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):WMC002247
doi: 10.9754/journal.wmc.2011.002247
No
Click here
Submitted on: 24 Sep 2011 12:07:39 PM GMT
Published on: 24 Sep 2011 02:45:34 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  0.75  HZ 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  1eve1  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  of  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 depression  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 T.T.,. 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, BOLY M, LAUREYS S, MAQUET 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
0 reviews 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)