Review articles
 

By Dr. Mohammad Torabi Nami , Prof. Mohammad Reza Zarrindast
Corresponding Author Dr. Mohammad Torabi Nami
Institute for Cognitive Sciences Studies, Neuroscience Research Center, ICSS, 17Pezeshkpour St., Valiasr Ave. - Iran (Islamic Republic of)
Submitting Author Dr. Mohammad Torabi-Nami
Other Authors Prof. Mohammad Reza Zarrindast
ICSS, - Iran (Islamic Republic of)

BRAIN

Sleep, Memory, Consolidation, Emotion, Rapid eye movement

Torabi Nami M, Zarrindast M. Sleep and Memory Processing: A Solid Relationship. WebmedCentral BRAIN 2011;2(9):WMC002258
doi: 10.9754/journal.wmc.2011.002258
No
Click here
Submitted on: 25 Sep 2011 05:42:36 PM GMT
Published on: 26 Sep 2011 02:56:09 PM GMT

Abstract


The correlation between sleep and memory consolidation has recently drawn lot of attention and among these debates the link between the emotional memory and sleep, is of special note. Sleep is shown to importantly contribute to processes of memory. Sleep-dependent memory processing provides in the stabilization, enhancement, and consolidation of a wide range of memory types including declarative (explicit) and non declarative (implicit).These specific types of memory would be consolidated during sleep, associated with specific sleep stage. In reviewed studies, a broad range of perceptual and motor procedural tasks were shown to be  improved in performance after sleep.  Overnight improvement on a procedural task correlates with SWS and Sleep spindles are reported to be associated with improvement of motor sequence task. Sleep enhances declarative memory for emotional words and pictures. Emotions can also enhance memory consolidation. In many of reports, psychiatric disorders such as depression exhibit the predominance of REM sleep, suggesting hyperactivity of amygdala. It also has been declared that Sleep (nap) will enhance emotional memory consolidation and this emotional memory benefit will be positively correlated with REM sleep. It has been well documented in some investigations that Theta activity during REM sleep will be strongly associated with emotional memory enhancement and furthermore sleep can selectively enhance offline consolidation of motor and emotional memory. It’s of note that SWS improves sleep-dependent motor adaptation, while spindles facilitates sleep-dependent, motor sequence task. And importantly, Emotional memory enhancement is strongly associated with REM sleep activity, involving the right-dominant prefrontal theta activity.

Review


Background in neuroscience of sleep, with regard to learning and memory

A large number of evidence has accumulated that sleep contributes to both learning and memory, with increasing emphasis placed on the role of sleep in memory and plasticity ( Frank and Benington 2006; Wilhelm and others 2008;  Miyamoto and Hensch 2003). Among the multiple functions of sleep, its role in the establishment of memories is likely to have important aspect, in contrast of brain's normal processing of stimuli during wakefulness. The question of how sleep might contribute to human learning and memory has a long history, with a comment of ancient Roman rhetorician Quintilian in the first century of AD (Stickgold 2005). In the nineteenth century, the British psychologist David Hartley proposed that dreaming might strengthen associative memory within the brain. Testing Ebbinghaus's memory decay, Jenkins and Dallenbach demonstrated that night sleep was more beneficial for memory retention than an equivalent amount of time awake (Walker 2008). Followed by striking discovery of rapid eye movement (REM) sleep by Aserinsky and Kleitman in 1953, research began to verify that sleep, or even specific sleep of stage actively play a role in the memory processing (Walker 2005;Walker and Stickgold 2006).

The brain has a cycle through periods of different neural and metabolic activity, divided biological states into wakefulness and sleep. Sleep is composed of REM and NERM sleep, which alternate across the night in human, with NREM sleep further divided into stage 1 to 4. Stages 3 and 4 are the deepest stage of sleep, and are referred to collectively as slow wave sleep (SWS) on the basis  of the patterns of low- frequency cortical oscillations in the electroencephalogram (EEG) (Stickgold 2005; Born 2010). Sleep stages differ not only in the depth of sleep but also in the frequency, EEG oscillations, eye movements, muscle tone, involved dramatic change of neurochemistry and  regional brain activation. Thus sleep can be considered as a heterogeneous state, which either  does or does not affect memory processing. Each sleep stage holds a set of physiological and  neurochemical mechanism that may contribute to memory processing and plasticity (Walker and Stickgold 2004).

Memory categories

There  is more  than  a  single  type  of memory. Memories are commonly divided into declarative memories and non-declarative memories.  Declarative  memory can be considered as the consciously accessible memories of fact based information. Non-declarative memories are normally used without conscious recollection. Declarative memories are further divided into episodic memories and semantic memories ( Henke 2010). Episodic memories consist of specific events of one's past, semantic memories are general information and knowledge. Non-declarative memories are also divided into several subcategories, such as procedural skills.  In addition to speculum of memory systems, working memory is regarded as a specific process, implemented both the  temporally storage and manipulation of information. ( Fig.1)

Current neural models of declarative memory information focus on the critical importance of strictures in the medial temporal lobe, exclusively the hippocampus. In contrast, non-declarative memory includes procedural memory, through action and behavior, depending on diverse  neural components (Markowitsch and Staniloiu 2011;Born 2010).

Memory storage

There is no consensus on what "memory consolidation” means in terms of memory processing. After encoding, the memory representation can undergo several subsequent stages of development,  the commonly considered of which is consolidation. The term memory consolidation  originally referred to a process of memory stabilization, becomes increasingly resistant to interference. In other words, memory becomes more stable (Winocur and others 2010).

Recent findings have shown that consolidation can be thought as serving not only to stabilize memories, but also to enhance them. Although the stabilization process is likely to occur predominantly across time, the enhancement appears to occur during sleep. These additional memory consolidation process show the involvement of sleep dependence, occurring at the local  synaptic level and system-level organization (Frankland and Bontempi 2005).

Thus, consolidation appears to be expanded to include more than one phase of post-encoding memory processing, with each brain states such as wake and sleep. Through the consolidation process, a memory can be retained for days to years, which time it can be recalled (Henke 2010; Winocur and others 2010; Sara and Hars 2006; Kandel 2006).

It is important to note that there is no consensus on how many distinct post-encoding processes exist, of which integration of recent acquired information with past experiences and knowledge, reactivation and reconsolidation of memory through recall. It is also interesting to note that sleep  has been implicated in many of these steps (Walker and Stickgold 2004; Born 2010).

Sleep-dependent memory consolidation

A plethora of study has confirmed the beneficial effect  of sleep on learning, affecting the structure of sleep. The act of learning can affect sleep and produce changes in the subsequent sleep ( Fig.2) A period of post-learning sleep enhances retention of declarative information and improves performance of procedural skills. Using a variety of behavioral paradigms, evidence of sleep  dependent memory consolidation has been found in numerous species, including human being (Walker and Stickgold 2004).

Sleep after learning

A large number of early work investigating sleep and memory in human mainly focused on declarative tasks,  the results demonstrated that REM sleep plays a specific role in memory consolidation and that post-training REM increases reflect a homeostatic response to adjust the increased input (Gais and others 2006). Although REM sleep is considered as the critical period for memory processing, recent studies has shown the importance of NREM sleep, altering brain plasticity accordingly based on synaptic homeostasis hypothesis (Frank and Benington 2006; Peigneux and others 2004; Brand and Kirov 2011).

In a computerized finger-tapping task, sleep after leaning resulted in consolidated and enhanced motor skill memories. Motor skill performance (number and accuracy of key-press sequences completed) was tested following offline time delays. Walker et al. reported that large and significant enhancements in motor performance were observed after sleep; representing the  positive correlation with the amount stage 2 NREM sleep (Hotermans and others 2006; Walker 2008; Doyon and others 2009) .

Based on evidence that motor skill memories are consolidated across a night of sleep, daytime nap enhanced motor memory consolidation, exhibiting correlation with regional spindle activity (Mednick 2011; Walker 2008) .

In terms of declarative memory, several studies by Born and his colleagues demonstrated that the amount of slow wave sleep (SWS) was correlated with declarative memory consolidation. They  found improvement on a related word-pair associate task after early night of sleep, which consists of rich SWS stages. The experiment of Direct Current Stimulation (DCS) demonstrated 0.75HZ slow oscillation induce by DCS increased not only the amount of SWS but also the retention of factual memories, suggesting a causal benefit of SWS neurophysiology. Related word pairs are favorable to strengthen or tag hippocampal-dependent memories, in which sleep play a subtle role (Walker 2005; Mednick 2010) .

Relating motor memory and SWS, motor adaptation  task  also  the  similar  to  those  reported for the  motor  sequence  task. The  striking  result  is the  increase  of  delta wave  oscillation  during  SWS, localized  in right parietal  lobe,  correlates  with subsequent  sleep-dependent  improvement  of performance.  Together, sleep can facilitate sleep- dependent  procedural memory consolidation, incorporating  neural correlates  such  as SWS, spindle  activity  and ripple  wave (Backhaus and Junghanns 2006; Eschenko and others 2008; Andrade 2011) .

The neural  basis  for  the role of sleep  after learning  has  been  increasingly  investigated.  A system  level  alteration  in neural  representation  of a  learned  memory  may  occur  during  sleep,  without such  an alteration  during wakefulness. Using functional  magnetic  resonance  imaging  (fMRI), several  studies  showed  differential  activation  of brain  regions  and  a re-organization of  memories ( Rauchs and others 2011) .

Overnight, plastic reorganization of memory within brain may result in a more refined storage representation  of  information,  such  that  the  access and  availability  of memory recall  in more  efficient the  following  day.  Therefore, sleep after learning of certain  tasks  looks to be required  for  the subsequent  neural re-organization  needed  to consolidate memory (Walker and Stickgold 2004;  Born and others 2006; Rauchs and others 2011) .

Sleep before learning

While  the  merits  of sleep  after  learning  have been  clearly  demonstrated,  it has  become  apparent that  sleep  before  learning  is  also  important  for brain functioning.  Animal studies  have  shown  that  sleep deprivation  leads  to change  at a cellular and molecular  level  that  inhibit  hippocampal  functioning  and  impair  subsequent  performance on hippocampus-dependent  spatial  learning  task ( Stickgold and others 2001).  Yoo et  al.  reported  the  hippocampal  deficits  in humans produced by  total  sleep  deprivation  are  strongly related  with memory  encoding  by using  fMRI ( Yoo and others 2007).

The impact of sleep deprivation on the neural dynamics associated with encoding of new declarative memories  has  been  revealed  using event-related  fMRI.  In addition  to  performance ,encoding  impairments  at  a behavioral  level,  a highly significant  and selective  deficit in  encoding activation  was  revealed  in bilateral  regions  of  hippocampus  in  the  sleep  deprived  condition.  It is apparent  that  sleep  deprivation markedly impairs  hippocampal  memory  function  in  humans ( Walker 2009;Yoo and others 2007).

Neuroimaging studies  performing sleep deprivation  indicate  the critical need  for sleep before  learning: without adequate  sleep, hippocampal  function  obviously  impaired,  resulting in  a  decreased  ability  to  encode  new  experiences the  extent of  which  appears  to be  further governed by alterations  in prefrontal  encoding.  Thus,  sleep is  not  only  critical  after  learning  for  the  subsequent consolidation  of memory,  but  also  sleep  before learning  looks  equally  important  in preparing  brain structures  for  efficient  memory formation (Yoo and others 2007; Chee and others 2011).

Sleep stage on consolidation

Early  studies  in  rats  and  humans  investigating whether  different  sleep  stages  have  different  roles mainly focused  on REM  sleep.  REM sleep deprivation,  by waking  subjects  up  repeatedly  at the  first signs  of REM sleep,  itself  influences memory  function. The  results  of REM deprived studies  have  been  remained  controversial (Rauchs and others 2005; DANG-VU 2006; Diekelmann and Born 2010) .

Several  studies  have  shown that NREM  stage 2  sleep  of post-training  sleep  strengthen procedural motor memory ( walker and others 2002; Fischer and others 2002; Nishida and Walker 2007). It is commonly recognized that sleep  spindles,  a  thalamocortical  rhythm  manifested on the EEG as  a brief  11-15  Hz oscillation,  a defining  characteristic  of stage  2 NREM sleep, triggering  intracellular  mechanisms  required  for synaptic  plasticity. Recent  finding elucidated  that those  who  generated  more  sleep  spindles  during a

night of sleep went on to exhibit higher tolerance for noise during a subsequent, noisy night of sleep ( Nishida and Walker 2007).

Although spontaneous spindles may have capacity of protecting  sleep  from disrupting  stimuli,  the further  study  should  distinguish  natural  spindles from  drug-induced  spindle  activities,  considering medicated  psychiatric  disorders.

In humans,  SWS has  a critical  role in both declarative  and non-declarative  memory consolidation.  Tononi and his colleagues proposed synaptic  homeostasis  hypothesis,  explaining  the mechanisms  assumes  that  consolidation  is  a  by- product  of  the  global  synaptic  downscaling  during sleep. Slow oscillations  are associated  with downscaling:  they  show  maximum  amplitudes  at the beginning of  sleep  when overall synaptic strength  is  high,  due  to  information  uptake  during encoding  prior  to sleep,  and  decrease  in amplitude across SWS  cycles  as  a  result  of the synaptic depotentiation ( walker 2005).

Thus,  it is not a  particular  sleep  stage  per se that  mediates  memory  consolidation,  but  rather  the neurophysiological  mechanisms  associated  with those  sleep  stages.  Specific  neural  correlates  are complemented  each other, representing electrophysiological  unique  oscillation (Rauchs and others 2005; Diekelmann and Born 2010). (Fig.2)

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  monoaininergic brainstem  systems  that  are  also  involved  in the basic  regulation  of sleep.

Slow Wave Sleep (SWS)

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  neurons.  Accordingly,  increasing cholinergic  tone  during  SWS-rich  sleep  blocked the  sleep-dependent  consolidation of hippocampus-dependent  word-pair  memories.

Conversely,  blocking  the  high  cholinergic  tone  in awake subjects  improved consolidation  but impaired the encoding  of new information, suggesting  that  acetylcholine  serves  as  a  switch between  modes  of brain  activity,  from encoding during  wakefulness  to  consolidation  during  SWS. 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  neocoftex, and  if the  level  of glucocorticoids  is artificially increased  during SWS,  the consolidation  of declarative  memories  is  blocked.  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   almost 300 ms.  It  is  possible  that such  bursts  enforce  plasticity-related  immediate early gene  (IEG) activity in the neocortex  and thereby support at the synaptic level  the stabilization of  newly  formed memory representations (Diekelmann 2010).

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  activity  162  and the maintenance  of  long-term  potentiation (LTP).

Accordingly,  blocking  muscarinic  receptors  in  rats by  scopolamine  during REM  sleep  impaired memory  in a  radial arm maze  task.  In humans, blocking  cholinergic  transmission  during  REM-rich sleep  prevented  gains  in  finger  motor skill.

Conversely, enhancing  cholinergic  tone  during  post-training REM-rich  sleep  improved  consolidation  of a  visuo-motor skill.  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 consolidation.  However, enhancing noradrenergic activity  during  post-learning  REM sleep  in  humans failed  to  impair  procedural  memory  consolidation ( Diekelmann 2010).

Sleep-specific electrophysiological oscillations

Sleep stages are characterized by specific electrical field potential rhythms that temporally coordinate information  transfer  between  brain regions. Neocortical  slow  oscillations,  thalamo-cortical spindles  and hippocampal  ripples  have been associated  with memory  consolidation  during SWS.  The  neocortical  slow  oscillations  (of < 1 Hz) are  thought  to  provide  a  supra-ordinate  temporal frame  for  the  dialogue  between  the  neocortex  and subcortical  structures  that is necessary  for redistributing  memories  for  long-term  storage.  The amplitude  of  the  slow  oscillations  are  increase when SWS is preceded  by specific  learning experiences  and  decreased  when  the  encoding  of information  was  prevented.  These  changes  occur locally  in  the  cortical  regions  that  were  involved  in encoding  process. Inducing  slow oscillations during  non-REM  sleep  by  transcranial  magnetic stimulation  (TMS)  using  slow  oscillating potential  fields  improved  the  consolidation  of hippocampus-dependent  memories,  indicating  that slow oscillations  have a causal  role in  the consolidation  of  hippocampus-dependent  memories.

Thalamo-cortical  spindles  appear  to prime cortical  networks  for the  long-term  storage  of memory representations.  Repeated  spindle  associated  spike  like discharges  can  trigger  long term  potentiation  (LTP) and  synchronous  spindle activity  occurs  preferentially  at  synapses  that  were potentiated  during  encoding.  Human  studies  have shown  increases  in spindle  density  and  activity during  non-REM  sleep  and  SWS  after  learning  of both  declarative  tasks  and procedural motor skills.

In some studies these increases correlated with the post-sleep memory improvement and were localized to the cortical areas that were activated during encoding.

Hippocampal sharp wave-ripples accompany the sleep-associated re-activation of hippocampal neuron ensembles that were active during the preceding awake experience. The occurrence of sharp wave ripples is facilitated in previously potentiated synaptic circuits and sharp wave ripples might promote synaptic potentiation. During an individual ripple event only a small subpopulation of pyramidal cells fire, indicating modulation of select neuronal circuits. In humans (epileptic patients) the consolidation of picture memories that were acquired before a nap correlated with the number of ripples recorded from the entorhinal cortex, which is important output region of the hippocampus. Animal study showed that selective disruption of ripples by electrical stimulation during the post-learning rest periods in rats impaired formation of long-lasting spatial memories, suggesting that ripples have a causal role in sleep-dependent memory consolidation.

Ponto-geniculo-occipital  (PGO) wave and the EEG theta rhythm appear to support REM sleep associated memory consolidation.

The significance of PGO-waves for memory consolidation is indicated by findings in rats of an increase PGO wave density following training on an avoidance task. This improvement was associated with increased activity of brain derived neurotropic factor (BDNF) in the dorsal hippocampus. The theta (4-8lIz) oscillations that characterize REM sleep are also considered to contribute  to memory consolidation, based on the numerous studies shown hippocampus dependent learning. Theta activity occurring in conjunction with the activity in other EEG frequencies points to another important feature that is relevant to

memory processing during REM sleep. During REM sleep, all EEG activity including theta activity show remarkable reduction in terms of both power and coherence between limbic-hippocampal circuit than SWS or wakefulness. The gamma band (>40 Hz) also behaves in similar way. These findings suggest that memory system would be disengaged during REM sleep.

Taking together, accumulated electrical results suggest that sleep plays an important role in

balancing stabilization of the rehearsed material against the continued plasticity required for the further improvement ( Fig. 3).

Sleep and Brain Plasticity

Memory depends on brain plasticity, lasting structural or functional neural changes in response to stimuli. Evidence pof sleep-dependent plasticity would reinforce the idea that  sleep is important as a mediator of memory consolidation.

Several studies have investigated whether daytime learning may alter brain activation during subsequent sleep at night(Born 2006).

A Positron Emission Tomography (PET) study has demonstrated that patterns of brain activity expressed during training on a motor sequence task replayed during subsequent REM sleep. Daytime task was initially associated with hippocampal activity.

Hippocampal activation is considered mainly during SWS, occurring hippocampal-neocortex dialogue resulted in transition of long-term memory.

The striking result showed the amount of reactivation of hippocampus during SWS remarkably proportional to the amount of subsequent task improvement. Sleep-dependent replay may potentially modify synaptic connections established in specific brain network, acquired during daytime wakefulness. Brain imaging studies conclusively suggest  that sleep supports enhanced performance by altering the entire strategy used by the brain and allows more automatic execution of the tasks.

Cortical plasticity i.e. the formation and elimination of synapses is essential for learning, development and recovery process. Several hypotheses about the function of sleep postulate that sleep is causally linked to these processes. For instance, the synaptic homeostasis hypothesis ( Tononi and Cirelli 2006) proposes that cortical plasticity is reflected in electroencephalographic activityin the slow-wave frequency range ( slow wave activity, SWA)– the hallmark of deep sleep. According to the hypothesis, sleep slow waves are not only reflecting cortical plasticity but are also responsible for synaptic downscaling,  a renormalization process that recalibrates neural circuits.

On the neuronal level, such synaptic downscaling should lead to energy and space savings and increase the signal to noise ratio. The resulting increased efficiency in signal transduction might be responsible for sleep dependent performance improvements.

An increasing number of studies support the hypothesis. Thus, as SWA decreases in the course of a night, the responsiveness of cortical neurons in rats (Vyazovskiy et al., 2008), the size and number of synapses in Drosophila melanogaster ( Bushey et al., 2011), and the frequency and amplitude of miniature EPSPs in cortical slices, the most direct measure of cortical responsiveness (Liu et al., 2010), decrease.

Human studies link such synaptic changes to changes in performance. For example,sleep dependent performance improvement on a visuo-motor learning  task was positively correlated with the local increase of SWA (Huber et al., 2004). On the other hand, a suppression of sleep slow-waves abolished sleep dependent performance improvement on a texture discrimination task ( Aeschbach et al., 2008).

For now, the synaptic homeostasis hypothesis represents a compelling hypothesis about the function of sleep integrating molecular, electrophysiological and behavioral findings allowing for testable experiments.

The Dreaming

The study of dreaming has provided the unexpected result in sleep-dependent memory consolidation. Dream reports can be meaningful for explaining brain during sleep. Stickgold et al. reported that dream  construction occurs without activation of hippocampus-mediated episodic memories, applying the computer Tetris game to amnesic patients. Such an absence of episodic memory replays is supported by human PET studies showing the dorsolateral prefrontal  cortex, normally involved in memory recall, is deactivated especially during REM sleep. Animal studies suggest that the flow of information from the hippocampus to the cortex is blocked during REM sleep.

Clinical Considerations

All major psychiatric disorders such as schizophrenia, bipolar disorder and major depression, have associated sleep disturbances mainly manifesting insomnia. But the interaction between  psychiatric symptom and sleep disturbance might be bi-directional. Indeed, chronic, medicated  schizophrenia patients show normal practice-dependent improvement in the finger tapping  task, but show no overnight improvement. Major depressive patients show the similar result regarding motor memory consolidation, with interaction of REM suppressive agents such as  Selective Serotonin Reuptake Inhibitors (SSRIs).

In the context of REM-dependent negative emotional memory enhancement, negative aversive memories may hold implications for the mechanistic understanding and treatment of mood disorders, including major depressive disorders. Depression is commonly associated with alterations in REM sleep, including a faster progression into REM (reduced  REM latency) and an increase in the amount of REM. Considering the REM association with negative emotional memory such REM abnormalities in d-epression may represent an excessive consolidation process of prior negative affective experiences, due to the increased REM amount and faster speed of entry into REM, could selectively and disproportionately reinforce negative memories at night, thereby potentiating the mood disorder. Likewise, post-traumatic stress disorder (PTSD) is also associated with a dysregulation of REM sleep, with  reports of increased sympathetic autonomic tone. There may similarly be an adverse consequence to such trauma-induced REM-sleep changes in PTSD, which if they persist, could counter-productively amplify, rather than ameliorate, the acquired affective experience.

Such basic research findings may help the growing translational appreciation of the interaction between affective mood disorders and sleep physiology.

Thus, in one major psychiatric illness, at least, one process of sleep dependent memory consolidation seems to be totally dysfunctional.

Conclusion(s)


The field of sleep and memory has grown remarkably, with a lot of studies ranging from molecular biology in animals to neurophysiology in humans. These reports have provided converging evidence that claims sleep's role in memory processing, including both initial learning and post-training sleep associated neural plasticity.

Although the evidence has proved that sleep itself is beneficial for memory processing, several major questions remain: the types of memory, consolidation and neural correlates. Regarding procedural skill leaning and declarative memory consolidation, there are strong evidences. But the rules determining which are consolidated during sleep remain unclear. The interaction  between NREM and REM sleep should be further investigated, including the elucidation of neural correlates such as SWS, sleep spindles and ripple waves. The search for answers to these questions is the task of the next decade of research into sleep dependent memory processing.

References


1. Backhaus J and Junghanns  K. Daytime naps improve procedural motor memory. Sleep Medicine 2006; 7(6): 508-512
2. Born J, Bjorn Rasch,  Gais S. Sleep to Remember. Neuroscientist 2006; 12 (5 ): 410-424
3. Brand S, Kirov R. Sleep and its importance in adolescence and in common adolescent somatic and psychiatric conditions. Int J Gen Med. 2011; 4: 425–42.
4. Christophe Hotermans, Philippe Peigneux, Alain Maertens de Noordhout, et al. Early boost and slow consolidation in motor skill learning. Learn. Mem 2006;13:580-83
5. Dang-Vu TT, Desseilles M., Peigneux P., Maquet P. A role for sleep in brain plasticity. Pediatric Rehabilitation 2006; 9(2): 98–118
6. Diekelmann  S,  Born  J.  The  memory  function  of sleep. Nat  Rev  Neurosci.  2010  Feb;11  (2):114-26
7. Doyon J,  Korman M,  Morin A,  Dostie V, Hadj Tahar A,  Benali H,  Karni A, Ungerleider LG, Carrier J. Contribution of night and day sleep vs. simple passage of time to the consolidation of motor sequence and visuomotor adaptation learning. Experimental Brain Research 2009; 195(1): 15-26
8. Fischer S, Hallschmid M, Elsner AL, Born J Sleep forms memory for finger skills. Proc Natl Acad Sci U S A 2002;  99: 11987–91
9. Frankland PW., Bontempi B. The organization of recent and remote memories. Nature Reviews Neuroscience 2005;6: 119-130
10. Gais S,  Lucas B, Born J. Sleep after learning aids memory recall. Learn. Mem. 2006; 13: 259-262
11. Geraldine Rauchs, Dorothee Feyers, Brigitte Landeau, Christine Bastin, Andre Luxen, Pierre Maquet, and Fabienne Collette . Sleep Contributes to the Strengthening of Some Memories Over Others, Depending on Hippocampal Activity at Learning. JNEUROSCI 2011; 31(7): 2563-68
12. Gordon Winocur, Morris Moscovitch and Bruno Bontempi. Memory formation and long-term retention in humans and animals: Convergence towards a transformation account of hippocampal–neocortical interactions . Neuropsychologia  2010;48(8): 2339-56
13. Henke K. A model for memory systems based on processing modes rather than consciousness. Nature Reviews Neuroscience 2010; 11:523-532
14. Kandel E. In search of memory. The Emergence of a New Science of Mind 2006; ISBN 0-393-05863-8:198-208
15. Katia C. Andrade, Victor I. Spoormaker, Martin Dresler, Renate Wehrle, Florian Holsboer, Philipp G. Samann, and Michael Czisch. Sleep Spindles and Hippocampal Functional Connectivity in Human NREM Sleep. JNEUROSCI 2011, 31(28): 10331-10339
16. Marcos G. Frank and Joel Benington. The Role of Sleep in Memory Consolidation and Brain Plasticity: Dream or Reality? Neuroscientist 2006;12(6):1–12
17. Peigneux P, Melchior G, Schmidt Ch , Dang-Vu T, BolyM, Lauryed S, Ma P. Memory processing during sleep mechanisms and evidence from neuroimaging studies. Psychologica Belgica 2004;44(1/2):121-42
18. Matthew P. Walker. Cognitive consequences of sleep and sleep loss. Sleep Medicine 2008; 9(1):  S29–S34
19. Matthew H. Davis and M. Gareth Gaskell. A complementary systems account of word learning: neural and behavioural evidence. Phil. Trans. R. Soc. B 2009; 364: 3773–3800
20. Oxana Eschenko,  Wiam Ramadan, Matthias Molle,  Jan Born, and  Susan J. Sara. Sustained increase in hippocampal sharp-wave ripple activity during slow-wave sleep after learning. Learn. Mem. 2008. 15: 222-228
21. Matthew P. Walker. The Role of Sleep in Cognition and Emotion; Ann. N.Y. Acad. Sci. 2009; 1156: 168–97
22. Michael W.L. Chee, Cindy S.F. Goh, Praneeth Namburi, Sarayu Parimal, Katharina N. Seidl, Sabine Kastner. Effects of sleep deprivation on cortical activation during directed attention in the absence and presence of visual stimuli. NeuroImage 2011,doi:10.1016/j.neuroimage.2011.06.058
23. Markowitsch J.H., Staniloiu A. Memory, autonoetic consciousness, and the self. Consciousness and Cognition 2011; 20(1): 16-39
24. Miyamoto H. , Hensch T.K. Reciprocal Interaction of Sleep and Synaptic Plasticity. MI 2003;3(7): 404-417
25. Matthew P. Walker, Tiffany Brakefield, Alexandra Morgan, J. Allan Hobson,and Robert Stickgold. Practice with Sleep Makes Perfect:Sleep-Dependent Motor Skill Learning. Neuron 2002; 35: 205–11
26. Nishida M, Walker MP .Daytime Naps, Motor Memory Consolidation and Regionally Specific Sleep Spindles. PLoS ONE 2007; 2(4): e341. doi:10.1371/journal.pone.0000341
27. Rauchs G , Desgranges B, Foret J, Eustache F. The relationships between memory systems and sleep stages. J. Sleep Res. 2005; 14: 123–40
28. Sara C. Mednick, William A. Alaynick. Comparing Models of Sleep-dependent Memory Consolidation. J Exp Clin Med 2010;2(4):156–164
29.Sara  C.  Mednick,  Denise  J.  Cai, Tristan  Shuman, Stephan  Anagnostaras, and  John  T.  Wixted. An  opportunistic  theory  of  cellular and  systems  consolidation. Trends in Neurosciences  2011; 834:  1- 11
30. Stickgold R.  Sleep-dependent  memory consolidation.  Nature.  2005  Oct 27  ;437 (7063)  :1272-8 Review
31. Stickgold R, . Hobson J.A.,  Fosse R., and  Fosse M. Sleep, Learning, and Dreams: Off-line Memory Reprocessing. Science 2001;294(5544pp.):1052-57
32. Seung-Schik Yoo, Peter T Hu, Ninad Gujar, Ferenc A Jolesz & Matthew P Walker. A deficit in the ability to form new human memories without sleep. Nature Neuroscience 2007; 10: 385 - 392
33. Stickgold R. Sleep-dependent memory consolidation; review article. Nature 2005;437: 1272-1278
34. Sara SJ, Hars B.  In memory of consolidation. Learn. Mem. 2006; 13: 515-21
35. Walker  MP.  Sleep-dependent  memory processin Harv  Rev  Psychiatry.  2008  ;  16(5):  287-98.  Review.
36. Walker MP. A refined model of sleep and the time course of memory formation. Behavioral and Brain Sciences 2005; 28,:51–104
37. Walker  MP, Stickgold R. Sleep,memory, and plasticity. Annu. Rev. Psychol. 2006. 57:139–66
38. Walker MP ,Stickgold R. Sleep-Dependent Learning and Memory Consolidation. Neuron 2004;44(1): 121-133
39. Walker MP. Sleep-Dependent Memory Processing. informahealthcare 2008;16(5):  287-98
40. Wilhelm I,  Diekelmann S., Born J. Sleep in children improves memory performance on declarative but not procedural tasks. Learn. Mem. 2008;15: 373-7.

Source(s) of Funding


None

Competing Interests


None

Disclaimer


This article has been downloaded from WebmedCentral. With our unique author driven post publication peer review, contents posted on this web portal do not undergo any prepublication peer or editorial review. It is completely the responsibility of the authors to ensure not only scientific and ethical standards of the manuscript but also its grammatical accuracy. Authors must ensure that they obtain all the necessary permissions before submitting any information that requires obtaining a consent or approval from a third party. Authors should also ensure not to submit any information which they do not have the copyright of or of which they have transferred the copyrights to a third party.
Contents on WebmedCentral are purely for biomedical researchers and scientists. They are not meant to cater to the needs of an individual patient. The web portal or any content(s) therein is neither designed to support, nor replace, the relationship that exists between a patient/site visitor and his/her physician. Your use of the WebmedCentral site and its contents is entirely at your own risk. We do not take any responsibility for any harm that you may suffer or inflict on a third person by following the contents of this website.

Reviews
1 review posted so far

Comments
0 comments posted so far

Please use this functionality to flag objectionable, inappropriate, inaccurate, and offensive content to WebmedCentral Team and the authors.

 

Author Comments
0 comments posted so far

 

What is article Popularity?

Article popularity is calculated by considering the scores: age of the article
Popularity = (P - 1) / (T + 2)^1.5
Where
P : points is the sum of individual scores, which includes article Views, Downloads, Reviews, Comments and their weightage

Scores   Weightage
Views Points X 1
Download Points X 2
Comment Points X 5
Review Points X 10
Points= sum(Views Points + Download Points + Comment Points + Review Points)
T : time since submission in hours.
P is subtracted by 1 to negate submitter's vote.
Age factor is (time since submission in hours plus two) to the power of 1.5.factor.

How Article Quality Works?

For each article Authors/Readers, Reviewers and WMC Editors can review/rate the articles. These ratings are used to determine Feedback Scores.

In most cases, article receive ratings in the range of 0 to 10. We calculate average of all the ratings and consider it as article quality.

Quality=Average(Authors/Readers Ratings + Reviewers Ratings + WMC Editor Ratings)