Neuroscience and Biobehavioral Reviews 36 (2012) 1718–1728
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Neuroscience and Biobehavioral Reviews
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Review
Sleep-dependent memory consolidation – What can be learnt from children?
I. Wilhelma,b,∗
, A. Prehn-Kristensenc
, J. Borna,b
a
Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, 72074 Tübingen, Germany
b
Department of Neuroendocrinology, University of Lübeck, 23538 Lübeck, Germany
c
Center for Integrative Psychiatry, Department of Child and Adolescent Psychiatry and Psychotherapy, Christian-Albrechts-University School of Medicine, Niemannsweg 147, 24105
Kiel, Germany
a r t i c l e i n f o
Article history:
Received 27 September 2011
Received in revised form 20 February 2012
Accepted 2 March 2012
Keywords:
Memory consolidation
Sleep
Children
Development
a b s t r a c t
Extensive research has been accumulated demonstrating that sleep is essential for processes of memory
consolidation in adults. In children and infants, a great capacity to learn and to memorize coincides with
longer and more intense sleep. Here, we review the available data on the influence of sleep on memory
consolidation in healthy children and infants, as well as in children with attention-deficit/hyperactivity
disorder (ADHD) as a model of prefrontal impairment, and consider possible mechanisms underlying agedependent
differences. Findings indicate a major role of slow wave sleep (SWS) for processes of memory
consolidation during early development. Importantly, longer and deeper SWS during childhood appears
to produce a distinctly superior strengthening of hippocampus-dependent declarative memories, but
concurrently prevents an immediate benefit from sleep for procedural memories, as typically observed
in adults. Studies of ADHD children point toward an essential contribution of prefrontal cortex to the
preferential consolidation of declarative memory during SWS. Developmental studies of sleep represent
a particularly promising approach for characterizing the supra-ordinate control of memory consolidation
during sleep by prefrontal-hippocampal circuitry underlying the encoding of declarative memory.
© 2012 Elsevier Ltd. All rights reserved.
Contents
1. Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1718
2. Sleep-dependent memory consolidation in adults – current state of knowledge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1719
3. The role of sleep on processes of memory consolidation in children and infants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1720
3.1. Declarative memory. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1720
3.2. Emotional memory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1721
3.3. Procedural memory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1721
3.4. Extraction of explicit knowledge from procedural skill . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1722
3.5. Wake consolidation and the role of the pre-sleep performance level. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1724
4. Sleep-dependent memory consolidation in children suffering from ADHD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1724
4.1. Why studying sleep-dependent memory consolidation in ADHD patients?. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1724
4.2. Sleep-dependent memory consolidation in patients with ADHD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1725
5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1726
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1727
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1727
1. Introduction
From the cradle to the grave we accumulate great amounts of
memories that enable us to effectively cope with environmental
∗ Corresponding author at: Department of Neuroendocrinology, University of
Lübeck, 23538 Lübeck, Germany. Tel.: +49 451 5004602; fax: +49 451 5003640.
E-mail address: wilhelm@kfg.uni-luebeck.de (I. Wilhelm).
challenges and also define who we are. The developing brain with
its particularly high capacity for plasticity easily acquires basic
motor skills like running, speaking and writing as well as fundamental
knowledge about how the world is organized. Studies
in adults have compellingly demonstrated that sleep after learning
new materials supports the consolidation of this information
in memory, thereby generating stable and long-lasting memory
representations (Diekelmann and Born, 2010; Stickgold, 2005;
Peigneux et al., 2001). Infants and children do not only learn much
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doi:10.1016/j.neubiorev.2012.03.002
I. Wilhelm et al. / Neuroscience and Biobehavioral Reviews 36 (2012) 1718–1728 1719
but also sleep longer and more deeply than adults (Campbell and
Feinberg, 2009; Ohayon et al., 2004). Importantly, children spend
a particularly long time during sleep in slow wave sleep (SWS),
i.e., a sleep stage that in adults has been revealed to causally contribute
to the consolidation of memories (Marshall et al., 2006;
Rasch et al., 2007). Considering the immense plasticity of the developing
brain together with its specific sleep architecture, children
might represent a promising model to further our understanding
of the fundamental principles and mechanisms underlying
sleep-dependent memory consolidation, although some of these
mechanisms may be specific to the conditions during development
and cannot be generalized to the adults’ brain. This review
aims at discussing recent studies investigating the role of sleep
for processes of memory consolidation in children and infants.
In so doing, we will contrast findings in children with those in
adults, keeping in mind the question “What can we learn from
children?”
2. Sleep-dependent memory consolidation in adults –
current state of knowledge
Since almost 100 years it is well-known from experimental
psychological research that sleep benefits the consolidation of
memory in adults (Jenkins and Dallenbach, 1924; Heine, 1914).
As a standard design in these studies, subjects learn memory
materials (encoding) and retrieval of the encoded memories is
tested after retention interval of a specific length filled with
either sleep or wakefulness. Comparing the retrieval performance
when subjects had slept after learning with that after
they had stayed awake during the retention interval generally
reveals better performance in the sleep condition (Diekelmann
et al., 2009; Stickgold, 2005; Peigneux et al., 2001; Rauchs et al.,
2005). Sleep-associated improvements in the retention of memories
were reported for a great variety of declarative (e.g. learning
of paired associates, texts, object locations) and procedural memory
tasks (e.g. finger sequence tapping, mirror tracing; for review
see Stickgold, 2005; Peigneux et al., 2001; Born and Wilhelm,
2011).
In one of the first studies on processes of sleep-dependent
memory consolidation, by Jenkins and Dallenbach (1924), better
memory for nonsense syllables after retention sleep than
wakefulness was reported. Those authors assumed that sleep benefits
performance by protecting newly encoded memories from
retroactive interference (Jenkins and Dallenbach, 1924). Specifically,
it was assumed that during sleep there is no further entry
and encoding of new information into the brain which, during
wakefulness, would disturb the consolidation of the formerly
encoded memories by overwriting respective representations.
Recent theories have proposed that sleep does not only passively
protect memories from retroactive interference but enables
processes that actively enhances specific memories (Ellenbogen
et al., 2006a; Stickgold, 2005; Born et al., 2006; Marshall and
Born, 2007). This theorizing arose from the so-called ‘standard
consolidation theory’ that is based on a two-stage model of memory
comprising a temporary and a long-term store (Marr, 1971;
McClelland et al., 1995). The active system consolidation theory
of sleep-dependent memory consolidation postulates that memories
initially encoded in the hippocampus which serves as a
temporary store for declarative memories, are reactivated during
sleep in order to be gradually redistributed preferentially
to neocortical sites which serve as long-term store for declarative
memories, whereby these memories are incorporated into
the pre-existing network of long-term memories (Fig. 1). While
most memories during this redistribution process become less
dependent of hippocampal circuitry, genuinely episodic memories
probably remain anchored in hippocampal networks, as specified
in the multiple trace theory of memory consolidation (Winocur
et al., 2010; Nadel et al., 2000). Empirical evidence for a neuronal
redistribution in the representation of memories that is induced
by sleep was provided by studies demonstrating that, compared
with wakefulness, sleep after learning declarative materials produced
a distinctly greater activation of mid-prefrontal regions at
a later retrieval (Gais et al., 2007; Takashima et al., 2006). The
theory assumes that the redistribution of neuronal memory representations
during sleep is invoked by the repeated reactivation
of newly encoded representations. Reactivations of new neuronal
representations, representing a basic mechanism of offline memory
consolidation, have been demonstrated in a number of studies
in rats, where they occurred almost exclusively during SWS and
rarely during REM sleep (Pavlides and Winson, 1989; Wilson and
McNaughton, 1994; Skaggs and McNaughton, 1996; Ribeiro et al.,
2004; Ji and Wilson, 2007; O’Neill et al., 2010). Specifically these
studies demonstrated that firing patterns that were present in
neuronal assemblies in the hippocampus during the exploration
of a novel environment were reactivated in the same sequential
order during subsequent SWS. Sleep-dependent neuronal reactivations
were also found in birds learning a tutored song, which
presumably represents a procedural type of learning (Margoliash
and Schmidt, 2010). The neuronal replay observed in adult birds
during nocturnal sleep after presenting the tutored song preceded
specific changes in the bird’s song performance occurring the first
time on the next day (Shank and Margoliash, 2009; Dave and
Margoliash, 2000). Rasch et al. (2007) demonstrated that reactivations
of hippocampus-dependent memories during SWS are
indeed causally linked to the consolidation of declarative memory
during sleep. They showed in humans that retention of spatial
memories (for card-pair locations) was enhanced after experimentally
inducing the reactivation of these memories by re-exposing
the subjects with memory-associated odors during SWS (Rasch
et al., 2007). Exposure to the odor-cues during SWS was associated
with an enhanced activation of the left anterior hippocampus
confirming that odor presentation indeed reactivated the hippocampal
representations (Rasch et al., 2007). Reactivations during
sleep also effectively enhance spatial memories when induced
by the presentation of auditory cues during SWS (Rudoy et al.,
2009).
System consolidation during sleep is assumed to rely on a
dialog between hippocampus and neocortex under control of
the EEG slow oscillations (∼0.75 Hz) that characterize SWS and
are mainly generated in the neocortex where they originate
mostly from frontal cortex areas (Massimini et al., 2004; Murphy
et al., 2009). The slow oscillation temporally groups neuronal
activity into global up states with wake-like levels of firing activity,
and down states of neuronal silence (Steriade et al., 1993).
Neuronal reactivations of memory representations in the hippocampus
are associated with the occurrence of so-called sharp
wave-ripples. The top-down driving influence of the depolarizing
up-state of slow oscillations on both the generation of hippocampal
sharp-wave ripples and thalamo-cortical spindles synchronizes
the occurrence of memory reactivations (and associated ripples)
in the hippocampus to the occurrence of ripples forming socalled
spindle–ripple events (Clemens et al., 2011; Ji and Wilson,
2007; Sirota et al., 2003; Siapas and Wilson, 1998). Spindle–ripple
events have been proposed as a mechanism for the facilitation
of the integration of reactivated hippocampal memory information
into neocortical storage sites (Fig. 1; Mölle and Born, 2009;
Diekelmann and Born, 2010). The importance of slow oscillations
and spindles for processes of memory consolidation has
been confirmed in a number of recent studies in adults (Wilhelm
et al., 2011; Gais et al., 2002; Mölle et al., 2009; Marshall et al.,
2006).
1720 I. Wilhelm et al. / Neuroscience and Biobehavioral Reviews 36 (2012) 1718–1728
Fig. 1. Active system consolidation during sleep. (A) During slow wave sleep (SWS) memories newly encoded into a temporary store (i.e., the hippocampus in the declarative
memory system) are reactivated to be redistributed to the long-term store (i.e., the neocortex). (B) System consolidation during SWS relies on a dialog between neocortex
and hippocampus under top-down control by the neocortical slow oscillations (red). The depolarizing up phases of the slow oscillations drive the repeated reactivation of
hippocampal memory representations together with sharp-wave ripples (green) in the hippocampus and thalamo-cortical spindles (blue). This synchronous drive allows for
the formation of spindle–ripple events where sharp-wave ripples and associated reactivated memory information becomes nested into single troughs of a spindle (shown
at larger scale). Spindle–ripple events are considered a mechanism that supports the integration of reactivated memory information into the neocortex.
Adapted from Born and Wilhelm (2011).
3. The role of sleep on processes of memory consolidation
in children and infants
3.1. Declarative memory
Declarative memories are memories for facts and events that
are explicitly encoded and later on can be consciously recollected.
Encoding of declarative memory during the initial learning episode
is thought to essentially rely on the hippocampus and closely connected
regions of the medial temporal lobe (Squire et al., 1993;
Eichenbaum, 2006). It is well known that sleep changes fundamentally
during development (Ohayon et al., 2004; Grigg-Damberger
et al., 2007). Importantly, amplitude and slope of slow waves as well
as slow wave activity (SWA; EEG spectral power between 0.5 and
4 Hz, including both <1 Hz slow oscillation and 1–4 Hz delta activity)
increases until the beginning of puberty at the age of 10–12
years and remarkably decreases thereafter (Jenni and Carskadon,
2004; Campbell and Feinberg, 2009; Kurth et al., 2010). Because
SWA was shown to be causally related to the consolidation of
declarative memory material in adults (Marshall et al., 2006; Rasch
et al., 2007; Mölle et al., 2009), it was hypothesized that the effect of
sleep on the consolidation of declarative memories might be even
greater in children.
A first study of sleep-associated declarative memory consolidation
tested 9–12 years old children on two conditions: In the
sleep–wake condition, the children learnt 40 word-pairs in the
evening and cued recall was tested the first time in the next morning
after a 12-h retention interval of nocturnal sleep, and a second
time in the next evening after a second 12-h retention interval
filled with daytime wakefulness (Backhaus et al., 2008). In the
wake–sleep condition, children learnt the task in the morning and
recall was tested first in the following evening and again, after nocturnal
retention sleep, in the next morning. Recall of the word
memories was significantly improved after the sleep retention
intervals, independently of whether sleep occurred immediately
after learning (sleep–wake condition) or after a period of daytime
wakefulness (wake–sleep condition; Fig. 2). In the latter condition,
retention sleep produced a significant gain in the number of
recalled word pairs when retrieval performance after sleep was
compared with that before. Retention of word-pairs across the
sleep interval was positively associated with the time spent in
non-rapid eye movement (REM) sleep and negatively related to
the time in REM sleep during the night, in both the sleep–wake
and wake–sleep condition (Backhaus et al., 2008). The beneficial
effect of sleep on the consolidation of declarative materials in children
was confirmed in a later study testing visuo-spatial memories
in a 2D object-location task similar to the game “Concentration”
(Wilhelm et al., 2008). Remarkably, although in those latter experiments,
the amount of SWS during the experimental nights was
on average more than twofold higher in the children than in the
adults, the size of the sleep effect on memory retention was closely
comparable between both age-groups. In rats, the process of system
consolidation is boosted by the presence of an associative
schema in long-term memory, into which new information can
be integrated (Tse et al., 2007, 2011). Hence, it could be argued
that children, despite higher amounts of SWS, do not show superior
declarative memory consolidation because of the presence of
fewer schemata and knowledge in long-term memory available to
adapt the newly learnt information. Thus, it remains open whether
or not the effect of sleep on consolidation of declarative memory,
due to the preponderance of SWS, is stronger in children than in
adults. To explore this issue, studies need to be performed comparing
sleep-dependent memory consolidation in children and adults
with task material that is as novel for adults as it is for children.
In contrast to adults, the adolescent’s brain seems to be highly
capable of compensating for effects of sleep restriction, possibly
by flexibly increasing the depth of sleep during the remaining
sleep period (Voderholzer et al., 2011). In this study, 14–16 years
old adolescents were tested for impairments in sleep-dependent
declarative (lists of word-pairs) and procedural memory consolidation
(mirror tracing task) as well as for executive functions (i.e.
divided attention, working memory, psychomotor speed) during
restriction of sleep to up to 5 h on 4 consecutive nights. Performance
in all these tasks was not affected by the experimental
sleep curtailment, neither after 2 nights of recovery sleep nor
after 4 weeks, excluding any short or long-term effect of sleep
restriction on memory consolidation. However, the adolescence
showed also a remarkable increase in the proportion of SWS during
this period which could have nullified effects of reduced sleep
time.
I. Wilhelm et al. / Neuroscience and Biobehavioral Reviews 36 (2012) 1718–1728 1721
Fig. 2. Sleep-dependent declarative memory consolidation in children. Declarative memory was tested using the word paired associates task (consisting of 40 word-pairs).
During learning, the word-pairs were presented on a computer screen, which was followed by a cued recall test. Presentation of the word-pairs was repeated until a learning
criterion of 50% correctly recalled word-pairs was reached. Bottom panel illustrates procedure: in the sleep–wake condition, children learned the word-pairs in the evening
before sleep and delayed recall was tested first the next morning after a retention interval of nocturnal sleep, and a second time in the following evening after a retention
interval of daytime wakefulness. In the wake–sleep condition, children learned the word-pairs in the morning and delayed recall was tested first in the next evening after a
retention interval of daytime wakefulness, and then the second time in the next morning after a sleep retention interval. Only during the learning phase, but not at the 1st or
2nd delayed retrieval test, children received feedback upon their response by subsequent presentation of the correct response word (for 1 s). Top bar graphs show results:
Performance at the 1st recall test was significantly better when this occurred after a sleep retention interval than after a wake retention interval. Performance at the 2nd
recall test significantly increased retention performance (with reference to performance at 1st recall) only when the retention interval between both recall tests was filled
with sleep, but not if the children remained awake in this interval. Retention performance is indicated by the difference in correctly recalled words at the 1st/2nd recall
minus the number of words recalled at the criterion trial during learning.
Data are from Backhaus et al. (2008).
3.2. Emotional memory
We refer here to emotional memories as memories for events,
which are associated with an affective response (e.g. negative or
positive feelings, facial and bodily responses). Encoding of such
memories typically involves the amygdala, in addition to the
hippocampus-dependent declarative memory system. A preferential
storage of emotional memory contents is highly adaptive in
order to avoid possibly threatening situations in the future. Emotional
events are encoded more deeply than neutral events, and
from studies in adults there is also evidence that the consolidation
of emotional memories during sleep is superior to that of neutral
materials, indicating that sleep is actively involved in the selection
of highly relevant memories (Wagner et al., 2001; Payne et al., 2008;
Hu et al., 2006).
In a first developmental study, Prehn-Kristensen et al. compared
the effects of sleep on emotional and neutral memory consolidation
in a group of healthy 10–12 years old children and adults using pictures
from the International Affective Picture System (IAPS). In line
with the above mentioned studies in adults, sleep preferentially
benefited recognition memory for emotionally arousing pictures
whereas in both age groups the effects of sleep on recognition of
neutral pictures was negligible when compared with wakefulness
during the retention interval. Importantly, the emotional enhancement
(i.e., the superior retention of emotional over neutral items)
was even greater in children than in the adults indicating that the
selection of relevant memories during sleep is even more effective
during early life (Prehn-Kristensen et al., unpublished results).
That in these studies contrasting the effects of sleep on emotional
versus neutral memories the effect of sleep on consolidation of
neutral materials often failed to reach significance should not be
used to infer that the strengthening effect of sleep on these neutral
memories is of a small magnitude in general. In fact, such results
rather point to a trade-off accompanying sleep’s selectivity in memory
consolidation such that when overnight retention is tested for
neutral and emotional memories simultaneously, the preferential
enhancement of emotional memory by sleep in parallel produces a
diminution of the effect on the neutral material.
3.3. Procedural memory
The majority of developmental studies concerned with the
effects of sleep on memory consolidation examined procedural
memories. Procedural memories are memories for skills and habits
that are acquired through repeated practice, and basically belong
to the category of non-declarative memory (Squire and Zola, 1996;
1722 I. Wilhelm et al. / Neuroscience and Biobehavioral Reviews 36 (2012) 1718–1728
Cohen and Squire, 1980). Sensorimotor skills form a major part of
everyday life activities like writing, riding a bicycle, driving a car
and playing a music instrument, with some of these basic skills
being acquired during early development like learning to walk and
to speak. A great number of studies in adults demonstrated that
sleep after training a new motor skill benefits its consolidation as
indicated behaviourally by a gain in skill performance (i.e., a faster
and more accurate performance at retest compared to performance
before sleep) and by a stabilization of the skill memory against disturbing
influence of training a similar interfering task (Fischer et al.,
2002; Korman et al., 2007; Ellenbogen et al., 2006b; Plihal and Born,
1997).
Fischer et al. (2007) compared the effects of sleep on motor skill
memory in a sample of 7–11 years old children and adults, using
the serial reaction time task (SRTT, Fig. 3). The SRTT requires the
subject to press as fast as possible a repeated cued sequence of
buttons while the subject is not aware of the underlying sequence
grammar, i.e., that the cued sequence follows distinct regularities.
Learning the sequence is thus implicit and manifests itself
in faster reaction times to cues that follow the sequence grammar
compared to reaction times to a random sequence of cues.
Astonishingly, in the children, sleep did not support but instead
even impaired skill performance on the SRTT, indicating an impairing
effect on the sensorimotor representations underlying the
implicit sequence knowledge (Fischer et al., 2007). Following the
wake retention period, implicit performance on the SRTT remained
unchanged. This pattern clearly differed from that in adults who significantly
improved in implicit SRTT performance across overnight
sleep but showed deteriorated performance after the retention
period of wakefulness. Two recent studies (Prehn-Kristensen et al.,
2009; Wilhelm et al., 2008), confirmed this lack of sleep-dependent
gain in implicit motor performance in children, using two other
procedural tasks which in adults are well-known to profit from
post-learning periods of sleep, i.e. the finger sequence tapping task
and the mirror tracing task (Walker et al., 2003; Plihal and Born,
1997). The absence of a sleep-dependent gain in skill memories
in children is the more striking as the neuroanatomical structures
underlying procedural memory formation mature quite early during
development, i.e., within the first 3 years of life (Casey et al.,
2005; Gogtay et al., 2006).
Interestingly, a lacking gain in sensorimotor performance across
sleep has been also revealed in studies of juvenile birds (zebra
finches) learning a tutored song (which is an animal model of language
learning; Deregnaucourt et al., 2005). Compared with song
performance in the evening, the juvenile birds showed more variable
and deteriorated song performance in the morning after sleep,
and the birds regained original performance levels only after substantial
practice during daytime. Adult birds that were kept in
acoustic isolation until training started at day 90 after hatching did
not show this sleep associated deterioration in song performance.
Surprisingly, in the juvenile birds those showing acutely the greatest
morning deterioration in performance in the beginning of the
3-months study period, were those which achieved the best song
performance at the end of the study period, indicating that the deterioration
of song performance in the morning after sleep is linked to
some kind of song-memory forming process during sleep. In adult
birds, neurons of premotor and motor structures of the bird’s vocal
song control system, i.e. the nucleus HVC and the robust nucleus of
the arcopallidum (RA) show replay of the tutored song during sleep
that produces changes in the song representation as well as in subsequent
song performance the next day (Shank and Margoliash,
2009), and basically similar adaptive processes may occur upon
replay activity during sleep in juvenile birds although, along with
the deterioration in song structure, HVC neurons show a general
decline in burst activity across sleep in juvenile birds (Day et al.,
2009). Importantly, replay activity in premotor neurons of the song
control system appears to be driven not only by activity related to
the sensory template of the tutor song but also by the auditory feedback
from the bird’s own singing, as replay is drastically reduced in
surgically muted birds. Offline reprocessing in sensorimotor nuclei
during sleep may become necessary because of the inability of premotor
and motor regions of the song control system to acutely
integrate the two types of complex sensory inputs, i.e., the tutored
song and feedback from the bird’s own singing (Margoliash and
Schmidt, 2010; Gobes et al., 2010; Konishi, 2004). Because early
reactivated sensory representations and sensorimotor feedback as
experiencedduring actual singing are poorly correlated during song
development in juvenile birds, the replay occurring in the absence
of supervision by any immediate actual auditory song feedback may
manifest itself in a deteriorated song performance in the morning
after sleep. This view also implicates that the overnight deterioration
in song performance observed only in young birds, is at
least partially due to a less established sensorimotor integration in
young birds preventing an immediate fine-tuning of premotor and
motor representations on the basis of feedback signals from the
bird’s own song behavior, neither acutely during wakefulness nor at
replay during sleep. For a similar reason, i.e., due to basically diminished
capabilities to immediately and accurately integrate complex
sensory and sensorimotor inputs into premotor programs, sleepassociated
reactivations, in the beginning of training, may also fail
to produce overnight gains in skill performance during development
in humans. Recent data in humans indicate that sleep indeed
produces a significant enhancement performance on a motor finger
sequence tapping task after the children had received an extended
pre-training over several days (Wilhelm et al., in press). Thus, the
capability to further improve motor performance by the off-line
integration of sensory and sensorimotor inputs into premotor programs
might essentially depend on the presence of already quite
elaborate representations. A related yet unresolved question in this
context is, whether in children, like in zebra finches (Deregnaucourt
et al., 2005), a stronger sleep-induced disturbance of skill at an early
stage of training, is predictive for a higher level of performance that
is achieved at a later stage of training.
3.4. Extraction of explicit knowledge from procedural skill
Taken together, the data discussed in the foregoing section
consistently indicate that procedural memories are differentially
processed in children and adults, although researchers are far
from understanding the underlying mechanisms. Whereas sleepinduced
deteriorations in song performance in juvenile birds were
related to the developmentally diminished capabilities to accurately
integrate complex sensory (feedback) inputs into the song
motor representation, in children lacking performance gains after
sleep were ascribed to a strong competitive interaction between
explicit (i.e., declarative) and implicit components within a motor
task in children (Fischer et al., 2007; Wilhelm et al., 2008). Whereas
procedural memories were originally conceptualized as being completely
independent of any consciousness; i.e., they are implicit
(Squire and Zola, 1996; Cohen and Squire, 1980), more recent
studies indicate that explicit and implicit aspects operate in parallel
in motor memory tasks (Schendan et al., 2003; Shanks and
Johnstone, 1999; Willingham, 1998; Ashe et al., 2006). Explicit
knowledge can deteriorate implicit task performance manifesting
itself in a slowing of reaction times preferentially at the earlier
stages of motor learning, when a task is difficult or when cognitive
resources are less available. This competitive interaction between
explicit declarative and implicit procedural task aspects was found
during acquisition (Fletcher et al., 2005; Poldrack et al., 2001;
Albouy et al., 2008; Stefaniak et al., 2008), but it can extend to processes
of memory consolidation (Brown and Robertson, 2007a,b;
Robertson, 2009) and also affects retrieval (Wagner et al., 2004;
I. Wilhelm et al. / Neuroscience and Biobehavioral Reviews 36 (2012) 1718–1728 1723
Fig. 3. Sleep-dependent procedural memory consolidation in children and adults using the serial reaction time task (SRTT). (A) On the SRTT subjects were presented six
horizontally arranged white boxes. The target cue consisted of a white star, which successively appeared in one of the boxes following a repeated 12-element probabilistic
sequence. The subject’s task was to react as fast and as accurately as possible to each target position by pressing the spatially corresponding response key, as soon as the cue was
presented. (B) The sequence of target locations was based upon a set of probabilistic rules such that each of two successive target locations constituted the temporal context
that legally could be followed by one of two possible target locations, each occurring with a probability of 50%. In the illustrated example sequence the temporal context ‘D’,
‘A’ (gray fields) could be legally followed by position ‘C’ or ‘F’. (C) SRTT performance before (learning) and after (retesting) retention intervals of sleep and wakefulness in
children and adults. At learning, subjects performed two blocks of 194 target positions, each containing 15% non-grammatical target positions. Bars represent, as a measure of
implicit knowledge of the sequence grammar underlying the SRTT, mean reaction time differences between grammatical and non-grammatical target positions. This reaction
time difference was significantly decreased at retesting (with reference to performance at learning) when children had slept during the retention interval, indicating that
sleep deteriorated implicit sequence knowledge in the children. By contrast, in adults sleep during the retention interval improved implicit sequence knowledge. The wake
retention interval did not affect implicit sequence knowledge in children, but in adults distinctly diminished implicit sequence knowledge at retesting. *p < 0.05, (*)p < 0.07
compared with performance at learning, ††
p < 0.01 compared with the wake condition.
Data are from Fischer et al. (2007).
Fischer et al., 2006). Because of their great amounts of SWS, sleep in
children might preferentially strengthen hippocampus-dependent
explicit aspects in a skill representation thereby crucially disturbing
implicit aspects. In a recent study, we tested this hypothesis using
a coarse motor memory task resembling the SRTT, i.e. the ‘buttonbox
task’ (Wilhelm et al., submitted for publication). During the
learning session taking place under implicit conditions, children
and adults repeatedly pressed a sequence of buttons according to
an underlying 8-elements sequence, without being aware of this
sequence. After a night of sleep or after a parallel daytime wake
interval, the subject’s explicit knowledge about the SRTT sequence
was explored using a generation task where the subject was asked
to point at the buttons in the order they were cued at the original
SRTT training (under implicit conditions). The number of correct
transitions from one to the next button predicted on this generation
task was used as measure of explicit sequence knowledge.
Sleep benefited the generation of explicit knowledge in both agegroups.
However, this benefit was strikingly greater in children
than in adults. Importantly, explicit knowledge after sleep in children
was also profoundly enhanced in comparison to what a control
group of children showed when tested immediately after training,
indicating that it is indeed sleep which supports the extraction of
explicit from implicit knowledge. Superior explicit knowledge after
sleep correlated with the amount of SWA in both age groups.
These findings are well in line with a previous study in adults
showing that those subjects who slept after implicitly practicing
an arithmetic number reduction task comprising a hidden rule, at
a later re-test gained insight into this hidden rule with a twofold
higher probability than subjects who had stayed awake after practicing
the task (Wagner et al., 2004). The emergence of insight into
this task is promoted by SWS-rich early nocturnal sleep in adults
rather than by late REM-rich sleep, indicating that SWS is critically
involved in the extraction of explicit knowledge (Yordanova et al.,
2008).
The learning of language and underlying grammar in infants
is a process that shares essential features with the sleep-induced
extraction of regularities and rules observed in tasks like the SRTT.
Recent studies have provided first evidence that sleep preferentially
supports the extraction of grammatical aspects rather than
the memory for words in language learning infants. Gomez et al.
(2006) familiarized 15-months old infants in a learning phase with
auditory strings of words of an artificial language. The infant’s
orienting response, i.e. turning his/her head toward familiar and
unfamiliar strings, was used to assess delayed retrieval. Compared
to a non-napping control group, children who had napped after
learning appeared to be more able to abstract a rule-like pattern
underlying the strings of words. However, signs of correct remembering
of the presented words were enhanced in the wake group
(Gomez et al., 2006). The authors replicated and extended these
results in a second study employing the same task and the same
study design but a retention interval of 24 h (Hupbach et al., 2009).
Although orienting is a well-known hippocampus-dependent function
(Sokolov, 1975), it remains to be elaborated to what extent
the sleep-induced extraction of grammatical structure in infants
involves the hippocampus-dependent declarative memory system.
Overall, the findings indicating a facilitating effect of sleep
on the generation of hippocampus-dependent explicit knowledge
from an implicitly learned motor task are in line with the general
assumptions of system consolidation theory as specified by
the more recently proposed ‘transformation hypothesis’ (Frankland
and Bontempi, 2005; Winocur et al., 2010; Diekelmann and Born,
2010). This theory postulates that newly acquired memories are initially
stored into a temporary buffer, i.e., the hippocampus in the
declarative memory system. During sleep – and here in SWS – these
1724 I. Wilhelm et al. / Neuroscience and Biobehavioral Reviews 36 (2012) 1718–1728
memories are reactivated to be redistributed and integrated with
the existing network of memories within the neocortex. In the process
of system consolidation fresh memory representations are not
only strengthened but also become qualitatively transformed and
reorganized (Born et al., 2006; Payne and Kensinger, 2010). During
SWS memory reactivations spreading from hippocampus toward
the neocortex might mediate a restructuring of the representation
so as to produce an increased binding into neocortical, particularly
prefrontal circuits (Frankland and Bontempi, 2005; Darsaud
et al., 2011) and such restructuring might in fact underlie the sleepdependent
generation of explicit knowledge. Thus, sleep does not
only strengthen a memory representation in the way it exists but,
by extracting invariant and relevant features of the representation
and its adaptation to pre-existing schemata, brings about changes
in its quality, with this effect being greater during childhood than
adulthood.
3.5. Wake consolidation and the role of the pre-sleep
performance level
It could also be argued that the missing sleep-induced gain
in motor performance in children does not primarily reflect an
altered consolidation during sleep but is due to an enhanced capacity
to consolidate newly acquired memories during wakefulness, as
respective studies often compare retention performance after sleep
with those after wake retention intervals. Evidence in support of
this view came from a recent study testing the stability of newly
encoded motor memories after wake retention intervals in different
age groups (Dorfberger et al., 2007). In children (aged 9 years)
newly acquired finger sequence tapping representations after a 2-h
wake retention period were less susceptible to interference from
learning a different sequence than in adolescents (aged 17 years)
or adults, indicating that processes of motor memory consolidation
during waking follow rather fast kinetics in children. However, this
study did not compare the stabilization of motor memories during
waking with that after retention intervals of sleep, which prevents
any conclusions with regard to differential effects originating from
the two brain states. In fact, observations in adults suggest that
the process of stabilizing a motor representation is even further
accelerated by sleep, compared with wakefulness (Korman et al.,
2007).
Motor performance in children is much slower and less automated
than in adults (Thomas et al., 2004; Fischer et al., 2007;
Dorfberger et al., 2007). This is of importance because the performance
level at learning has repeatedly been shown to modulate
processes of sleep-dependent memory consolidation in adults.
Intermediate performance levels are considered most effective in
this context (Diekelmann et al., 2009; Albouy et al., 2008; Kuriyama
et al., 2004). Against this background, a basic question arises about
the nature of the lacking sleep-induced gain in motor performance
in children: does this missing profit from sleep represent an ubiquitous
and unchangeable characteristic of the immature brain, or
does it depend on behavioral features specifically linked to a task in
which children are usually less experienced but which can be modified
by training. The later alternative predicts that sleep would be
beneficial to motor memories also in children if pre-sleep performance
can be enhanced to a level comparable with that in adults.
Hence, the purpose of a recent study was to compare motor skill
across 120-min retention periods of sleep and wakefulness in children
(aged 4–6 years) after experimentally increasing performance
at learning by manipulating the amount of training (Wilhelm et al.,
in press). In two corresponding control groups of adults, motor performance
was either kept at a low level by restricting the amount
of training to a minimum, or brought to a quite high performance
level by providing increased amounts of training. Results confirmed
that sleep supports the gain in motor performance at an
intermediate performance level, i.e., in children after high amounts
of training and in adults after restricted training. However, sleep did
not improve skill performance in children whose pre-sleep performance
was kept at a low level or in highly trained adults (Fig. 4).
Getting back to the initial question, these data indicate that the
lacking gain in motor performance which was found in the first
studies in children is not a general phenomenon inextricably linked
to the developing brain but is due to a currently low level of performance
on a specific task. It seems that motor performance in
children only after extensive training reaches a level of strength at
which sleep-dependent benefits directly translate into benefits in
skill and reaction times rather than in a disruption of skill due to a
predominant gain in explicit task knowledge.
4. Sleep-dependent memory consolidation in children
suffering from ADHD
4.1. Why studying sleep-dependent memory consolidation in
ADHD patients?
The key symptoms in patients suffering from attentiondeficit/hyperactivity
disorder (ADHD) are inattention, hyperactivity
and impulsivity (American Psychiatric Association, 2000). The
sleep architecture in terms of the macro structure of sleep appears
to be not consistently altered in children with ADHD (Cortese et al.,
2009), although these patients often experience multiple sleep disturbances,
such as delayed sleep onset, sleep or bedtime resistance,
prolonged tiredness upon waking and daytime sleepiness (Cortese
et al., 2009; Konofal et al., 2010). When experimentally invoked
in healthy subjects, such alterations of sleep can induce ADHD-like
behavior, indicating that sleep disturbances might contribute to the
maintenance of ADHD (Gruber et al., 2011; Paavonen et al., 2009;
Steenari et al., 2003). The primary cause of the disease, however, is a
malfunction of the prefrontal cortex. There is convergent evidence
from a great number of imaging and neuropsychological studies
indicating a profound deficit in the prefrontal cortex together with
striatal brain regions in patients with ADHD. This deficit, amongst
others, expresses itself in a volume reduction and decreased activation
in these regions during task execution (Bush et al., 2005;
Rubia et al., 1999; Shaw and Rabin, 2009; Zang et al., 2005). On the
background of this evidence, ADHD can serve as a model to scrutinize
the contributions of the prefrontal cortex to sleep-dependent
memory consolidation.
Based on studies in healthy adults, it was argued that the prefrontal
cortex during the encoding of memories in the wake phase
is involved in a tagging of those memories that are relevant for
the subject’s future and, therefore, are preferentially consolidated
for the long-term during subsequent sleep (Diekelmann and Born,
2010; Wilhelm et al., 2011). This in mind, it can be hypothesized
that such tagging of memories is diminished in ADHD patients and
that consequently sleep in these patients does not adequately discriminate
between relevant and less relevant memories. Given that
the frontal cortex is also the main source of slow oscillations which
hallmark the EEG during SWS (Massimini et al., 2004; Murphy
et al., 2009) the study of ADHD patients can additionally provide
important information on the role of this sleep stage for the consolidation
of declarative and procedural memories. Although the
total time spent in SWS during the night does not differ between
ADHD patients and healthy subjects, its stability as reflected by
the cyclic alternating pattern in slow wave activity appears to
be reduced (Miano et al., 2006), and specific features such as
amplitude and functionality of slow oscillations might be altered
in these patients although this has not been thoroughly studied
so far.
I. Wilhelm et al. / Neuroscience and Biobehavioral Reviews 36 (2012) 1718–1728 1725
Fig. 4. Sleep-dependent motor memory consolidation at different amounts of training on the button-box task. The button box is a white 50 cm × 22 cm × 7 cm box with
eight colored buttons placed on its upper panel in two rows that are consecutively flashed up according to a repeating 8-elements sequence. Subjects were instructed to
press the button flashing up as fast as possible. Each block during training and retrieval testing consists of five sequences with a 20-s break between blocks during which
the subject received feedback on his/her individual performance level during the preceding block. (A) Motor performance in low-performing and intermediate-performing
children (filled and open circles, respectively) and intermediate-performing and high-performing adults (filled and open triangles, respectively) during training and first
retrieval (Retrieval 1) that took place 30 min after the training phase. The amount of finger tapping training received before the experimental retention interval was in
low-performing children 13 30-s blocks, in intermediate performing children 33 blocks, in intermediate performing adults 13 blocks, and in high performing adults 4 blocks.
(B) Motor memory consolidation. Gains in motor performance after 2-h retention intervals filled with sleep (black bars) and wakefulness (white bars) in low-, intermediateand
high-performing subjects indicated by the percent difference in performance between a first retrieval test before the retention interval and a second retrieval test after
the retention interval (with performance at the first retrieval set to 100%). **p < 0.01, *p < 0.05, for pairwise comparisons between sleep and wake conditions.
Data are from Wilhelm et al. (in press).
4.2. Sleep-dependent memory consolidation in patients with
ADHD
Indeed, consolidation of memory during sleep in ADHD patients
appears to deviate from that in healthy controls. We compared
the retention of declarative memories for pictures across retention
intervals of nocturnal sleep and of daytime wakefulness between
ADHD children (aged 10–16 years) and healthy controls (Fig. 5;
Prehn-Kristensen et al., 2011a). Retrieval testing following the
retention intervals revealed that both subject groups recognized
a greater number of previously presented pictures after retention
sleep compared to wakefulness. However, the impact of sleep
on memory performance was greater in healthy controls than in
ADHD patients. Although slow oscillation power during NonREM
sleep in the retention intervals did not differ between the groups, a
significant positive association of sleep-dependent memory gains
with slow oscillation power was observed only in the healthy subjects,
pointing toward a reduced functionality of slow oscillations
in ADHD.
Whereas the impact of sleep on declarative memories is smaller
in ADHD children compared to healthy controls, overnight sleep
did benefit procedural motor performance in these patients (PrehnKristensen
et al., 2011b). In this study, ADHD patients improved in
performance on the button-box task to a greater extent after offline
periods of sleep compared to wakefulness, whereas motor performance
in healthy children did not differ between both conditions.
As the benefit from sleep was assessed with reference to corresponding
performance improvements across the wake retention
interval, which were lower in the ADHD children than controls, this
study cannot exclude contributions of an altered wake processing
of memories to the pattern of skill performance in the ADHD. Nevertheless,
the findings overall indicate that the sleep-dependent
consolidation of declarative and procedural memories in ADHD is in
stark contrast to that found in healthy children. Indeed, these findings
are clearly in line with our view derived from the investigation
of healthy children discussed above, namely that the consolidation
of both declarative and procedural aspects of memory during
sleep is interlinked. The impaired consolidation of hippocampusdependent
memories during sleep in ADHD patients might reduce
the competitive interaction with processes strengthening implicit
procedural aspects in the skill representation, thus unmasking the
emergent offline gains in procedural motor performance at retest
after sleep in these subjects.
Boosting slow oscillations during NonREM sleep in adults by the
transcranial application of electrical potentials fields (oscillating
at the 0.75 Hz slow oscillations frequency) significantly enhanced
the retention of word-pairs the subjects had learned before sleep,
indicating that slow oscillations are causally related to processes
of declarative memory consolidation (Marshall et al., 2006). In
order to investigate the role of slow oscillations for processes of
memory consolidation during development, we applied the same
protocol of sleep-associated transcranial electrical stimulation in
children suffering from ADHD (Prehn-Kristensen et al., unpublished
results). Prior to sleep, the children acquired declarative
(visuo-spatial object-locations) and procedural memories (finger
sequence tapping). Retrieval performance after sleep was compared
between slow oscillation stimulation and a sham control
condition. Preliminary analyses revealed that in ADHD children,
similar to the findings in healthy adults (Marshall et al.,
2006), slow oscillation stimulation during post-learning sleep
improved retention of declarative memories. Interestingly, with
respect to the consolidation of procedural memories, transcranial
electrical stimulation simultaneously reduced sleep-induced
gains in performance accuracy, compared to the sham condition.
These findings suggest slow oscillations might also contribute
to the altered processes of sleep-dependent memory consolidation
in ADHD (as reflected by inferior sleep-induced changes
in declarative memory). The applied electrical stimulation could
improve the functionality of slow oscillations thereby normalizing
memory consolidation during sleep in ADHD patients toward
predominant consolidation of hippocampus-dependent declarative
aspects in memory. However, healthy control children
were not included in this study rendering these conclusions
preliminary.
1726 I. Wilhelm et al. / Neuroscience and Biobehavioral Reviews 36 (2012) 1718–1728
Fig. 5. Sleep-dependent declarative memory consolidation in young patients with attention-deficit/hyperactivity disorder (ADHD). Twelve patients with ADHD and twelve
healthy controls (aged 10–16) were shown two sets of pictures each containing 180 emotional and 180 neutral pictures taken from the International Affective Picture
System. During learning (120 pictures) participants had to rate the emotional arousal of the pictures; at a delayed recognition test old (120) and new (90) pictures were
presented in random order and the subject had to indicate for each picture whether it was old or new. In the sleep condition, learning took place in the evening and picture
recognition was tested in the morning after nocturnal sleep; in the wake condition, learning took place in the morning and recognition was tested after a retention interval of
daytime wakefulness. (A) Recognition accuracy in both groups after sleep and wake retention intervals. Although both, ADHS patients and controls improved in recognition
accuracy to a greater extent after sleep than wakefulness, the benefit from sleep in recognition accuracy was significantly lower in the ADHD patients compared to the
controls. *p < .05; ***p < .001, for comparisons between sleep and wake conditions. (B) Correlations between the sleep-associated enhancement in recognition accuracy (i.e.,
the individual difference between recognition accuracy in the sleep and wake condition) and slow oscillation power (<1 Hz in ␮V2
) during NonREM sleep. Bold circles and
solid regression line refer to ADHD children; triangles and dashed regression line refer to healthy controls. Only in healthy controls slow oscillation power was correlated
with sleep-associated improvement in recognition accuracy. Note: correlation coefficients between ADHD and healthy controls differ significantly.
Data are from Prehn-Kristensen et al. (2011a).
Sleep in adults preferentially consolidates memories that are
of future relevance possibly by a SWS related reprocessing of
these memories (Wilhelm et al., 2011; Fischer and Born, 2009;
Diekelmann et al., submitted for publication). As mentioned, this
selectivity in memory consolidation during sleep is presumably
achieved by a prefrontal marking of hippocampus-dependent
memories during encoding, a mechanism that could likewise be
involved in the preferential consolidation of emotional over neutral
memories during sleep (e.g., Wagner et al., 2001; Payne et al.,
2008; Hu et al., 2006). A prefrontal contribution to the enhanced
consolidation of emotional materials is in fact indicated by recent
experiments in ADHD children who – presumably due to a dysfunctional
prefrontal control of memory processing during both
encoding and off-line consolidation – did not show the normal
sleep-associated enhancement for the consolidation of emotional
memories (Prehn-Kristensen et al., unpublished results). Such
deficits in the consolidation of emotional memory during sleep
might contribute to an exacerbation of symptoms of disruptive
behavior disorders (such as conduct disorder, oppositional defiant
disorder) often reported in ADHD (Maughan et al., 2004),
although this issue requires further studies. Collectively, these
studies exploiting ADHD as a model of prefrontal dysfunction support
the notion that normal development is characterized by an
enhanced consolidation of hippocampus-dependent memory during
sleep, whereby the effective regulation of these consolidation
processes that take place during SWS, essentially relies on the prefrontal
marking of memories to be strengthened by sleep.
5. Conclusion
The studies discussed here confirm the importance of sleep for
processes of memory consolidation in children and infants. However,
sleep-dependent memory consolidation during development
does not appear to be entirely different from that in adults but
is based on similar principles. Rather, due to the great amounts
of SWS, consolidation during sleep is more efficient. These great
amounts of SWS with prevalent EEG slow oscillation activity in
children promote the preferential consolidation of memories in the
hippocampus-dependent declarative memory system whereby,
compared with adults’ sleep, sleep in children produces greater
gains of declarative knowledge, which can express in quantitative
(increased number of words recalled) and qualitative (enhanced
implicit-to-explicit conversion of knowledge) changes in memory
performance (e.g., Backhaus et al., 2008; Wilhelm et al., submitted
for publication). Investigations in children with ADHD as a model
of impaired prefrontal function, do not only underscore the role
of SWS for the consolidation of hippocampus-dependent memory
but also the contribution of the prefrontal cortex to this process.
Explicit encoding of hippocampus dependent memories relies on
the prefrontal cortex, which appears to tag these memories during
encoding thereby facilitating their access to consolidation during
subsequent sleep. In ADHD children, the prefrontal marking of
memories during waking or preferential selection of hippocampal
memories for consolidation during sleep slow oscillation activity
(or both) may be compromised. Accordingly, they show diminished
benefits from sleep for declarative memories, and they are
also less able to select emotional over neutral memories for consolidation
during sleep. On the other hand, ADHD children display
a clear sleep-associated benefit for motor skills, which was lacking
in healthy children most likely because of the preponderance of
declarative memory consolidation. Indeed, findings in healthy children
highlight the strong competitive interaction between explicit
(declarative) and implicit (procedural) components of a memory
representation that persists during the sleep-dependent process of
consolidation. Healthy children, due to predominant SWS, show
preferential strengthening of declarative aspects in memory, and
only at advanced performance levels is there a direct profit of
motor skill (Wilhelm et al., in press). This predominant consolidation
of hippocampus-dependent declarative memory at the cost
of an immediate benefit in procedural skill that is seen during sleep
in healthy children finds a striking parallel in juvenile song birds
learning a song, whose performance on the tutored song deteriorates
across sleep rather than improving (Deregnaucourt et al.,
2005). It may in fact point at a principle function of sleep-dependent
memory formation as such offline-consolidation may be necessary
only in conditions where complex afferent patterns of sensorimotor
(feedback) stimulation cannot be effectively integrated online
into representations regulating efferent motor behaviors of similar
complexity. This is a hypothesis clearly in need of experimental
elaboration. However, children and infants who are in the very
I. Wilhelm et al. / Neuroscience and Biobehavioral Reviews 36 (2012) 1718–1728 1727
beginning of learning complex behaviors, may comprise a very
promising model for the study of this hypothesis.
Acknowledgments
The authors are grateful to Sabine Groch for her highly valuable
comments on previous versions of the manuscript. This work was
supported by grants from the DFG (SFB 654) and BMBF (F280125).
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