Sleep-Dependent Memory Consolidation

Image Unavailable
Student caught performing offline memory consolidation in class.

Although the function of sleep largely remains a mystery, it is well recognized that sleep plays an important role in memory consolidation. Those who have had first-hand experience with sleep deprivation can attest to the memory impairments that arise with inadequate sleep. Among many others, structures involved in sleep-dependent memory processes include the hippocampus, mPFC, brainstem, and neocortex[1]. A sleep cycle can be divided up into stages based on characteristic patterns such as neural electrical activity, and can be broadly categorized under REM and NREM sleep[2]. The periods of REM and NREM sleep encompass numerous processes that have been found to be correlated with memory consolidation. Different types of memory (eg. declarative vs procedural) appear to be affected more strongly by different portions of the sleep cycle[1]. While processes such as slow-wave activity and REM activity have been associated with memory function, our hypotheses of the detailed underlying mechanisms constantly undergo revision. Despite the difficulties of trying to understand the memory-consolidating mechanisms employed by sleep, it is worth pursuing in the hopes that these mechanisms may be exploited in order to treat memory deficits, or enhance memory.

1. Memory Consolidation

Memory consolidation is the process in which temporary, labile memory traces are made more stable, and available for long-term use[5]. Consolidation may be observed as increased resistance to interference (e.g. against retrograde interference), and improvements in performance on memory tests after sleep [3]. There are two main hypothesized models to explain the mechanisms underlying sleep-dependent memory consolidation: the standard two-stage model, and the synaptic homeostasis hypothesis.

Two-Stage Model of Memory Consolidation
Image Unavailable
Starting on the left, there is the initial parallel encoding to both the temporary and long-term storages.
During SWS, there is system consolidation, reactivating the memory traces in the temporary storage to
facilitate transfer and reorganization. Next, synaptic consolidation during REM sleep strengthens these memory traces.[1]

1.1 Standard Two-Stage Model of Memory-Consolidation

In order to resolve the stability-plasticity dilemma posed by previous memory models, the standard two-stage model of memory was devised. This model overcomes the challenges that would arise if rapidly encoding incoming information, incorporating info with existing networks, and retaining older memory traces were all attempted simultaneously, in one step. The two-part system consists of the sequential action of system consolidation during slow-wave sleep (SWS), and synaptic consolidation during REM sleep[1]. The order in which they occur is important.

The initial encoding process during wakefulness occurs in a parallel-manner, encoding to both the temporary, hippocampal-dependent system, as well as to neocortical structures[5]. During SWS, it is thought that system consolidation occurs, whereby repeated reactivations of the hippocampal memory traces serve to facilitate reorganization and integration of the information into the existing network[6]. It is important that system consolidation occurs as an offline (during sleep) process because the constant activity and inputs from environmental stimuli during wakefulness would interfere with the reactivation-based mechanism[5]. SWS is followed by periods of REM sleep, which strengthens the established memory traces through LTP, contributing to the persistence of the memories[4].

Sleep-mediated synaptic downscaling
Image Unavailable
Changes in synaptic strength over time. Note the relative changes in synaptic weight with respect
to the activity of the synapses. W is synaptic weight/strength measured in arbitrary units.
White synapses are unactivated, yellow synapses are activated, and the wine-red synapses
are the synapses after synaptic downscaling[1].

1.2 Synaptic Homeostasis Hypothesis

Based on our current understanding of memory systems, the consensus is that LTP mediates persistant memories via processes that selectively increase synaptic strength. Synaptic homeostasis represents a global downscaling of synaptic weight which serves the purpose of keeping synaptic networks at a physically-sustainable level in terms of energy and resource expenditure [7]. It also improves the signal to noise ratio, while still allowing the more potentiated synapses to stand-out relative to synapses that have undergone less potentiation. The figure to the left illustrates the changes in synaptic strength from baseline, to wakeful-encoding, to sleep-mediated synaptic downscaling. The synaptic downscaling that follows the potentiation processes leads to a net change that strengthens the activated synapse (in figure, W=100 -> 120), and weakens the unactivated synapse (in figure, W=100 -> 80).

2. NREM Sleep

EEG Features
Image Unavailable
Various processes observed in EEG recordings of sleep.
Image from modified.

2.1 EEG Overview

The non-REM (NREM) portion of sleep can be divided into 3 stages. Stage 1 is characterized by the appearance of theta waves, stage 2 contains spindles and k-complexes, and stage 3 is slow-wave sleep consisting of delta waves. Historically, slow-wave sleep (SWS) was encompassed by stages 3 and 4, with stage 4 containing more delta waves. However, this distinction was somewhat arbitrary and variable between sleep labs. After review by the AASM(American Academy of Sleep Medicine), it was deemed that the division of stages 3 and 4 was unwarranted, and since 2007, they have been combined under the identity of stage 3 NREM sleep [2]. In general, NREM sleep has been associated with a role in hippocampal-dependent declarative memory consolidation.

Cognitive performances with
pharmacological changes
in spindle density
Image Unavailable
Differences in scores on
memory tasks before vs. after
sleep under drug treatments of
sodium oxybate, placebo, and
zolpidem. **p=0.004, *p=0.02[10]

2.2 Sleep Spindles

Sleep spindles are bursts of activity that predominantly occur during stage 2 of NREM sleep, usually ranging from 12 to 14 Hz[8]. GABAergic thalamic reticular neurons have been implicated in the generation of sleep spindles, through a mechanism that requires connections between the thalamus and cortex[9].

In the past, it was difficult to acquire strong evidence linking spindles to memory consolidation due to the nature of the available techniques. Without the ability to experimentally manipulate features of sleep, studies were limited to showing associations, using techniques like memory task performance, and measured changes to the sleep that followed learning sessions[8]. In such studies, the sleep that followed periods of declarative learning showed increased spindle activity during NREM sleep. More recently, fMRI neuroimaging techniques have revealed correlations between spindles and the activation of memory-related brain structures including the hippocampus, thalamus, and frontal cortex[11].

In a recent study by Mednick, et al.[10], the importance of sleep spindles for hippocampal-dependent verbal memory consolidation was investigated. A pharmacological approach was used to manipulate the sleep features, using a GABAA agonist hypnotic called zolpidem (Zol), and sodium oxybate (SOx). Zol was shown to increase sleep spindle density (spindles per minute), while SOx had the opposite effect. Numerous controls were used to minimize confounding factors, for example, ensuring that the changes in spindle density were not accompanied by changes to the other spindle characteristics (i.e. frequency, amplitude, etc.). The experiment required subjects to learn and perform one of three memory tasks, with an intervening daytime nap influenced by pharmacological treatment. A word-pair association task was used to test verbal memory, a texture discrimination task for perceptual memory, and a finger-tapping task for motor memory. Subjects were given drug treatment (Zol, SOx or placebo) for their post-learning nap. Post-nap testing results showed that greater sleep spindle density was correlated with increased verbal memory (p=0.004) and decreased perceptual memory (p=0.02)[10]. Notably, statistical analysis of the data found that verbal memory was unrelated to any sleep features besides sleep spindles. These findings may encourage future application of pharmacological treatments to modify sleep features (spindles) for the purpose of enhancing the memory of healthy individuals.

Dr. Mednick discusses her study that was mentioned above for the first two minutes of the video.

2.3 K-Complexes

Also found during stage 2 of NREM sleep are k-complexes. K-complexes are biphasic or triphasic wave complexes that appear 1.0-1.7 times each minute[2]. In a study using intracranial electrodes (originally surgically implanted into epileptic patients for the purpose of locating epileptogenic areas[13]), along with EEG recordings, Cash, et al.[14] found that k-complexes shared the same features as cortical down-states. These down-states are characterized as periods of low neuronal activity, and are seen as part of a slow oscillating cycle, paired with high-activity, up-states. It has been suggested that k-complexes may play a role in reducing synaptic strength during these cortical down-states, making k-complexes a candidate mechanism for synaptic homeostasis [14].

Improved hippocampal-dependent declarative
memory with reactivation during SWS
Image Unavailable
A) Spatial test performance (hippocampal-
dependent declarative task). significant difference for
experiment AI compared to other AII,III,IV (p=0.01)
B) Procedural finger-tapping tasks (hippocampal-
independent task). Vehicle is odourless control

2.4 Slow-Wave Sleep

Slow-wave sleep is thought to be responsible for reactivation of memories which is hypothesized to aid in system consolidation. In early studies performed on rats, it was found that hippocampal activity recorded during spatial tasks was repeated during slow-wave sleep. The replayed patterns of activity observed during SWS appeared to follow the same order of activity during the wake period, but on a compressed time scale[15]. In a landmark study with human subjects by Rasch, et al.[16], it was found that odours presented during spatial task learning (hippocampal-dependent declarative), were able to improve memory consolidation when the same odour returned during SWS. In this same study, fMRI showed that the re-exposure to the odour, and subsequent improvement in declarative memory, were both associated with a significant increase in hippocampal activity[16]. A more recent experiment by Diekelmann, et al.[17] expanded upon the findings by Rasch's group. Comparing subjects who had 90 minutes v.s. 40 minutes of sleep following a spatial learning task, the 90-minute group was found to have better memory for the task. Interestingly, stimulating enhanced-reactivation of the hippocampus using the odour-associating protocol used by Diekelmann[16], was able to compensate for the difference in sleep duration such that the 40-minute-odor group matched the 90-minute-odourless group's performance[17]. These results provide evidence consistent with the current system consolidation model.

This process is relevant to our neuropathological understanding of some sleep-related memory disorders. In the case of aging, Mander, et al.[18] were able to reconcile three phenomena that were previously observed and studied individually: aging, atrophy of the medial prefrontal cortex (mPFC), and a decline in declarative memory. The experiments utilized word-pair tasks to evaluate declarative memory consolidation, MRI for brain structure, fMRI to analyze hippocampal-neocortical activity during SWS, EEG recordings to monitor activity and stages of sleep, and statistical analysis. The findings suggest that age-related atrophy of the mPFC leads to decreased SWS, which leads to the declarative-memory deficit. More importantly, the fMRI results found increased hippocampal activation, and decreased functional connectivity between the hippocampus and neocortex, suggesting that the underlying mechanism for this impairment involves a disruption of memory reactivation and transfer between the systems, supporting the system consolidation model[18].

Professor Guosong Liu discusses memory issues with respect to sleep. In particular, he brings up
changes in sleep duration with age, and the effect this has on memory and cognitive function.

2.5 Neurotransmitters

During SWS sleep, levels of acetylcholine are at a minimum, which is thought to allow reactivation during system consolidation[19]. In a study conducted by Gais and Born[20], the administration of the cholinesterase inhibitor physostigmine during SWS, leading to higher levels of ACh, was found to inhibit the consolidation of declarative memories. These results suggest that low levels of ACh are critical for hippocampal-dependent memory.

Although norepinephrine is usually considered to be part of the ascending activating system and thought to be present in low levels during sleep, the discovery of bursts of activity in the locus coeruleus (noradrenergic neurons) during NREM sleep suggest otherwise[21]. In a series of experiments using clonidine and reboxetine, which decrease and increase norepinephrine levels respectively, it was found that low norepinephrine during NREM sleep blocked memory consolidation[21]. Consistent in the opposite direction, increased levels of norepinephrine were found to enhance memory[21].

3. REM Sleep

During REM sleep, EEG recordings pick up high frequency, low amplitude waves, showing high levels of activity that resemble the awake state. The processes that occur during REM sleep suggest that it is involved in synaptic consolidation. A commonly held view is that REM sleep is for procedural memory consolidation, and that SWS is for declarative memories. While there is some truth to this in terms of the relative influence that the type of sleep has on the type of memory, this is a misleading oversimplification. Rather than subserving specific types of memories, NREM and REM sleep have complementary roles that are both crucial for proper memory function[1]. SWS may affect declarative memories more strongly than procedural memories because reorganization and integration with existing memory networks is more crucial for declarative memories[1]. Procedural memory being less concerned with integrating previously learned information, can be represented more discretely, and is thus less reliant on SWS. In the event that both types of memory are affected by reduced SWS, and hence unable to properly organize and arrange the memory traces, synaptic consolidation during REM sleep would be expected to be more beneficial for procedural memories.

Treatment of mAChR with pilocarpine
Image Unavailable
Northern blot analysis following pilocarpine administration
to rat brains. ARC and Cyr61 are immediate
early genes, and GAPDH serves as a control.[24]

Immediate early genes (IEGs) like zif-268[22] and ARC have been implicated in long-term memory consolidation and LTP maintenance. Their participation in calcium signalling pathways[22][23] help these IEGs mediate synaptic plasticity when there is high neuronal activity and LTP induction.

In the case of REM sleep, neurotransmitters are believed to play a role in IEG regulation. In contrast to NREM sleep, cholinergic activity during REM sleep is high, and in some cases, higher than during wakefulness[1]. While investigating muscarinic acetylecholine receptors (mAChR) (which had been implicated in learning and memory), Teber, et al.[24], found that activation of mAChR upregulated the IEG ARC. Shown in the figure to the right, the use of the mAChR agonist pilocarpine, resulted in an increase in ARC mRNA levels as well as Cyr61.

Of the two IEGs (ARC and Cyr61), ARC is of particular interest due to its roles in consolidation and LTP maintenance, and because it has been found in the dendrites of activated synapses[25]. When ARC proteins were disrupted in rats, impairments were observed for LTP maintenance, and long-term memory consolidation[25]. Conversely, LTP induction, and short-term memory were unaffected by the disruption of ARC[25]. These findings suggest that ARC is involved in the stabilization of long term memory through LTP, contributing supporting evidence for synaptic consolidation as outlined in the two-stage model.

1. Diekelmann, S., & Born, J. (2010). The memory function of sleep. Nature reviews. Neuroscience, 11(2):114-26.
2. Silber, M. H., Ancoli-Israel, S., Bonnet, M. H., Chokroverty, S., Grigg-Damberger, M. M., Hirshkowitz, M., Kapen, S., Keenan, S. A., Kryger, M. H., Penzel, T., Pressman, M. R., & Iber, C. (2007). The visual scoring of sleep in adults. Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine, 2, 121–131.
3. Krakauer, J. W., Ghez, C., & Ghilardi, M. F. (2005). Adaptation to visuomotor transformations: consolidation, interference, and forgetting. The Journal of neuroscience : the official journal of the Society for Neuroscience, 2, 473–478.
4. Frankland, P. W., & Bontempi, B. (2005). The organization of recent and remote memories. Nature reviews. Neuroscience, 2, 119–130.
5. Born, J., & Wilhelm, I. (2011). System consolidation of memory during sleep. Psychological research, 2, 192–203.
6. Diekelmann, S., Biggel, S., Rasch, B., & Born, J. (2012). Offline consolidation of memory varies with time in slow wave sleep and can be accelerated by cuing memory reactivations. Neurobiology of learning and memory, 2, 103–111.
7. Tononi, G., & Cirelli, C. (2005). Sleep function and synaptic homeostasis. Sleep medicine reviews, 1, 49–62.
8. Fogel, S. M., & Smith, C. T. (2010). The function of the sleep spindle: a physiological index of intelligence and a mechanism for sleep-dependent memory consolidation. Neuroscience and biobehavioral reviews, 5, 1154–1165.
9. De Gennaro, L., & Ferrara, M. (2003). Sleep spindles: an overview. Sleep medicine reviews, 5, 423–440.
10. Mednick, S. C., McDevitt, E. A., Walsh, J. K., Wamsley, E., Paulus, M., Kanady, J. C., & Drummond, S. P. (2013). The Critical Role of Sleep Spindles in Hippocampal-Dependent Memory: A Pharmacology Study. The Journal of neuroscience : the official journal of the Society for Neuroscience, 10, 4494–4504.
11. Schabus, M., Dang-Vu, T. T., Albouy, G., Balteau, E., Boly, M., Carrier, J., Darsaud, A., Degueldre, C., Desseilles, M., Gais, S., Phillips, C., Rauchs, G., Schnakers, C., Sterpenich, V., Vandewalle, G., Luxen, A., & Maquet, P. (2007). Hemodynamic cerebral correlates of sleep spindles during human non-rapid eye movement sleep. Proceedings of the National Academy of Sciences of the United States of America, 32, 13164–13169.
12. Girardeau, G., Benchenane, K., Wiener, S. I., Buzsáki, G., & Zugaro, M. B. (2009). Selective suppression of hippocampal ripples impairs spatial memory. Nature neuroscience, 10, 1222–1223.
13. Ulbert, I., Halgren, E., Heit, G., & Karmos, G. (2001). Multiple microelectrode-recording system for human intracortical applications. Journal of neuroscience methods, 1, 69–79.
14. Cash, S. S., Halgren, E., Dehghani, N., Rossetti, A. O., Thesen, T., Wang, C., Devinsky, O., Kuzniecky, R., Doyle, W., Madsen, J. R., Bromfield, E., Eross, L., Halász, P., Karmos, G., Csercsa, R., Wittner, L., & Ulbert, I. (2009). The human K-complex represents an isolated cortical down-state. Science (New York, N.Y.), 5930, 1084–1087.
15. Wilson, M. A., & McNaughton, B. L. (1994). Reactivation of hippocampal ensemble memories during sleep. Science (New York, N.Y.), 5172, 676–679.
16. Rasch, B., Büchel, C., Gais, S., & Born, J. (2007). Odor cues during slow-wave sleep prompt declarative memory consolidation. Science (New York, N.Y.), 5817, 1426–1429.
17. Diekelmann, S., Biggel, S., Rasch, B., & Born, J. (2012). Offline consolidation of memory varies with time in slow wave sleep and can be accelerated by cuing memory reactivations. Neurobiology of learning and memory, 2, 103–111.
18. Mander, B. A., Rao, V., Lu, B., Saletin, J. M., Lindquist, J. R., Ancoli-Israel, S., Jagust, W., & Walker, M. P. (2013). Prefrontal atrophy, disrupted NREM slow waves and impaired hippocampal-dependent memory in aging. Nature neuroscience, 3, 357–364.
19. Hasselmo, M. E., & McGaughy, J. (2004). High acetylcholine levels set circuit dynamics for attention and encoding and low acetylcholine levels set dynamics for consolidation. Progress in brain research, , 207–231.
20. Gais, S., & Born, J. (2004). Low acetylcholine during slow-wave sleep is critical for declarative memory consolidation. Proceedings of the National Academy of Sciences of the United States of America, 7, 2140–2144.
21. Gais, S., Rasch, B., Dahmen, J. C., Sara, S., & Born, J. (2011). The memory function of noradrenergic activity in non-REM sleep. Journal of cognitive neuroscience, 9, 2582–2592.
22. Ribeiro, S., Mello, C. V., Velho, T., Gardner, T. J., Jarvis, E. D., & Pavlides, C. (2002). Induction of hippocampal long-term potentiation during waking leads to increased extrahippocampal zif-268 expression during ensuing rapid-eye-movement sleep. The Journal of neuroscience : the official journal of the Society for Neuroscience, 24, 10914–10923.
23. Waltereit, R., Dammermann, B., Wulff, P., Scafidi, J., Staubli, U., Kauselmann, G., Bundman, M., & Kuhl, D. (2001). Arg3.1/Arc mRNA induction by Ca2+ and cAMP requires protein kinase A and mitogen-activated protein kinase/extracellular regulated kinase activation. The Journal of neuroscience : the official journal of the Society for Neuroscience, 15, 5484–5493.
24. Teber, I., Köhling R., Speckmann, E. J., Barnekow, A., & Kremerskothen, J. (2004). Muscarinic acetylcholine receptor stimulation induces expression of the activity-regulated cytoskeleton-associated gene (ARC). Brain research. Molecular brain research, 1-2, 131–136.
25. Guzowski, J. F., Lyford, G. L., Stevenson, G. D., Houston, F. P., McGaugh, J. L., Worley, P. F., & Barnes, C. A. (2000). Inhibition of activity-dependent arc protein expression in the rat hippocampus impairs the maintenance of long-term potentiation and the consolidation of long-term memory. The Journal of neuroscience : the official journal of the Society for Neuroscience, 11, 3993–4001.

Add a New Comment
Unless otherwise stated, the content of this page is licensed under Creative Commons Attribution-ShareAlike 3.0 License