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Group Information

  • Tu Minh Hoang (z3329949)
  • Vidushi Khatri (z3333226)
  • Vivian Le (z3416222)

Video Clip



http://www.wdr.de/tv/quarks/sendungsbeitraege/2006/0509/003_schlaf.jsp

Translated Page (via Google Translate)

Introduction


This media item, “Learning during Sleep”, is a video discussing the link between learning and sleep. Although it is obvious that sleep is essential for our survival, the exact effects and reasons why we need to sleep are still not transparently clear. It has been hypothesised that memory consolidation, the process of transferring information from our short-term to long term-memory, occurs while we sleep, and it is this claim which is investigated in the video.

The video clip itself is an excerpt from an episode of the German TV show Quarks and Co. which first aired on the 9th of May in 2006. The show collaborates with universities and scientists to explain complex and technical scientific issues in layman's terms. In this episode, Dr Reto Huber’s work on the subject is featured, and one of his experiments for a research paper involving the memory consolidation of motor-related tasks during sleep is shown. The subject’s competence at a certain motor task is observed before and after sleep, and throughout the course of the experiment her brain activity is also monitored with an EEG. While the precise details of the experiment results and observations are not discussed, the subject’s improvement at the task after sleeping as well as an increase in activity in the brain centres corresponding to learning during her phases of deep sleep strongly suggests that there is a distinct interaction between learning and deep sleep.

This topic is of substantial interest to us not only because of the general links to the neuroplasticity module, but also as students, finding out how to become more efficient learners is always something that catches our attention.

Memory


Memory is an ability to recall past experiences. It is a pivotal part of the learning process, contributing to our capacity to retain knowledge and adapt to our surrounding environments. According to Squire (2004), memories can be categorized as 'declarative' (explicit), in which our memories are recalled consciously, or ‘non-declarative’ (implicit), where the memories are recalled unconsciously. Factual knowledge as well as memories of past events can be classified as declarative. There are a number of subclasses of non-declarative memories, including procedural memory, priming and perceptual learning, emotional responses, skeletal responses and non-associative learning (Squire, 2004). These different types of memories are each encoded by different parts of the brain, as can be seen in the image below, from Squire (2004).

Squire 2004
Squire 2004



Formation of memory


Memory formation has a number of clear states, each involving movement of sensory input across different forms of memory:
  1. Encoding - sensory input is encoded into short term memory
  2. Consolidation - information is consolidated into long term memory
  3. Retrieval - stored long term memories are recalled

Memory formation has been an active area of interest since the case of HM (Henry Molaison) in 1953, who due to the removal of a portion of his Medial Temporal Lobes (Hippocampus and Amygdala) developed severe amnesia. After his surgery, H.M. wasn’t able to retain new memories about people, places or objects for longer than a few minutes. However, he still maintained a normal long-term memory and could recall memories from his childhood vividly (Squire, 2004; Squire & Wixted 2011). It was therefore hypothesised that H.M. was unable to consolidate memories into long-term memory, due to the removal of his hippocampus and/or amygdala.

Memory formation occurs when stimulus from multiple neurons converge and connections between these neurons are formed. At the neuronal level, studies have linked formation of memory and coordinated neuronal activity to formation of synaptic spines (Lai et al., 2012). Long Term Potentiation (LTP) has also been directly linked to the formation of neuronal connections at a synaptic level, mediated by an increase in AMPA receptors due to NMDA activation following activation of a neuron via firing of multiple neurons (Bliss & Collingridge, 1993).


Sleep

Stages of sleep

There are two main stages of sleep: REM sleep and non-REM sleep. While the specific functions of these two stages of sleep are unknown, it is known that sleep performs a dynamic function in restoration and is essential for life - sleep impaired rats die due to sleep deprivation. In humans, sleep deprivation has a whole range of effects ranging from tiredness, cognitive decline and changes in personality.

There are 4 main stages of sleep:

Sleep waves.png


Stage 1: Participant startss to fall asleep but still responds to environment
Stage 2: Participant is asleep and no longer responds to the environment
Stage 3: High amplitude, low frequency waves appear
Stage 4: Deepest stage of sleep

Humans oscillate between stages, slowly going into deep stage 4 sleep and coming back to almost awake during REM. On average humans spend 25% of their sleep in deep slow waves sleep, which has been linked to physical restoration and memory consolidation (Gambelunghe et al., 2001). Human spend another 25% of their sleep in REM sleep, which is an active state of sleep and has been linked with consolidation learning and memories. In neonates, who spend 50% of their time in REM sleep, REM is involved with myelination, and therefore is heavily involved with synaptic connections (Peirano & Algarin 2007).

Slow Wave Sleep


Brain electrical activity is composed of various stages with characteristic frequencies. Slow wave activity (SWA) is mainly involved with Stages 3 and 4 of non-rapid eye movement (NREM) sleep and modulating delta, theta, spindle, alpha, beta, gamma and ripple waves, which in combination orchestrate the electrical rhythmic systems during sleep (Csercsa et al., 2010). In an EEG reading, NREM sleep is thought be reached when 20% or more of the waves consist of slow wave activity of (0.5-2 Hz) in the frontal lobe, with peak to peak amplitude greater than 75mm, alongside behavioural signs of sleep (Iber et al., 2007).

There has been some research that has linked slow delta waves (which are characterised as waves of less than 4Hz) during periods of NREM sleep to various functions including basic restorative processes and facilitating consolidation of declarative memory (Huber et al., 2004) via ensemble reactivation and synaptic strength normalisation (Csercsa et al., 2010). Other findings have also linked low-frequency to cognitive functions in the awake state, despite the fact that under usual circumstances, slow rhythms are usually good signatures of compromised cerebral functions and sleep (Csercsa et al., 2010). Slow wave sleep has be shown to be comprised of an up-state corresponding to increased alpha and beta waves and a down-state suggesting the homeostatic regulation of SWA, which is thought to reflect synaptic changes in a cellular need for sleep (Csercsa et al., 2010; Huber et al., 2004).


Memory & Sleep


Prolonged waking periods induce an increase in slow wave activity (Yuval et al., 2011) and high-density EEGs have been used to demonstrated that sleep slow waves are locally regulated as a function of prior use and plastic processes (Huber et al., 2004).

Huber et al. (2004) used a motor learning task to induce localised increases in SWA activity. His findings demonstrated that EEG markers of sleep homeostasis, SWA, could be induced using a motor learning task, thus suggesting a role of sleep at a cellular level. He also suggested a possible link between SWA and learning via facilitation of synaptic consolidation. These finding were later backed up by studies that further investigated the cellular basis of the importance of sleep in consolidation, through investigating the impact of sleep on Glu-1 AMPAR and its phosphorylation, the proposed cellular basis for long term potentiation (LTP) (Vyazovskiy et al., 2008), or illustrating enhances in hippocampus-dependant declarative memory accomplished by inducing slow oscillation waves during nocturnal sleep (Marshall et al., 2006).

Studies have also shown that SWA during sleep is associated with enhanced recall of declarative information (Tucker & Fishbein., 2009; Marshall el al., 2006), while NREM Stage 2 sleep has often been associated with improvement in processing of motor skill tasks, such as the motor sequence task and the pursuit rotor task (Tucker & Fishbein., 2009; Walker et al., 2002). While some studies have also linked REM sleep to enhancement in perceptual-motor development (Huber et al., 2004), time spent in NREM sleep has been directly linked to improvement in perceptual and motor skill development (Walker et al., 2002).



Critical Analysis


The media item is from a German science TV show called Quarks and Co., while the specific episode this clip was taken from was aired in May of 2006. It appears to be aimed at non-scientists with a passing interest in science, and as such the complex concepts involved in explaining the links between sleep and memory are condensed into a more easily understandable package. The video is nearly void of any technical terms – it makes reference to “the learning part of the brain” without explicitly mentioning any brain regions, and while it does mention EEGs, it does not elaborate much past saying that there is a 30% increase in the brainwaves. The video also does not elaborate on the specific stages of sleep and their role in memory consolidation, instead only making mention to “deep sleep”. However, the omission of these details does not detract from the overall flow of the media item – in fact the highly accessible language allows it to communicate its message in a very clear and comprehensible manner, with an adequate amount of material to keep a layperson informed of the general idea of these findings. The collaboration with the University of Wisconsin and Dr Reto Huber also gives the video a great deal of credibility as a reliable source of information.

It seems the experiment shown in the video is based on the Huber et al. (2004) paper Local Sleep and Learning, published in Nature. Using that paper as a basis to pry out the details that the video does not mention, it appears that Huber et al. concluded that slow wave activity (SWA) was linked with the learning of motor skills, findings that were later corroborated by Vyazovskiy et al. (2008) and Marshall et al. (2006). However, there have also been a number of research articles indicating that it is in fact stage 2 of non-REM sleep that is instrumental in the consolidation of motor skills (Tucker & Fishbein, 2009), and that SWA is associated with the processing of declarative memory. Other schools of thought also exist, such as the view that it is merely the passage of time that facilitates memory consolidation, and that sleep itself is irrelevant (Vertes, 2004). These conflicting views show that even though the video does present a plausible view which succeeds in providing a general audience with a broad overview of the link between sleep and memory, the topic of sleep and learning still requires a great deal of research before definitive conclusions can be made.


Appendix


The selection of our topic was a team effort, with our group essentially in complete agreement all along the way. Having skimmed fruitlessly through a number of TED talks for a suitable topic which had not been covered by students who had done the course in previous years, we briefly turned our attention to journal articles from sources such as Nature, but this also proved to be unsuccessful. Ultimately we decided to pick our topic based on a conversation we had had involving learning by listening to audio while asleep, a topic we had all found to be fascinating. Initial searches for relevant clips on Youtube yielded very lengthy videos about sleep hypnosis which did not seem remotely academic, but eventually we stumbled upon this video, which appeared to have a much higher production value, with input from real scientists.Finding the source of the video was somewhat of an issue – there was no description of the video on YouTube, and the uploader’s account had been inactive for some months. However one of our group members was able to locate Dr Reto Huber’s email (the researcher featured in the video) and ask him personally what the source of the video was.

The original source video was aired in 2006, while the research paper it was based on was published in 2004. Since this is still a field where there is much uncertainty and new developments are continually being made, this allowed us to draw on a number of newer sources to investigate the claims in the video to a greater level of depth. Our supporting sources and references were taken from a number of places, using internet search engines and our library database to find peer-reviewed journal articles, lectures from this course, as well as other websites. We tried to ensure these sources were reliable and trustworthy by comparing the information found with other sources before we included them.

The peer reviewers provided a number of extremely valid points which we needed to address, namely:
- The inconsistency of tone/style of writing in between sections
- Numerous grammar mistakes
- The inconsistency in referencing styles (and lack of any referencing in one section)
- Varying depth of detail in between sections – there was specific mention of a need to define “delta waves” more clearly. Some sections also contained irrelevant information, in particular the paragraphs which went into too much detail regarding the discovery of the parts of the brain. A need to provide a little more information about sleep was also mentioned

We tried to fix these issues by firstly having all members thoroughly read through and proofread for grammar mistakes. The consistency of referencing was addressed by having one group member go through and reference in one style. The appropriate details were also added and removed as we saw fit.

References


  1. Bliss, T V, and G L Collingridge. "A synaptic model of memory: long-term potentiation in the hippocampus." Nature 361, no. 6407 (1993): 31-39.
  2. Csercsa, Richard, et al. "Laminar analysis of slow wave activity in humans." Brain 133, no. 9 (September 2010): 2814-2829.
  3. Gambelunghe, Cristiana, Ruggero Rossi, Giuseppina Mariucci, Michela Tantucci, and Maria Vittoria Ambrosini. "Effects of light physical exercise on sleep regulation in rats." Official Journal of the American College of Sports Medicine 33 (2001): 57-60.
  4. Huber, Reto, M Felice Ghilardl, Marcello Massimini, and Giulio Tononi. "Local sleep and learning." Nature 430 (July 2004): 78-81.
  5. Iber, Conrad, Chair Sonia Ancoli-Israel, Andrew L Chesson, and Stuart F Quan. The AASM Manual for the Scoring of Sleep and Associated Events. Edited by Conrad Iber. Westchester, IL: American Academy of Sleep Medicine, 2007.
  6. Lai, Cora Sau Wan, Thomas F. Franke, and Wen-Biao Gan. "Opposite effects of fear conditioning and extinction on dendritic spine remodelling." Nature 483 (2012): 87-91.
  7. Marshall, Lisa, Halla Helgrdottir, Matthias Molle, and Jan Born. "Boosting slow oscillations during sleep potentiates memory." Nature 444 (2006): 610-613.
  8. Peirano, Patricio D, and Cecilia R Algarin. "Sleep in brain development." Biological Research 40 (2007): 471-478.
  9. Squire, L.R. "Memory systems of the brain: A brief history and current perspective." Neurobiology of Learning and Memory 82 (2004): 171-177.
  10. Squire, L.R., Wixted J.T. "The Cognitive Neuroscience of Human Memory Since H.M." Annual Review of Neuroscience 34 (2011): 259-288.
  11. Vertes RP. "Memory Consolidation in Sleep: Dream or Reality." Neuron. 44, no. 1 (2004): 135-148
  12. Vyazovskiy, Vladyslav, Chiara Cirelli, Martha Pfister-Genskow, Ugo Faraguna, and Giulio Tononi. "Molecular and electrophysiological evidence for net synaptic potentiation in wake and depression in sleep." Nature Neuroscience 11, no. 2 (2006): 280-288.
  13. Walker, M. P., Brakefield, T., Morgan, A., Hobson, J. A. and Stickgold, R. "Practice with sleep makes perfect: sleep-dependent motor skill learning." Neuron 35 (2002): 205–211.