation depends
on the conditions of encoding. Encoding of declara-
tive memories is typically explicit, whereas proce-
dural memory encoding can involve both implicit
and explicit processes. Most robust and reliable sleep-
dependent gains in speed have been revealed for the
finger sequence tapping task, which involves explicit
procedural memory17–19,24. For the serial reaction time
task (SRTT), which can be learnt implicitly or explicitly,
the sleep-induced speeding of performance was more
robust when people learnt the task explicitly than
after implicit learning34. These observations suggest
that explicit encoding of a memory favours access to
sleep-dependent consolidation.
The benefit of sleep is greater for memories formed
from explicitly encoded information that was more dif-
ficult to encode or that was only weakly encoded35,36, a n d
it is greater for memories that were behaviourally relevant.
Thus, sleep enhances the consolidation of memories for
intended future actions and plans (D. S., I. Wilhelm, U.
Wagner, J. B., unpublished observations). Notably, this
enhancement could be nullified by letting the subject
Box 1 | Sleep architecture and neurophysiological characteristics of sleep stages
Sleep is characterized by the cyclic occurrence of rapid
eye movement (REM) sleep and non-REM sleep, which
includes slow wave sleep (SWS, stages 3 and 4) and lighter
sleep stages 1 and 2 (see the figure, part a). In humans, the
first part of the night (early sleep) is characterized by high
amounts of SWS, whereas REM sleep prevails during the
second half (late sleep). SWS and REM sleep are
characterized by specific patterns of electrical field
potential oscillations (part b) and neuromodulator activity
(part c, BOX 3).
The most prominent field potential oscillations during SWS
are the slow oscillations, spindles and sharp wave-ripples,
whereas REM sleep is characterized by ponto-geniculo-
occipital (PGO) waves and theta activity. The slow oscillations
originate in the neocortex with a peak frequency (in humans)
of ~0.8 Hz130,164. They synchronize neuronal activity into
down-states of widespread hyperpolarization and neuronal
silence and subsequent up-states, which are associated with
depolarization and strongly increased, wake-like neuronal
firing132,165,166 (part d). The hyperpolarization results from
activation of a Ca2+-dependent K+ current and inactivation of
a persistent Na+ current, which dampens excitability165,167,168.
The depolarizing up-state might be triggered by summation
of miniature EPSPs (from residual activity from encoding
information) and is formed by activation of T-type Ca2+ and
persistent Na+ currents.
Spindle activity refers to regular electroencephalographic
oscillations of ~10–15 Hz, which are observed in human sleep
stage 2 as discrete waxing and waning spindles, but are present
at a similar level during SWS (although here they form less
discrete spindles)169. Spindles originate in the thalamus from an
interaction between GABAergic neurons of the nucleus
reticularis, which function as pacemakers, and glutamatergic
thalamo-cortical projections that mediate their synchronized
and widespread propagation to cortical regions132,168,169.
Hippocampal sharp waves are fast depolarizing events, generated in the CA3, on which
high-frequency oscillations (100–300 Hz) originating from an interaction between inhibitory
interneurons and pyramidal cells in CA1 (so-called ripples) are superimposed104,121. Sharp
wave-ripples occur during SWS and also during waking, and accompany the re-activation
of neuron ensembles that are active during a preceding wake experience70,71,121,122,170.
PGO-waves are driven by intense bursts of synchronized activity that propagate from the pontine
brainstem mainly to the lateral geniculate nucleus and visual cortex. They occur in temporal association
with REM in rats and cats but are not reliably identified in humans. Theta oscillations (4–8 Hz) hallmark
tonic REM sleep in rats and predominate in the hippocampus141. In humans, theta activity is less
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Implicit learning
Learning without being aware
that something is being
Explicit learning
Learning while being aware
that something is being
Memory systems
Different types of memory,
such as declarative and
non-declarative memory, are
thought to be mediated by
distinct neural systems, the
organization of which is still a
topic of debate.
execute the intended behaviour before sleep. Similarly,
subjects who had been trained on two different finger-
tapping sequences showed greater sleep-dependent gains
in performance for the sequence for which they expected
to be rewarded for optimal performance at re-testing after
sleep37. Thus, a motivational tagging of memories, which
probably relies on the function of the prefrontal cortex38,
might signal behavioural effort and relevance and mediate
the preferential consolidation of these memories.
In summary, a great number of studies indicate that
sleep supports the consolidation of memory in all major
memory systems, but preferentially those that are explicitly
encoded and that have behavioural relevance to the indi-
vidual. There is growing evidence that explicit encoding,
even in procedural tasks, involves a dialogue between
the prefrontal cortex and the hippocampus38–40, which
also integrates intentional and motivational aspects of
the task. Activity of this circuit may be crucial in mak-
ing a memory susceptible to sleep-dependent memory
Sleep changes memory representations quantitatively
and qualitatively. Consolidation of memory during
sleep can produce a strengthening of associations as
well as qualitative changes in memory representations.
Strengthening of a memory behaviourally expresses itself
as resistance to interference from another similar task
(‘stabilization’) and as an improvement of performance
(‘enhancement’) that occurs at re-testing, in the absence
of additional practice during the retention interval.
The stabilizing effects of sleep have been observed in
declarative41 and procedural19 memory tasks. Similarly,
enhancements in performance after sleep have been
shown for declarative information13,14,20 and in proce-
dural tasks13,17,18,21,22,31. However, it is still controversial
to what extent these improvements reflect actual per-
formance ‘gains’ induced by sleep, because the measured
gains depend on the pre-sleep performance used as a
reference, which itself can be subject to rapid changes
after training42,43.
There is a long-standing debate about whether sleep
passively protects memories from decay and interfer-
ence or actively consolidates fresh memory represen-
tations44 (for a review see REF. 45). Importantly, a lack
of enhancement of memory performance after sleep
does not preclude an active role of sleep in memory
consolidation. There is strong evidence for an active con-
solidating influence of sleep from behavioural studies,
which indicate that sleep can lead to qualitative changes
in memory46–48. For example, in one study, subjects
learned single relations between different objects which,
unknown to the subject, relied on an embedded hierar-
chy47. When learning was followed by sleep, subjects at a
re-test were better at inferring the relationship between
the most distant objects, which had not been learned
before. Likewise, after sleep subjects more easily solved
a logical calculus problem that they were unable to solve
before sleep or after corresponding intervals of wakeful-
ness46. Of note, sleep facilitated the gain of insight into
the problem only if adequate encoding of the task was
ensured before sleep.
Interacting or competing memory systems? The behav-
ioural findings described above show that sleep can
‘re-organize’ newly encoded memory representations,
enabling the generation of new associations and the
extraction of invariant features from complex stimuli,
and thereby eventually easing novel inferences and
insights. Re-organization of memory representations
during sleep also promotes the transformation of
implicit into explicit knowledge, as was shown in an
SRTT which was implicitly trained but in which explicit
knowledge about the underlying sequence was exam-
ined during the re-test48. Following post-training sleep,
subjects were better at explicitly generating the SRTT
sequence. Interestingly, subjects who developed explicit
sequence knowledge no longer showed the improve-
ment in implicit procedural skill (that is, faster reaction
times) that is normally observed after sleep, suggesting
that procedural and declarative memory systems interact
during sleep-dependent consolidation.
Contrasting with this view of interacting memory
systems, it has also been proposed that disengagement
of memory systems is an essential characteristic of sleep-
dependent consolidation49. This idea derives mainly
from experiments showing that declarative learning of
words immediately after training of a procedural skill
can block off-line improvement in that skill if the subject
does not sleep between learning and re-testing, but not if
the subject sleeps between learning and re-testing50. This
suggests that memory systems compete and reciprocally
interfere during waking, but disengage during sleep,
allowing for the independent consolidation of memories
in different systems. The two views might be reconciled
by assuming a sequential contribution of interaction and
disengagement processes to consolidation, which might
be associated with different sleep stages (REM sleep and
SWS), as discussed below.
Influence of sleep stages on consolidation
Early studies in rats and humans investigating whether
different sleep stages have different roles in memory
consolidation mainly focused on REM sleep and the
consequences of REM sleep deprivation (REMD) by
repeatedly waking subjects at the first signs of REM
sleep. However, this approach is of limited value for logi-
cal reasons and because the repeated awakenings cause
stress, which itself influences memory function51,52.
Overall, these studies have provided mixed results52–55.
Of note is a recent study showing that pharmacologi-
cal suppression of REM sleep by administration of anti-
depressant drugs (selective noradrenaline or serotonin
re-uptake inhibitors) did not impair consolidation of
procedural memory56, which is in agreement with clini-
cal observations that antidepressant treatment does not
affect memory function57. However, such substances also
exert direct effects on synaptic plasticity and synaptic
forms of consolidation that could compensate for a loss
of REM sleep58.
Some studies performed in rats showed that REMD
is only effective during specific periods after learning
— the so-called ‘REM sleep windows’54. During post-
learning sleep, increases in the amount and intensity
© 20 Macmillan Publishers Limited. All rights reserved10
Transitory sleep
Short transitory periods of
sleep in rats that, based on
EEG criteria, can neither be
classified as REM sleep or
of REM sleep occur several hours or even days after
learning, depending on the kind of task and amount of
initial training54, and memory is particularly impaired if
REMD coincides with these periods. Of note, the mem-
ory tasks used in rats are typically emotionally loaded. As
there is evidence that REM sleep preferentially benefits
the consolidation of emotional aspects of a memory25,27,
this could partly account for the strong REMD effect
observed in many animal studies53,55.
Studies in humans have compared the effects on
consolidation between sleep periods with different
proportions of SWS and REM sleep. In humans, SWS
and REM sleep dominate the early and late part of noc-
turnal sleep, respectively (BOX 1). SWS-rich, early sleep
consistently benefits the consolidation of declarative
memories12,13,59, whereas REM-rich sleep benefits non-
declarative types of memory (that is, procedural and
emotional aspects of memory)13,25,59. These results are con-
sistent with the ‘dual-process hypothesis’, which assumes
that SWS facilitates declarative, hippocampus-depend-
ent memory and REM sleep supports non-declarative,
hippocampus-independent memory6.
Other studies have shown that SWS can also
improve procedural skill (that is, non-declarative)
memories31,60,61 and that REM sleep can also improve
declarative memory62,63. Although these divergent find-
ings could reflect that stimuli used in memory tasks are
often not of one type of memory system, they agree
with the ‘sequential hypothesis, which argues that the
optimum benefits of sleep on the consolidation of both
declarative and non-declarative memory occur when
SWS and REM sleep take place in succession31,64. Thus,
overnight improvements in visual texture discrimina-
tion correlated with both the amount of SWS in the
first quarter of sleep and the amount of REM sleep in
the last quarter21. Texture discrimination also improved
following a short midday nap of 60–90 minutes con-
taining solely SWS, but more so if the nap included
both SWS and REM sleep23. Also, memory consolida-
tion seems to be impaired by disruptions of the natural
SWS–REM sleep cycle that left the time spent in these
sleep stages unchanged65.
Intermediate sleep stages (non-REM sleep stage 2 in
humans, transitory sleep in rats) can also contribute to
memory consolidation66,67. For example, pharmaco-
logical suppression of REM sleep in humans produced
an unexpected overnight improvement in procedural
skill that was correlated with increased non-REM sleep
stage 2 spindle activity (see below)56. Such findings high-
light the fact that it is not a particular sleep stage per se
that mediates memory consolidation, but rather the
neuro physiological mechanisms associated with those
sleep stages, and that some of these mechanisms are
shared by different sleep stages.
Core features of off-line consolidation
Since the publication of Hebbs seminal book68, memory
formation has been conceptualized as a process in which
neuronal activity reverberating in specific circuits pro-
motes enduring synaptic changes. Building on this, it is
widely accepted that the consolidation process that takes
place off-line after encoding relies on the re-activation
of neuronal circuits that were implicated in the encod-
ing of the information. This would promote both the
gradual redistribution and re-organization of memory
representations to sites for long-term storage (that is,
system consolidation; BOX 2) and the enduring synaptic
changes that are necessary to stabilize memories (syn-
aptic consolidation). The conditions that enable these
two processes during sleep differ strongly between SWS
and REM sleep.
Re-activation of memory traces during sleep. The finding
that in rats the spatio-temporal patterns of neuronal
firing that occur in the hippocampus during explora-
tion of a novel environment or simple spatial tasks are
re-activated in the same order during subsequent sleep
was an important breakthrough in memory research69–74
(FIG. 1a, see REF. 75 for methodological considerations
on the identification of neuronal re-activations). Such
neuronal re-activation of ensemble activity mostly
occurs during SWS (it is rarely observed during REM
sleep76,77) and during the first hours after learning (but
see REF. 78), and typically only in a minority of recorded
neurons69–74. Moreover, unlike re-activations that occur
during wakefulness, re-activations during SWS almost
always occur in the order in which they were expe-
rienced79. Compared with activity during encoding
phases, re-activations during SWS seem to be noisier,
less accurate and often happen at a faster firing rate71.
They are also observed in the thalamus, the striatum
and the neocortex72–74,78. Sleep-dependent signs of re-
activation in brain regions implicated in prior learning
were also shown in human neuroimaging studies80,81.
The first evidence for a causal role of re-activation
during SWS in memory consolidation came from a study
in humans learning spatial locations in the presence of an
odour15. Re-exposure to the odour during SWS, but not
REM sleep, enhanced the spatial memories (FIG. 1b) and
induced stronger hippocampal activation than during
wakefulness, indicating that during SWS hippocampal
networks are particularly sensitive to inputs that can
re-activate memories (FIG. 1c). It is assumed that the re-
activations during system consolidation stimulate the
redistribution of hippocampal memories to neocorti-
cal storage sites, although this has not been directly
demonstrated yet82,83.
Synaptic consolidation. In addition to system consoli-
dation (BOX 2), consolidation involves the strengthening
of memory representations at the synaptic level (syn-
aptic consolidation)84,85. Long-term potentiation (LTP)
is considered a key mechanism of synaptic consolida-
tion, but it is unclear whether memory re-activation
during sleep promotes the redistribution of memories
by inducing new LTP (at long-term storage sites not
involved at encoding) or whether re-activation merely
enhances the maintenance of LTP that was induced
during encoding.
LTP can be induced in the hippocampus during
REM sleep but less reliably so during SWS86. LTP induc-
tion in the hippocampus or neocortex during SWS is
© 20 Macmillan Publishers Limited. All rights reserved10
Nature Reviews | Neuroscience
Long-term store (slow learning)
Encoding Consolidation
Temporary store (fast learning)
Immediate early genes
Genes that encode
transcription factors that are
induced within minutes of
raised neuronal activity without
requiring a protein signal.
Immediate-early gene
activation is, therefore, used as
an indirect marker of neuronal
activation. The immediate
early genes Arc and Egr1
(zif268) are associated with
synaptic plasticity.
Hebbian plasticity
Refers to the functional
changes at synapses that
increase the efficacy of
synaptic transmission and
occurs when the presynaptic
neuron repeatedly and
persistently stimulates the
postsynaptic neuron.
Spike-time dependent
Refers to the functional
changes at synapses that alter
the efficacy of synaptic
transmission depending on the
relative timing of pre- and
postsynaptic firing (‘spiking’).
The synaptic connection is
strengthened if the presynaptic
neuron fires shortly before the
postsynaptic neuron, but is
weakened if the sequence of
firing is reversed. probably temporally restricted to the up-states of the
slow oscillation and its concurrent phenomena of rip-
ples and spindles87,88 (see BOX 1 and below). Indeed, in
neocortical slices, stimulation that mimicked neuronal
activity during SWS could induce long-term depression
(LTD)89 or LTP87 depending on the pattern of stimula-
tion (rhythmic bursts or spindle-like trains, respectively).
LTP maintenance in the rat hippocampus, but not in the
medial prefrontal cortex, was impaired if induction was
followed by REMD90. In humans, sleep strengthened
LTP-like plasticity that had been induced in the neocor-
tex by transcranial magnetic stimulation (TMS) prior
to sleeping91.
Globally (meaning measured in whole-brain or large
cortical samples) sleep suppresses the molecular sig-
nals that mediate LTP-related synaptic remodelling but
enhances LTD-related signalling, and this effect seems
to be mediated by SWS92–95. This observation, however,
does not preclude that LTP occurs during sleep (during
SWS or REM sleep) in specific regions, for example in
those that were engaged in memory encoding prior to
sleeping. In rats, both induction of hippocampal LTP
and exposure to a novel tactile experience during wak-
ing increased the expression of the plasticity-related
immediate early genes (IEGs) Arc and Egr1 (which are
implicated in LTP) during subsequent sleep, mainly in
cortical areas that were the most activated by the novel
experience, and this effect seemed to be mediated by
REM sleep96–98. Investigations in visual cortex in cats
and humans have demonstrated that sleep-dependent
plasticity depends on the activation of glutamatergic
NMDA (N-methyl--aspartate) receptors and associ-
ated cAMP-dependent protein kinase A (PKA), and
on AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazole
propionic acid) receptor activation, that is, the post-
synaptic machinery that is crucial for the induction and
maintenance of LTP99102. These findings indicate that
local, off-line re-activation of specific glutamatergic
circuits supports both LTP induction and maintenance,
and the molecular processes underlying synaptic con-
solidation. Moreover, these processes probably occur
preferentially during REM sleep, although they are
likely to be triggered by the re-activations that occur
during prior SWS (see below). Evidence about how LTP
induction and maintenance is linked to specific sleep
stages is presently scarce, but based on the available
data it is tempting to speculate that SWS supports the
re-activation of new memories (system consolidation)
and thus, could initialize LTP and prime the relevant
networks for synaptic consolidation during subsequent
REM sleep. This idea seems to be supported by elec-
troencephalographic (EEG) rhythms that characterize
these sleep stages.
Sleep-specific field potential oscillations
Sleep stages are characterized by specific electrical
field potential rhythms that temporally coordinate
information transfer between brain regions and
might support Hebbian and spike-time-dependent
Box 2 | The two-stage model of memory consolidation
A key issue of long-term memory formation, the
so-called stability–plasticity dilemma, is the problem
of how the brain’s neuronal networks can acquire new
information (plasticity) without overriding older
knowledge (stability). Many aspects of events
experienced during waking represent unique and
irrelevant information that does not need to be stored
long term. The two-stage model of memory offers a
widely accepted solution to this dilemma2,7,85,152 (see
the figure). The model assumes two separate memory
stores: one store allows learning at a fast rate and
serves as an intermediate buffer that holds the
information only temporarily; the other store learns at
a slower rate and serves as the long-term store.
Initially, new events are encoded in parallel in both
stores. In subsequent periods of consolidation, the
newly encoded memory traces are repeatedly
re-activated in the fast-learning store, which drives
concurrent re-activation in the slow-learning store,
and thereby new memories become gradually
redistributed such that representations in the slow-learning, long-term store are strengthened. Through the
repeated re-activation of new memories, in conjunction with related and similar older memories, the fast-learning
store acts like an internal ‘trainer’ of the slow-learning store to gradually adapt the new memories to the
pre-existing network of long-term memories. This process also promotes the extraction of invariant repeating
features from the new memories. As both stores are used for encoding information, in order to prevent interference,
the re-activation and redistribution of memories take place off-line (during sleep) when no encoding occurs.
Because in this model consolidation involves the redistribution of representations between different neuronal
systems that is, the fast- and slow-learning stores, it has been termed ‘system consolidation’. For declarative
memories, the fast- and slow-learning stores are represented by the hippocampus and neocortex, respectively.
Figure modified, with permission, from REF. 85 © (2005) Macmillan Publishers Ltd. All rights reserved.
© 20 Macmillan Publishers Limited. All rights reserved10
Nature Reviews | Neuroscience
x = 11 y = -15
Run Sleep Run Sleep
Sleep RetrievalLearning
Cortex Hippocampus
Cell number
Cell number
1 s
0.5 s 0.2 s
1 s
Stage 1
Stage 2
Stage 3
Stage 4
During SWS
Recalled card locations
No odour Odour No odour OdourNo odour Odour
20:00 24:0004:00 08:00
During REM During waking
Odour re-exposure
Time of day
Field potentials associated with SWS. Neocortical slow
oscillations, thalamo-cortical spindles and hippocampal
ripples have been associated with memory consolidation
during SWS (BOX 1). The neocortical slow oscillations (of
<1 Hz), by globally inducing up- and down-states of neu-
ronal activity, are thought to provide a supra-ordinate
temporal frame for the dialogue between the neocortex
and subcortical structures that is necessary for redistrib-
uting memories for long-term storage8,105,106. The ampli-
tude and slope of the slow oscillations are increased
when SWS is preceded by specific learning experi-
ences60,107,108 and decreased when the encoding of infor-
mation was prevented109. These changes occur locally, in
the cortical regions that were involved in encoding, and
can also be induced in humans by potentiating synap-
tic circuits through TMS91,110,111. Inducing slow oscilla-
tions during non-REM sleep by transcranial electrical
stimulation using slow (0.75 Hz) but not fast (5 Hz)
oscillating potential fields improved the consolidation
of hippocampus-dependent but not hippocampus-
independent (procedural) memories112, indicating that
slow oscillations have a causal role in the consolidation
of hippocampus-dependent memories.
Thalamo-cortical spindles seem to prime cortical
networks for the long-term storage of memory repre-
sentations. Repeated spindle-associated spike discharges
can trigger LTP87 and synchronous spindle activity
occurs preferentially at synapses that were potentiated
during encoding113. Studies in rats and humans showed
increases in spindle density and activity during non-
REM sleep and SWS after learning of both declarative
tasks and procedural motor skills20,108,114118. In some
studies these increases correlated with the post-sleep
memory improvement30,119,120 and were localized to the
cortical areas that were activated during encoding, for
example, in the prefrontal cortex after encoding of dif-
ficult word pairs117,119, the parietal cortex after a visuo-
spatial task120 and the contralateral motor cortex after
finger motor-skill learning30.
Hippocampal sharp wave-ripples accompany the
sleep-associated re-activation of hippocampal neuron
ensembles that were active during the preceding awake
experience70,71,121,122. The occurrence of sharp wave-
ripples is facilitated in previously potentiated synap-
tic circuits123 and sharp wave-ripples might promote
synaptic potentiation88,124. During an individual ripple
event only a small subpopulation of pyramidal cells fire
— the subpopulation varies between successive ripples,
indicating modulation of select neuronal circuits121,125.
In rats, learning of odour–reward associations pro-
duced a robust increase in the number and size of ripple
events for up to two hours during subsequent SWS126. In
humans (epileptic patients) the consolidation of picture
memories that were acquired before a nap correlated
with the number of ripples recorded from the peri- and
entorhinal cortex, which are important output regions
of the hippocampus127. Selective disruption of ripples
by electrical stimulation during the post-learning rest
periods in rats impaired formation of long-lasting spatial
memories128, suggesting that ripples have a causal role in
sleep-associated memory consolidation.
Figure 1 | Memory re-activation during slow wave sleep (SWS). a | In awake rats
running on a circular track (Run), neurons in the sensory cortex and hippocampus fire
in a characteristic sequential pattern. Each row represents an individual cell and each
mark in the upper parts of the diagrams indicates a spike; the curves in the lower parts
indicate the respective average firing patterns of the cells. During subsequent slow
wave sleep (SWS) (Sleep), temporal firing sequences observed in the cell assemblies
during running re-appear both in the cortex and in the hippocampus72. b | Human
subjects learned a two-dimensional object location task on a computer while an odour
was presented as a context stimulus. Re-exposure to the odour specifically during
subsequent SWS enhanced retention performance (recalled card locations) when
tested the next day. There was no enhancement in retention when no association was
formed between object locations and odour (that is, odour presentation during SWS
but not during learning) or when odour re-exposure occurred during rapid eye
movement (REM) sleep or waking15. c | When participants slept in an fMRI scanner after
learning in the presence of odour, re-exposure to the odour during SWS activated the
left anterior hippocampus (left) and neocortical regions like the retrosplenial cortex
(right), which was not observed without odour presentation during prior learning7. Part
a is modified, with permission, from REF. 72 © 2007 Macmillan Publishers Ltd. All rights
reserved; part b is modified, with permission, from REF. 15 © 2007 American
Association for the Advancement of Science; part c modified, with permission, from
REF. 7 © 2007 Elsevier.
© 20 Macmillan Publishers Limited. All rights reserved10
Up- and down-states
The slow oscillations that
predominate EEG activity
during SWS are characterized
by alternating states of
neuronal silence with an
absence of spiking activity and
membrane hyperpolarization
in all cortical neurons
(‘down-state’) and strongly
increased wake-like firing of
large neuronal populations and
membrane depolarization
Interestingly, there is a fine-tuned temporal relation-
ship between the occurrence of slow oscillations, spin-
dles and sharp wave-ripples during SWS that coordinates
the bidirectional information flow between the neocor-
tex and the hippocampus. With some exceptions (which
are probably due to methodological differences129) a
consistent finding in humans, cats, rats and mice is that
spindle activity and ripples increase during the up-state
and become suppressed during the down-state of a slow
oscillation105,129132. The top–down control of neuronal
activity by neocortical slow oscillations probably extends
to activity in other brain regions that are also relevant to
memory consolidation, such as the noradrenergic
burst activity of the locus coeruleus133,134. Sharp wave-
ripple complexes are also temporally coupled to sleep
spindles105,135,136, with individual ripple events becom-
ing nested in individual spindle troughs135. It has been
suggested that such ripple-spindle events provide a
mechanism for a fined-tuned hippocampal-neocortical
information transfer, whereby ripples and associated
hippocampal memory re-activations feed exactly into
the excitatory phases of the spindle cycle8,105,137,138. In
this scenario, the feed-forward control of slow oscil-
lations over ripples and spindles enables transferred
information to reach the neocortex during widespread
depolarization (during the up-state), that is, a state that
favours the induction of persistent synaptic changes,
eventually resulting in the storage of the information in
the cortex. The extent to which the grouping effect of the
slow oscillation on hippocampal activity is associated
with transfer of memory-specific information in the
opposite direction (from cortex to hippocampus), is
currently unclear.
Field potentials associated with REM sleep. Ponto-
geniculo-occipital (PGO) waves and the EEG theta
rhythm seem to support REM sleep-dependent consoli-
dation processes (BOX 1). The significance of PGO-waves
for memory consolidation is indicated by findings in rats
of a robust increase in REM sleep PGO-wave density
for 3–4 hours following training on an active avoid-
ance task67,139,140. The increase was proportional to the
improvement in post-sleep task performance, and was
associated with increased activity of plasticity-related
IEGs and brain-derived neurotrophic factor (Bdnf)
in the dorsal hippocampus within 3 hours following
The theta (4–8 Hz) oscillations that characterize REM
sleep in rats are also thought to contribute to consolida-
tion, based mainly on the finding that theta activity during
waking occurs during the encoding of hippocampus-
dependent memories141. However, evidence for this
assumption is scarce. There is evidence of neuronal
re-play of memories in the hippocampus during REM
sleep-associated theta activity76,77. Place cells encoding a
familiar route were re-activated preferentially during the
troughs of theta oscillations during post-training REM
sleep, whereas cells encoding novel sites fired during the
peaks77. As LTP induction in hippocampal CA1 cells
during theta activity depends on the phase of burst activ-
ity142, this finding is consistent with the idea that REM
sleep de-potentiates synaptic circuits that encode famil-
iar events but potentiates synaptic circuits that encode
novel episodes77. In humans, neocortical theta activity
was enhanced during REM sleep following learning of
word pairs62. Theta activity specifically over the right
prefrontal cortex was correlated with the consolidation
of emotional memories27. By contrast, mice exhibited
reduced REM sleep theta activity after fear condition-
ing143. Thus, although overall there is some evidence for
an involvement of theta activity in memory processing
during sleep, its specific contribution to consolidation is
obscure at present.
Theta activity occurring in conjunction with activity
in other EEG frequencies points to another important
feature that is relevant to memory processing: during
REM sleep, EEG activity in a wide range of frequencies,
including theta, shows reduced coherence between lim-
bic-hippocampal and thalamo-cortical circuits than dur-
ing SWS or waking144,145. Likewise, >40 Hz gamma band
activity shows reduced coherence between CA3 and
CA1 during tonic REM sleep146. These findings suggest
that memory systems become disengaged during REM
sleep49, possibly as a pre-requisite for establishing effec-
tive local processes of synaptic consolidation in these
systems (see below).
Synaptic homeostasis versus system consolidation
There are currently two hypotheses for the mecha-
nisms underlying the consolidation of memory during
sleep (FIG. 2). The synaptic homeostasis hypothesis11,147
assumes that consolidation is a by-product of the glo-
bal synaptic downscaling that occurs during sleep. The
active system consolidation hypothesis proposes that
an active consolidation process results from selective
re-activation of memories during sleep2,8. The two
models are not mutually exclusive; indeed, the hypoth-
esized processes probably act in concert to optimize the
memory function of sleep.
Synaptic homeostasis. According to the synaptic home-
ostasis hypothesis, information encoding during wake-
fulness leads to a net increase in synaptic strength in the
brain. Sleep would serve to globally downscale synaptic
strength to a level that is sustainable in terms of energy
and tissue volume demands and that allows for the re-
use of synapses for future encoding92,94. Slow oscillations
are associated with downscaling: they show maximum
amplitudes at the beginning of sleep when overall syn-
aptic strength is high, due to information uptake dur-
ing encoding prior to sleep, and decrease in amplitude
across SWS cycles as a result of the gradual synaptic de-
potentiation. Memories become relatively enhanced as
downscaling is assumed to be proportional in all syn-
apses, nullifying weak potentiation and thus improv-
ing the signal-to-noise ratio for the synapses that were
strongly potentiated during prior waking147 (FIG. 2a).
However, there is no clear evidence on how slow
oscillations might induce synaptic downscaling. The
low levels of excitatory neurotransmitters during SWS
(BOX 3) and the sequence of depolarization (up-states)
and hyperpolarization (down-states) of slow oscillations
© 20 Macmillan Publishers Limited. All rights reserved10
Nature Reviews | Neuroscience
Waking – Synaptic potentiation
Sleep – Synaptic downscaling
Synaptic plasticity
Slow oscillations
Sharp wave-ripples
Synaptic strength
at a frequency of <1 Hz might specifically promote the de-
potentiation of synapses148. Indeed, slow oscillations and
the associated activation of T-type Ca2+ channels seem to
favour LTD over LTP89; however, thalamo-cortical spindles
and hippocampal ripples nesting in depolarizing up-states
of slow oscillations support LTP87,88,124.
In addition, although the expression of markers of
synaptic potentiation (such as plasticity-related IEGs) is
globally reduced after a period of sleep, it is increased in
specific regions, particularly if sleep was preceded by a
learning experience78,96,98, indicating that synaptic poten-
tiation might still take place during sleep. Consistent
with downscaling, some neuroimaging studies (which
measure relative changes in brain activation) have shown
reduced task-related activity in cortical regions after sleep
(e.g. REF. 149), but these reductions were accompanied by
increases in activity in other regions82,83,149,150. Also, glo-
bal synaptic downscaling implicates that weakly encoded
memories are forgotten, which contrasts with behav-
ioural evidence indicating either no or, under certain
conditions, a greater benefit from sleep for weakly than
strongly encoded memories35,36. Therefore, downscaling
per se does not explain key features of sleep-dependent
consolidation. However, the synaptic downscaling
model explains a second memory-related function
of sleep, namely that sleep pro-actively facilitates the
encoding of new information during subsequent wake-
fulness through the de-potentiation of synapses that had
become saturated during preceding wakefulness (this
topic is beyond the scope of this Review)151.
Active system consolidation. This concept originated
from the standard two-stage model of consolidation pro-
posed for declarative memory2,7,85,121,152 (BOX 2; FIG. 2b), but
might also account for consolidation in other memory
systems8. It is assumed that in the waking brain events
are initially encoded in parallel in neocortical networks
and in the hippocampus. During subsequent periods of
SWS the newly acquired memory traces are repeatedly
re-activated and thereby become gradually redistributed
such that connections within the neocortex are strength-
ened, forming more persistent memory representations.
Re-activation of the new representations gradually adapt
them to pre-existing neocortical ‘knowledge networks’,
Figure 2 | Synaptic homeostasis versus active system consolidation. The synaptic homeostasis hypothesis (a)
proposes that due to encoding of information during waking, synapses become widely potentiated (large yellow nerve
ending), resulting in a net increase in synaptic strength (W = synaptic weight). The small nerve ending represents a new
synapse and the unfilled nerve ending is not activated and therefore does not increase in weight. The slow oscillations
during subsequent SWS serve to globally downscale synaptic strength (burgundy nerve endings). Thereby, weak
connections are eliminated, whereas the relative strength of the remaining connections is preserved. Thus, a memory is
enhanced as a consequence of an improved signal-to-noise ratio after downscaling. The active system consolidation
model (b) assumes that events during waking are encoded in both neocortical and hippocampal networks. During
subsequent slow wave sleep (SWS), slow oscillations drive the repeated re-activation of these representations in the
hippocampus, in synchrony with sharp wave-ripples and thalamo-cortical spindles (synchronizing feed-forward effect of
the slow oscillation up-state). By synchronizing these events the slow oscillations support the formation of ripple-spindle
events, which enable an effective hippocampus-to-neocortex transfer of the re-activated information. Arrival of the
hippocampal memory output at cortical networks, coinciding with spindle activity during the depolarizing slow oscillation
up-state predisposes these networks to persisting synaptic plastic changes (for example, expression of immediate early
genes (IEG) through Ca2+/calmodulin-dependent protein kinase II (CaMKII) and protein kinase A (PKA) activation) that are
supported primarily by subsequent rapid eye movement (REM) sleep. AMPAR, α-amino-3-hydroxy-5-methyl-4-isoxazole
propionic acid receptor; LTP, long-term potentiation; NMDAR, N-methyl-d-aspartate receptor. Part a is modified, with
permission, from REF. 147 © 2006 Elsevier; part b is modified, with permission, from REF. 5 © 2006 Sage publications.
© 20 Macmillan Publishers Limited. All rights reserved10
thereby promoting the extraction of invariant repeat-
ing features and qualitative changes in the memory
Corroborating this concept, studies showed that
memory re-activation during post-learning SWS and
hippocampal ripples accompanying this re-activation
have a causal role in consolidation15,128. Re-activation in
hippocampal networks seems to be enabled by the low
cholinergic tone that characterizes SWS153155 (BOX 3).
Moreover, there is evidence that the re-activation and
redistribution of memories during SWS is regulated
by a dialogue between the neocortex and the hippoc-
ampus that is essentially under feed-forward control of
the slow oscillations, which provide a temporal frame.
The depolarizing cortical up-states repetitively drive the
re-activation of memory traces in hippocampal circuits
in parallel with thalamo-cortical spindles and activity
from other regions (for example, noradrenergic locus
coeruleus bursts, see BOX 3). This enables synchronous
feedback from these structures to the neocortex during
the slow oscillation up-state, which is probably a pre-
requisite for the formation of more persistent traces in
neocortical networks8,106. Consistent with this concept,
neuronal re-activations in the timeframe of cortical slow
oscillations have been demonstrated, in which hippocam-
pal re-play leads re-activation in the neocortex72,122 (and
also in other structures like the striatum156). Moreover,
slow oscillations drive the ripples that accompany hip-
pocampal re-activation, thus allowing for the formation
of spindle-ripple events as a mechanism for effective
hippocampus-to-neocortex information transfer105,137,138
(FIG. 2b). Spindles reaching the neocortex during slow
oscillation up-states probably act to prime specific neu-
ronal networks, for example, by stimulating Ca2+ influx,
for subsequent synaptic plastic processes87,157.
The concept of active system consolidation during
SWS integrates a central finding from behavioural stud-
ies, namely that post-learning sleep not only strength-
ens memories but also induces qualitative changes in
their representations and so enables the extraction of
invariant features from complex stimulus materials, the
forming of new associations and, eventually, insights
into hidden rules46–48. The concept of a redistribution
of memories during sleep has been corroborated by
human brain imaging studies82,83,149,150,158. Interestingly, in
these studies, hippocampus-dependent memories were
particularly redistributed to medial prefrontal cortex
regions82,83,122 that also contribute to the generation of
slow oscillations159,160. These regions not only have a key
role in the recall and binding of these memories once
they are stored for the long term85, but also, together
with the hippocampus, form a loop that supports the
explicit encoding of information. As mentioned above,
behavioural data indicate that sleep does not benefit all
memories equally, but seems to preferentially consoli-
date explicitly encoded information34. In this context, the
prefrontal–hippocampal system might provide a selec-
tion mechanism that determines which memory enters
sleep-dependent consolidation.
A role for REM sleep in synaptic consolidation
The active system consolidation hypothesis leaves open
one challenging issue: although it explains a re-activation-
dependent temporary enhancement and integration
of newly encoded memories into the network of pre-
existing long-term memories, active system consoli-
dation alone does not explain how post-learning sleep
strengthens memory traces and stabilizes underlying
synaptic connections in the long term. Hence, sleep pre-
sumably also supports a synaptic form of consolidation
for stabilizing memories and this could be the function
of REM sleep.
The view that synaptic consolidation is promoted
by REM sleep is supported by the molecular and elec-
trophysiological events that characterize this stage.
Box 3 | Neuromodulators
The specific neurochemical milieu of neurotransmitters and hormones differs strongly
between slow wave sleep (SWS) and rapid eye movement (REM) sleep. Some of these
neuromodulators contribute to memory consolidation. Interestingly, the most
prominent contributions to memory processing seem to originate from the cholinergic
and monoaminergic brainstem systems that are also involved in the basic regulation of
Cholinergic activity is at a minimum during SWS; this is thought to enable the
spontaneous re-activation of hippocampal memory traces and information transfer to
the neocortex by reducing the tonic inhibition of hippocampal CA3 and CA1 feedback
neurons8,154,155. Accordingly, increasing cholinergic tone during SWS-rich sleep (using
physostigmine) blocked the sleep-dependent consolidation of hippocampus-dependent
word-pair memories153. Conversely, blocking the high cholinergic tone in awake
subjects improved consolidation but impaired the encoding of new information172,
suggesting that acetylcholine serves as a switch between modes of brain activity, from
encoding during wakefulness to consolidation during SWS154,155. This dual function of
acetylcholine seems to be complemented by glucocorticoids (cortisol in humans), the
release of which is also at a minimum during SWS. Glucocorticoids block the
hippocampal information flow to the neocortex, and if the level of glucocorticoids
is artificially increased during SWS, the consolidation of declarative memories is
Noradrenergic activity is at an intermediate level during SWS, and seems to be
related to slow oscillations. In rats, phasic burst firing in the locus coeruleus (the brain’s
main source of noradrenaline) can be entrained by slow oscillations in the frontal
cortex, with a phase-delay of ~300 ms133. It is possible that such bursts enforce
plasticity-related immediate early gene (IEG) activity in the neocortex93,95, and thereby
support at the synaptic level the stabilization of newly formed memory
representations. In humans, the consolidation of odour memories was impaired after
pharmacological suppression of noradrenergic activity during SWS-rich sleep and
improved after increasing noradrenaline availability (S. Gais, B. Rasch, J.C. Dahmen, S.J.
Sara and J. B., unpublished observations).
REM sleep
Cholinergic activity during REM sleep is similar or higher than during waking. This high
cholinergic activity might promote synaptic consolidation by supporting
plasticity-related IEG activity162 and the maintenance of long-term potentiation163.
Accordingly, blocking muscarinic receptors in rats by scopolamine during REM sleep
impaired memory in a radial arm maze task175. In humans, blocking cholinergic
transmission during REM-rich sleep prevented gains in finger motor skill176. Conversely,
enhancing cholinergic tone during post-training REM-rich sleep improved
consolidation of a visuo-motor skill177.
Noradrenergic and serotonergic activity reaches a minimum during REM sleep, but it
is unclear whether this contributes to consolidation. It has been proposed that the
release from inhibitory noradrenergic activity during REM sleep enables the
re-activation of procedural and emotional aspects of memory (in cortico-striatal and
amygdalar networks, respectively), thus supporting memory consolidation154,178.
However, enhancing noradrenergic activity during post-learning REM sleep in humans
failed to impair procedural memory consolidation56.
© 20 Macmillan Publishers Limited. All rights reserved10
Nature Reviews | Neuroscience
Waking SWS REM sleep
Long-term store
Temporary store
Active system
Although any links between sleep phases of short dura-
tion and gene expression are difficult to demonstrate
for methodological reasons, several studies suggest that
REM sleep, unlike SWS, is associated with an upregu-
lation of plasticity-related IEG activity (REFS 97,98,139).
The upregulation depends on learning experience dur-
ing prior wakefulness and is localized to brain regions
involved in prior learning97,98,139. Interestingly, this IEG
activity is correlated with EEG spindle activity during
preceding SWS98. Spindles (which, as discussed above,
represent a candidate mechanism that tags networks for
the neocortical storage of memories during system con-
solidation) per se do not induce IEG activity, but might
prime particular brain areas for it, possibly by enhanc-
ing Ca2+ concentrations in select subgroups of cortical
neurons87,157. The activity of plasticity-related early genes
depends on cholinergic tone161,162, which is enhanced to
wake-like levels during REM sleep (BOX 3). Cholinergic
activation strengthens the maintenance of LTP in the hip-
pocampus-medial prefrontal cortex pathway163, a main
route for transferring memories during SWS-dependent
system consolidation82,83,122,136. Electrophysiological sig-
natures of REM sleep, such as PGO waves, are increased
during post-learning sleep and might promote IEG
activity and memory consolidation140. EEG recordings
indicate that during REM sleep brain activation is as
high as during waking, but less coherent between differ-
ent regions and noisier144146. This high level of activation
could act non-specifically to amplify local synaptic plas-
ticity in an environment that, compared with the awake
state, is almost entirely unbiased by external stimulus
inputs. The disentangled, localized nature of synaptic
consolidation might also explain why REM sleep alone
fails to improve declarative memory consolidation: this
process essentially relies on the integration of features
from different memories in different memory sys-
tems and corresponding information transfer between
widespread brain areas, that is, SWS-dependent system
Conclusions and future directions
SWS and REM sleep have complementary functions to
optimize memory consolidation (FIG. 3). During SWS —
characterized by slow oscillation-induced widespread
synchronization of neuronal activity — active system
consolidation integrates newly encoded memories with
pre-existing long-term memories, thereby inducing con-
formational changes in the respective representations.
System consolidation (which preferentially affects explic-
itly encoded, behaviourally relevant information) acts in
Figure 3 | Sequential contributions of SWS and REM sleep to memory consolidation in a two-stage memory
system. During waking, memory traces are encoded in both the fast-learning, temporary store and the slow-learning,
long-term store (in the case of declarative memory these are represented by the hippocampus and neocortex,
respectively). During subsequent slow wave sleep (SWS), active system consolidation involves the repeated re-activation
of the memories newly encoded in the temporary store, which drives concurrent re-activation of respective
representations in the long-term store together with similar associated representations (dotted lines). This process
promotes the re-organization and integration of the new memories in the network of pre-existing long-term memories.
System consolidation during SWS acts on the background of a global synaptic downscaling process (not illustrated) that
prevents saturation of synapses during re-activation (or during encoding in the subsequent wake-phase). During ensuing
rapid eye movement (REM) sleep, brain systems act in a ‘disentangled’ mode that is also associated with a disconnection
between long-term and temporary stores. This allows for locally encapsulated processes of synaptic consolidation, which
strengthen the memory representations that underwent system consolidation (that is, re-organization) during prior SWS
(thicker lines). In general, memory benefits optimally from the sequence of SWS and REM sleep. However, declarative
memory, because of its integrative nature (it binds features from different memories in different memory systems),
benefits more from SWS-associated system consolidation, whereas procedural memories, because of their specificity
and discrete nature, might benefit more from REM sleep-associated synaptic consolidation in localized brain circuits.
Figure modified, with permission, from REF. 85 © 2005 Macmillan Publishers Ltd. All rights reserved.
© 20 Macmillan Publishers Limited. All rights reserved10
concert with global synaptic downscaling, which serves
mainly to preclude the saturation of synaptic networks.
Ensuing REM sleep — characterized by de-synchroniza-
tion of neuronal networks, which possibly reflects a disen-
gagement of memory systems — might act to stabilize the
transformed memories by enabling undisturbed synaptic
consolidation. Although REM sleep has been suspected
for a long time to have a key role in memory consolida-
tion, research has paid little attention to the fact that REM
sleep naturally follows SWS. This points to complementing
contributions of sequential SWS and REM sleep to mem-
ory consolidation — an idea that was originally proposed
in the sequential hypothesis64. This Review revives this
idea by indicating an essential role of SWS in system con-
solidation that might be complemented by the synaptic
consolidation taking place during REM sleep. However,
direct evidence of this is scarce at present65. Specifying the
role of REM sleep, as an integral part of this sequence, in
synaptic consolidation will undoubtedly pose a particular
challenge to future research.
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We apologize to those whose work was not cited because of
space constraints. We thank Drs. B. Rasch, L. Marshall, I.
Wilhelm, M. Hallschmid, E. Robertson and S. Ribeiro for help-
ful discussions and comments on earlier drafts. This work was
supported by a grant from the Deutsche Forschungsgemeinschaft
(SFB 654 ‘Plasticity and Sleep’).
Competing interests statement
The authors declare no competing financial interests.
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... We also compared sleep variables on the eighth night between the two groups (Table S5) to ascertain that there were no differences in sleep variables (i.e., TBT, TST, SOL) that could have affected memory performance [23,24]. ...
... We also compared sleep variables on the eighth night between the two groups ( Table S5) to ascertain that there were no differences in sleep variables (i.e., TBT, TST, SOL) that could have affected memory performance [23,24]. ...
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Background: Sleep talking (ST) is characterized by the production of unaware verbal vocal activations (VBs) during sleep. ST seems potentially linked to linguistic and memory consolidation processes. However, sleep and dream characteristics and the relationship between verbal vocalizations (VBs) and cognitive functions are still unknown. Our study aimed to investigate qualitative sleep and dream features in sleep talkers (STs) compared to healthy subjects (CNTs) through retrospective and longitudinal measures and explore the relationship between ST and memory consolidation. Methods: We recruited N = 29 STs and N = 30 CNTs (age range of 18-35). Participants recorded their dreams and filled out sleep logs for seven consecutive days. Vocal activations of STs were audio-recorded. On the eighth day, we administered a word-pair task. Results: We showed that STs had significantly worse self-reported sleep quality. VBs were positively correlated with sleep fragmentation and negatively associated with the oneiric emotional load. No difference between groups was found in the memory consolidation rate. Conclusions: Although ST is a benign phenomenon, we revealed that ST is associated with more sleep alterations and lower emotional intensity of dreams. In this vein, we support that ST depends on sleep fragmentation and could represent a potential window into sleep-dependent cognitive processes.
... Sleep is implicated in learning and memory [1][2][3][4]. Both slow wave sleep (SWS) and REM sleep have been shown to be important for the consolidation of newly acquired memories through sleep-induced changes in neuronal activity and molecular cascades. ...
... In other words, such correlation is likely due to the IS spindles in REM animals, an idea corroborated by the fact that phospho-CaCNA2D1 is decreased during REM in exposed animals, and in agreement with the evidence that phosphorylated CaMKII levels are increased during REM sleep in animals that were previously exposed to novelty, in positive correlation with SWS+IS spindles [19]. The major phosphoproteomic differences between HP and S1 across the sleep cycle have implications for memory corticalization and active systems consolidation theory [4]. ...
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The role of sleep on memory consolidation is thought to involve experience-dependent changes in spindle oscillations and protein phosphorylation, but how these phenomena are related remains poorly understood. To gain insight into this relationship, we used electrophysiological recordings and quantitative phosphoproteomic analysis to assess spindle oscillations and phosphoprotein levels in the hippocampus (HP) and primary somatosensory cortex (S1) of adult male rats recorded across the sleep cycle. Animals were surgically implanted with multielectrode probes and after recovery were exposed or unexposed to novel objects (+ and – groups, respectively). HP and S1 samples were obtained after periods rich in either slow-wave sleep (SWS) or rapid-eye-movement sleep. Bottom-up shotgun mass spectrometry in a two-dimensional liquid chromatography-tandem mass spectrometry setup (MSE mode with label-free quantification) showed that the proteomes differed in the numbers of phosphoproteins identified by phosphoryl modification STY tags, with a total of 337 validated phosphoproteins identified in S1 and 198 in the HP. A comparison of the phosphoproteomic profiles of the treatments and regions (SWS+ versus SWS-, REM+ versus REM-, REM+ versus SWS+ and REM- versus SWS-), using clustering analysis of the significantly identified phosphoproteins, found that 51 phosphoproteins from S1 were sufficient to separate the four experimental conditions, while 37 phosphoproteins from the HP could only partially separate the groups. Fold change analysis identified 90 significantly modulated phosphoproteins related to synaptic function, actin-microtubule regulation, DNA-RNA binding, proteases-phosphatases-kinases and other regulatory functions, including CaMKII and MAPK. In both the HP and S1, nearly one third of the clustering-relevant phosphoproteins had levels significantly correlated with the abundance of spindle oscillations pooled across the transition from SWS to REM. In S1, phosphorylated Reelin was upregulated during REM compared to SWS, in proportion to the number of spindle oscillations during the transition from SWS to REM. In the HP, a voltage-gated calcium channel subunit (Cacna2d1) was down-regulated during REM+ compared to SWS+, in proportion to spindle counts. Since spindles facilitate calcium entry through the opening of voltage-dependent calcium channels, Cacna2d1 down-regulation may lead to a hippocampus-specific, REM-dependent downregulation of synaptic plasticity after exposure to novel objects. The results point to major experience-dependent differences between HP and S1 in phosphoproteomic regulation across the sleep cycle, with potential implications for memory corticalization.
... Therefore, fatigue applies not only to the muscular effort, but also to athletes' psychology. Sleep loss exerts a negative effect on perceived effort values 4 as well as on cognitive and neurobehavio ra l performance 5,6 , resulting in a reduction of the ability to encode new information and consolidate memory 7 . Sleep loss consists of insufficient sleep continuity and/or duration. ...
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The study aimed at investigating the association between different sleep management strategies and the final ranking during a one‐night sailing race. A large sample of 190 teams participating in the overnight sailing regatta (151 Miglia) were included in the study. The experimental design consisted of two surveys, administered one before the start of the race and the other after the arrival. The questionnaires provided general information on the sailboat, its crew, and the strategy adopted to manage sleep during the race. In this one‐night regatta, the self‐management of sleep/wake timing emerged as the most successful strategy. Among participants who adopted a shift‐based racing strategy, a short night shift duration (i.e., 2 hours) significantly predicted a better placement. These findings confirmed the relevance of sleep management in sport performance and provided new insights on the most suitable sleep management strategy during a relatively short off‐shore regatta. The conclusions might apply also to similar continuous‐cycle activities. Further investigations are needed to explore best sleep management strategy in team regattas of longer duration.
Previous research about learning new meanings for known words in second language (L2) has found that semantic relatedness, i.e., congruency, between new and existing meanings benefits encoding and explicit memory of new meanings, and reduces instant interference on accessing existing meanings. However, they did not take the memory consolidation process into account. Thus, integration of new meaning into long-term semantic memory, update of existing meaning representation, and the impact of semantic relatedness between new and existing meanings in this process remain unclear. The present study used the event-related potential (ERP) technique to explore these questions. We asked Chinese students to learn English known words' subdominant meanings variedly related to existing meanings and probed semantic representations with EEG recorded in primed lexical decision tasks four times before and after consolidation. We found that new meaning needs to go through offline consolidation to get integrated. Semantic relatedness/congruency boosted new meaning integration, not by directly expediting it during encoding or preliminary offline consolidation, but by promoting the update of existing meaning representation first, which presumably paved the way for better incorporation of new meaning in the long run. The whole pattern of results implies that long-term semantic representation of existing meaning is updated to integrate related new meaning after consolidation, which not only draws a clearer picture of L2 ambiguous word acquisition but also bears broader implications for research on memory updating.
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Every night, we pass through a transitory zone at the borderland between wakefulness and sleep, named the first stage of nonrapid eye movement sleep (N1). N1 sleep is associated with increased hippocampal activity and dream-like experiences that incorporate recent wake materials, suggesting that it may be associated with memory processing. Here, we investigated the specific contribution of N1 sleep in the processing of memory traces. Participants were asked to learn the precise locations of 48 objects on a grid and were then tested on their memory for these items before and after a 30-min rest during which participants either stayed fully awake or transitioned toward N1 or deeper (N2) sleep. We showed that memory recall was lower (10% forgetting) after a resting period, including only N1 sleep compared to N2 sleep. Furthermore, the ratio of alpha/theta power (an electroencephalography marker of the transition toward sleep) correlated negatively with the forgetting rate when taking into account all sleepers (N1 and N2 groups combined), suggesting a physiological index for memory loss that transcends sleep stages. Our findings suggest that interrupting sleep onset at N1 may alter sleep-dependent memory consolidation and promote forgetting.
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The cerebral cortex is spontaneously active during sleep, yet it is unclear how this global cortical activity is spatiotemporally organized, and whether such activity not only reflects sleep states but also contributes to sleep state switching. Here we report that cortex-wide calcium imaging in mice revealed distinct sleep stage-dependent spatiotemporal patterns of global cortical activity, and modulation of such patterns could regulate sleep state switching. In particular, elevated activation in the occipital cortical regions (including the retrosplenial cortex and visual areas) became dominant during rapid-eye-movement (REM) sleep. Furthermore, such pontogeniculooccipital (PGO) wave-like activity was associated with transitions to REM sleep, and optogenetic inhibition of occipital activity strongly promoted deep sleep by suppressing the NREM-to-REM transition. Thus, whereas subcortical networks are critical for initiating and maintaining sleep and wakefulness states, distinct global cortical activity also plays an active role in controlling sleep states. The cortex is very active during sleep. Wang et al. used macroscopic Ca2+ imaging to record the global cortical activity from the entire dorsal cortex of mice during sleep and uncover an unexpected role of the cortex in controlling REM sleep.
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Purpose Interictal epileptic discharges (IEDs) are known to affect cognitive function in patients with epilepsy, but the mechanism has not been elucidated. Sleep spindles appearing in synchronization with IEDs were recently demonstrated to impair memory consolidation in rat, but this has not been investigated in humans. On the other hand, the increase of sleep spindles at night after learning is positively correlated with amplified learning effects during sleep for motor sequence learning. In this study, we examined the effects of IEDs and IED-coupled spindles on motor sequence learning in patients with epilepsy, and clarified their pathological significance. Materials and methods Patients undergoing long-term video-electroencephalography (LT-VEEG) at our hospital from June 2019 to November 2021 and age-matched healthy subjects were recruited. Motor sequence learning consisting of a finger-tapping task was performed before bedtime and the next morning, and the improvement rate of performance was defined as the sleep-dependent learning effect. We searched for factors associated with the changes in learning effect observed between the periods of when antiseizure medications (ASMs) were withdrawn for LT-VEEG and when they were returned to usual doses after LT-VEEG. Results Excluding six patients who had epileptic seizures at night after learning, nine patients and 11 healthy subjects were included in the study. In the patient group, there was no significant learning effect when ASMs were withdrawn. The changes in learning effect of the patient group during ASM withdrawal were not correlated with changes in sleep duration or IED density; however, they were significantly negatively correlated with changes in IED-coupled spindle density. Conclusion We found that the increase of IED-coupled spindles correlated with the decrease of sleep-dependent learning effects of procedural memory. Pathological IED-coupled sleep spindles could hinder memory consolidation, that is dependent on physiological sleep spindles, resulting in cognitive dysfunction in patients with epilepsy.
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Nowadays communication device usage has already reached an unprecedented level. Based on data provided by Central Statistics Agency (BPS), by 2018, at least 62% of Indonesian had a cellphone or a smartphone, and 20% had a computer. Besides smartphones and computers, many Indonesians choose television (TV) as their entertainment device, as proven by 57% of Indonesian households having a TV, although the number has been reduced in the past decade. Based on research conducted by Zickuhr, in 2011, average adults in the United States spent 7-10 hours using their communication device per day, with the most usage in the young adult population (18-35 years) and decreasing as the age increased. The recent development of computer-based communication devices increased our chances of spending much time staring at the blue light emitting screen. Research about the blue light emission effect has become a significant concern, especially in the last five years. It is due to its effect on sleep quality and eyes well-being. This research is an analytic descriptive, non-experiment cross-sectional study. The research uses a prospective and retrospective approach due to the type of data is primary data collected using a questionnaire distributed through social media. Based on Slovin's formula, the sample needed for this study is 133 respondents. This study showed a significant correlation between the usage of blue light-emitting communication devices, sleep quality (P = 0.000), and a moderate relation (r = 0.425) with the positive pattern. Keywords: Communication device usage, blue light, sleeps quality
The majority of older adults express a desire to age successfully. Over the past decade, there has been an increased focus on understanding the lifestyle factors that influence cognitive aging. In years past, it was believed that genetic factors played a primary role in cognitive longevity, but it is now well-established that various lifestyle factors are strongly linked to successful cognitive and general aging. The present chapter aims to review lifestyle factors that contribute to brain and cognitive health in older adults. In particular, we review research examining the role of exercise, social and cognitively stimulating activity, purpose in life, sleep, diet and vascular health, and age-related attitudes and stereotypes on cognition in later life. We also discuss the impact of various interventions on cognitive health. We conclude with recommended future research and intervention-oriented directions that may further our understanding and promotion of successful cognitive aging.
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Active recall of short-term memory (STM) is known to last for a few hours, but whether STM has long-term functions is unknown. Here we show that STM can be optogenetically retrieved at a time point during which natural recall is not possible, uncovering the long-term existence of an STM engram. Moreover, re-training within 3 days led to natural long-term recall, indicating facilitated consolidation. Inhibiting offline CA1 activity during non-rapid eye movement (NREM) sleep, N-methyl-D-aspartate receptor (NMDAR) activity, or protein synthesis after first exposure to the STM-forming event impaired the future re-exposure-facilitated consolidation, which highlights a role of protein synthesis, NMDAR and NREM sleep in the long-term storage of an STM trace. These results provide evidence that STM is not completely lost within hours and demonstrates a possible two-step STM consolidation, first long-term storage as a behaviorally inactive engram, then transformation into an active state by recurrence within 3 days.
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In most mammalian species studied, two distinct and successive phases of sleep, slow wave (SW), and rapid eye movement (REM), can be recognized on the basis of their EEG profiles and associated behaviors. Both phases have been implicated in the offline sensorimotor processing of daytime events, but the molecular mechanisms remain elusive. We studied brain expression of the plasticity-associated immediate-early gene (IEG) zif-268 during SW and REM sleep in rats exposed to rich sensorimotor experience in the preceding waking period. Whereas nonexposed controls show generalized zif-268 down-regulation during SW and REM sleep, zif-268 is upregulated during REM sleep in the cerebral cortex and the hippocampus of exposed animals. We suggest that this phenomenon represents a window of increased neuronal plasticity during REM sleep that follows enriched waking experience.
We spend so much of our lives sleeping, yet its precise function is unclear, in spite of our increasing understanding of the processes generating and maintaining sleep. We now know that sleep can be accompanied by periods of intense cerebral activity, yet only recently has experimental data started to provide us with some insights into the type of processing taking place in the brain as we sleep. There is now strong evidence that sleep plays a crucial role in learning and in the consolidation of memories. Once the preserve of psychoanalysts, ‘dreaming’ is now a topic of increasing interest amongst scientists. With research into sleep growing, this book presents a unique study of the relationship between sleep, learning, and memory. It brings together a team of international scientists researching sleep in both human and animal subjects.
We have previously presented a wealth of data refuting the proposal that memories are processed or consolidated in sleep. Our objections have been largely ignored, creating the impression that the hypothesized role for sleep in memory processing is an established fact rather than a highly controversial and unresolved issue. We briefly review the main arguments against a role for sleep in learning/memory.
We spend so much of our lives sleeping, yet its precise function is unclear, in spite of our increasing understanding of the processes generating and maintaining sleep. We now know that sleep can be accompanied by periods of intense cerebral activity, yet only recently has experimental data started to provide us with some insights into the type of processing taking place in the brain as we sleep. There is now strong evidence that sleep plays a crucial role in learning and in the consolidation of memories. Once the preserve of psychoanalysts, ‘dreaming’ is now a topic of increasing interest amongst scientists. With research into sleep growing, this book presents a unique study of the relationship between sleep, learning, and memory. It brings together a team of international scientists researching sleep in both human and animal subjects.