Synaptic Homeostasis and Restructuring across the Sleep-Wake Cycle

The neurophysiology of closed-loop auditory stimulation in sleep: A magnetoencephalography study

Closed-loop auditory stimulation (CLAS) is a brain modulation technique in which sounds are timed to enhance or disrupt endogenous neurophysiological events. CLAS of slow oscillation up-states in sleep is becoming a popular tool to study and enhance sleep's functions, as it increases slow oscillations, evokes sleep spindles and enhances memory consolidation of certain tasks. However, few studies have examined the specific neurophysiological mechanisms involved in CLAS, in part because of practical limitations to available tools. To evaluate evidence for possible models of how sound stimulation during brain up-states alters brain activity, we simultaneously recorded electro- and magnetoencephalography in human participants who received auditory stimulation across sleep stages. We conducted a series of analyses that test different models of pathways through which CLAS of slow oscillations may affect widespread neural activity that have been suggested in literature, using spatial information, timing and phase relationships in the source-localized magnetoencephalography data. The results suggest that auditory information reaches ventral frontal lobe areas via non-lemniscal pathways. From there, a slow oscillation is created and propagated. We demonstrate that while the state of excitability of tissue in auditory cortex and frontal ventral regions shows some synchrony with the electroencephalography (EEG)-recorded up-states that are commonly used for CLAS, it is the state of ventral frontal regions that is most critical for slow oscillation generation. Our findings advance models of how CLAS leads to enhancement of slow oscillations, sleep spindles and associated cognitive benefits and offer insight into how the effectiveness of brain stimulation techniques can be improved.

Sleep sharp wave ripple and its functions in memory and synaptic plasticity

Memory is one of the fundamental cognitive functions of brain. The formation and consolidation of memory depend on the hippocampus and sleep. Sharp wave ripple (SWR) is an electrophysiological event which is most frequently observed in the hippocampus during sleep. It represents a highly synchronized neuronal activity pattern which modulates numerous brain regions including the neocortex, subcortical areas, and the hippocampus itself. In this review, we discuss how SWRs link experiences to memories and what happens in the hippocampus and other brain regions during sleep by focusing on synaptic plasticity.

Imagetic and affective measures of memory reverberation diverge at sleep onset in association with theta rhythm

The 'day residue' - the presence of waking memories into dreams - is a century-old concept that remains controversial in neuroscience. Even at the psychological level, it remains unclear how waking imagery cedes into dreams. Are visual and affective residues enhanced, modified, or erased at sleep onset? Are they linked, or dissociated? What are the neural correlates of these transformations? To address these questions we combined quantitative semantics, sleep EEG markers, visual stimulation, and multiple awakenings to investigate visual and affect residues in hypnagogic imagery at sleep onset. Healthy adults were repeatedly stimulated with an affective image, allowed to sleep and awoken seconds to minutes later, during waking (WK), N1 or N2 sleep stages. 'Image Residue' was objectively defined as the formal semantic similarity between oral reports describing the last image visualized before closing the eyes ('ground image'), and oral reports of subsequent visual imagery ('hypnagogic imagery). Similarly, 'Affect Residue' measured the proximity of affective valences between 'ground image' and 'hypnagogic imagery'. We then compared these grounded measures of two distinct aspects of the 'day residue', calculated within participants, to randomly generated values calculated across participants. The results show that Image Residue persisted throughout the transition to sleep, increasing during N1 in proportion to the time spent in this stage. In contrast, the Affect Residue was gradually neutralized as sleep progressed, decreasing in proportion to the time spent in N1 and reaching a minimum during N2. EEG power in the theta band (4.5-6.5 Hz) was inversely correlated with the Image Residue during N1. The results show that the visual and affective aspects of the 'day residue' in hypnagogic imagery diverge at sleep onset, possibly decoupling visual contents from strong negative emotions, in association with increased theta rhythm.

Distinct phosphorylation states of mammalian CaMKIIβ control the induction and maintenance of sleep

The reduced sleep duration previously observed in Camk2b knockout mice revealed a role for Ca2+/calmodulin-dependent protein kinase II (CaMKII)β as a sleep-promoting kinase. However, the underlying mechanism by which CaMKIIβ supports sleep regulation is largely unknown. Here, we demonstrate that activation or inhibition of CaMKIIβ can increase or decrease sleep duration in mice by almost 2-fold, supporting the role of CaMKIIβ as a core sleep regulator in mammals. Importantly, we show that this sleep regulation depends on the kinase activity of CaMKIIβ. A CaMKIIβ mutant mimicking the constitutive-active (auto)phosphorylation state promotes the transition from awake state to sleep state, while mutants mimicking subsequent multisite (auto)phosphorylation states suppress the transition from sleep state to awake state. These results suggest that the phosphorylation states of CaMKIIβ differently control sleep induction and maintenance processes, leading us to propose a "phosphorylation hypothesis of sleep" for the molecular control of sleep in mammals.

Order matters: sleep spindles contribute to memory consolidation only when followed by rapid-eye-movement sleep

Sleep is known to benefit memory consolidation, but little is known about the contribution of sleep stages within the sleep cycle. The sequential hypothesis proposes that memories are first replayed during nonrapid-eye-movement (NREM or N) sleep and then integrated into existing networks during rapid-eye-movement (REM or R) sleep, two successive critical steps for memory consolidation. However, it lacks experimental evidence as N always precedes R sleep in physiological conditions. We tested this sequential hypothesis in patients with central hypersomnolence disorder, including patients with narcolepsy who present the unique, anti-physiological peculiarity of frequently falling asleep in R sleep before entering N sleep. Patients performed a visual perceptual learning task before and after daytime naps stopped after one sleep cycle, starting in N or R sleep and followed by the other stage (i.e. N-R vs. R-N sleep sequence). We compared over-nap changes in performance, reflecting memory consolidation, depending on the sleep sequence during the nap. Thirty-six patients who slept for a total of 67 naps were included in the analysis. Results show that sleep spindles are associated with memory consolidation only when N is followed by R sleep, that is in physiologically ordered N-R naps, thus providing support to the sequential hypothesis in humans. In addition, we found a negative effect of rapid-eye-movements in R sleep on perceptual consolidation, highlighting the complex role of sleep stages in the balance to remember and to forget.

Examining Relationships between Sleep Physiology and the Gut Microbiome in Pre-Clinical and Translational Research: A Scoping Review Protocol (Preprint)

Background

Objective

Methods

Results

Conclusions

Trial Registration

International Registered Report Identifier (IRRID)

Abnormally abrupt transitions from sleep-to-wake in Huntington's disease sheep (Ovis aries) are revealed by automated analysis of sleep/wake transition dynamics

Sleep disturbance is a common and disruptive symptom of neurodegenerative diseases such as Alzheimer’s and Huntington’s disease (HD). In HD patients, sleep fragmentation appears at an early stage of disease, although features of the earliest sleep abnormalities in presymptomatic HD are not fully established. Here we used novel automated analysis of quantitative electroencephalography to study transitions between wake and non-rapid eye movement sleep in a sheep model of presymptomatic HD. We found that while the number of transitions between sleep and wake were similar in normal and HD sheep, the dynamics of transitions from sleep-to-wake differed markedly between genotypes. Rather than the gradual changes in EEG power that occurs during transitioning from sleep-to-wake in normal sheep, transition into wake was abrupt in HD sheep. Furthermore, transitions to wake in normal sheep were preceded by a significant reduction in slow wave power, whereas in HD sheep this prior reduction in slow wave power was far less pronounced. This suggests an impaired ability to prepare for waking in HD sheep. The abruptness of awakenings may also have potential to disrupt sleep-dependent processes if they are interrupted in an untimely and disjointed manner. We propose that not only could these abnormal dynamics of sleep transitions be useful as an early biomarker of HD, but also that our novel methodology would be useful for studying transition dynamics in other sleep disorders.

Cyclic alternation of quiet and active sleep states in the octopus

Previous observations suggest the existence of ‘Active sleep’ in cephalopods. To investigate in detail the behavioral structure of cephalopod sleep, we video-recorded four adult specimens of Octopus insularis and quantified their distinct states and transitions. Changes in skin color and texture and movements of eyes and mantle were assessed using automated image processing tools, and arousal threshold was measured using sensory stimulation. Two distinct states unresponsive to stimulation occurred in tandem. The first was a ‘Quiet sleep’ state with uniformly pale skin, closed pupils, and long episode durations (median 415.2 s). The second was an ‘Active sleep’ state with dynamic skin patterns of color and texture, rapid eye movements, and short episode durations (median 40.8 s). ‘Active sleep’ was periodic (60% of recurrences between 26 and 39 min) and occurred mostly after ‘Quiet sleep’ (82% of transitions). These results suggest that cephalopods have an ultradian sleep cycle analogous to that of amniotes.

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Octopus has ‘Quiet’ and ‘Active sleep’, with different episode duration and periodicity

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States differ on arousal thresholds, skin color and texture, and eye and mantle movement

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The results suggest that octopus has a sleep cycle analogous to that of amniotes

A mechanism for learning with sleep spindles

Spindles are ubiquitous oscillations during non-rapid eye movement (NREM) sleep. A growing body of evidence points to a possible link with learning and memory, and the underlying mechanisms are now starting to be unveiled. Specifically, spindles are associated with increased dendritic activity and high intracellular calcium levels, a situation favourable to plasticity, as well as with control of spiking output by feed-forward inhibition. During spindles, thalamocortical networks become unresponsive to inputs, thus potentially preventing interference between memory-related internal information processing and extrinsic signals. At the system level, spindles are co-modulated with other major NREM oscillations, including hippocampal sharp wave-ripples (SWRs) and neocortical slow waves, both previously shown to be associated with learning and memory. The sequential occurrence of reactivation at the time of SWRs followed by neuronal plasticity-promoting spindles is a possible mechanism to explain NREM sleep-dependent consolidation of memories. This article is part of the Theo Murphy meeting issue 'Memory reactivation: replaying events past, present and future'.

EEG connectivity across sleep cycles and age

STUDY OBJECTIVES

In young adults, sleep is associated with important changes in cerebral connectivity during the first cycle of non-rapid eye movement (NREM) sleep. Our study aimed to evaluate how electroencephalography (EEG) connectivity during sleep differs between young and older individuals, and across the sleep cycles.

METHODS

We used imaginary coherence to estimate EEG connectivity during NREM and rapid eye movement (REM) sleep in 30 young (14 women; 20-30 years) and 29 older (18 women; 50-70 years) individuals. We also explored the association between coherence and cognitive measures.

RESULTS

Older individuals showed lower EEG connectivity in stage N2 but higher connectivity in REM and stage N3 compared to the younger cohort. Age-related differences in N3 were driven by the first sleep cycle. EEG connectivity was lower in REM than N3, especially in younger individuals. Exploratory analyses, controlling for the effects of age, indicated that higher EEG connectivity in delta during N2 was associated with higher processing speed, whereas, during REM sleep, lower EEG connectivity in delta and sigma was associated with higher verbal memory performance and a higher global averaged intelligence quotient score.

CONCLUSION

Our results indicated that age modifies sleep EEG connectivity but the direction and the magnitude of these effects differ between sleep stages and cycles. Results in N3 and REM point to a reduced ability of the older brains to disconnect as compared to the younger ones. Our results also support the notion that cerebral functional connectivity during sleep may be associated with cognitive functions.

Regulation of gamma-frequency oscillation by feedforward inhibition: A computational modeling study

Throughout the brain, reciprocally connected excitatory and inhibitory neurons interact to produce gamma-frequency oscillations. The emergent gamma rhythm synchronizes local neural activity and helps to select which cells should fire in each cycle. We previously found that such excitation-inhibition microcircuits, however, have a potentially significant caveat: the frequency of the gamma oscillation and the level of selection (i.e., the percentage of cells that are allowed to fire) vary with the magnitude of the input signal. In networks with varying levels of brain activity, such a feature may produce undesirable instability on the time and spatial structure of the neural signal with a potential for adversely impacting important neural processing mechanisms. Here we propose that feedforward inhibition solves the latter instability problem of the excitation-inhibition microcircuit. Using computer simulations, we show that the feedforward inhibitory signal reduces the dependence of both the frequency of population oscillation and the level of selection on the magnitude of the input excitation. Such a mechanism can produce stable gamma oscillations with its frequency determined only by the properties of the feedforward network, as observed in the hippocampus. As feedforward and feedback inhibition motifs commonly appear together in the brain, we hypothesize that their interaction underlies a robust implementation of general computational principles of neural processing involved in several cognitive tasks, including the formation of cell assemblies and the routing of information between brain areas.

Primed to Sleep: The Dynamics of Synaptic Plasticity Across Brain States

It is commonly accepted that brain plasticity occurs in wakefulness and sleep. However, how these different brain states work in concert to create long-lasting changes in brain circuitry is unclear. Considering that wakefulness and sleep are profoundly different brain states on multiple levels (e.g., cellular, molecular and network activation), it is unlikely that they operate exactly the same way. Rather it is probable that they engage different, but coordinated, mechanisms. In this article we discuss how plasticity may be divided across the sleep-wake cycle, and how synaptic changes in each brain state are linked. Our working model proposes that waking experience triggers short-lived synaptic events that are necessary for transient plastic changes and mark (i.e., 'prime') circuits and synapses for further processing in sleep. During sleep, synaptic protein synthesis at primed synapses leads to structural changes necessary for long-term information storage.

The Function(s) of Sleep

Sleep is a highly conserved phenomenon in endotherms, and therefore it must serve at least one basic function across this wide range of species. What that function is remains one of the biggest mysteries in neurobiology. By using the word neurobiology, we do not mean to exclude possible non-neural functions of sleep, but it is difficult to imagine why the brain must be taken offline if the basic function of sleep did not involve the nervous system. In this chapter we discuss several current hypotheses about sleep function. We divide these hypotheses into two categories: ones that propose higher-order cognitive functions and ones that focus on housekeeping or restorative processes. We also pose four aspects of sleep that any successful functional hypothesis has to account for: why do the properties of sleep change across the life span? Why and how is sleep homeostatically regulated? Why must the brain be taken offline to accomplish the proposed function? And, why are there two radically different stages of sleep?The higher-order cognitive function hypotheses we discuss are essential mechanisms of learning and memory and synaptic plasticity. These are not mutually exclusive hypotheses. Each focuses on specific mechanistic aspects of sleep, and higher-order cognitive processes are likely to involve components of all of these mechanisms. The restorative hypotheses are maintenance of brain energy metabolism, macromolecular biosynthesis, and removal of metabolic waste. Although these three hypotheses seem more different than those related to higher cognitive function, they may each contribute important components to a basic sleep function. Any sleep function will involve specific gene expression and macromolecular biosynthesis, and as we explain there may be important connections between brain energy metabolism and the need to remove metabolic wastes.A deeper understanding of sleep functions in endotherms will enable us to answer whether or not rest behaviors in species other than endotherms are homologous with mammalian and avian sleep. Currently comparisons across the animal kingdom depend on superficial and phenomenological features of rest states and sleep, but investigations of sleep functions would provide more insight into the evolutionary relationships between EEG-defined sleep in endotherms and rest states in ectotherms.

Non-visual exploration of novel objects increases the levels of plasticity factors in the rat primary visual cortex

Background

Historically, the primary sensory areas of the cerebral cortex have been exclusively associated with the processing of a single sensory modality. Yet the presence of tactile responses in the primary visual (V1) cortex has challenged this view, leading to the notion that primary sensory areas engage in cross-modal processing, and that the associated circuitry is modifiable by such activity. To explore this notion, here we assessed whether the exploration of novel objects in the dark induces the activation of plasticity markers in the V1 cortex of rats.

Methods

Adult rats were allowed to freely explore for 20 min a completely dark box with four novel objects of different shapes and textures. Animals were euthanized either 1 (n = 5) or 3 h (n = 5) after exploration. A control group (n = 5) was placed for 20 min in the same environment, but without the objects. Frontal sections of the brains were submitted to immunohistochemistry to measure protein levels of egr-1 and c-fos, and phosphorylated calcium-dependent kinase (pCaKMII) in V1 cortex.

Results

The amount of neurons labeled with monoclonal antibodies against c-fos, egr-1 or pCaKMII increased significantly in V1 cortex after one hour of exploration in the dark. Three hours after exploration, the number of labeled neurons decreased to basal levels.

Conclusions

Our results suggest that non-visual exploration induces the activation of immediate-early genes in V1 cortex, which is suggestive of cross-modal processing in this area. Besides, the increase in the number of neurons labeled with pCaKMII may signal a condition promoting synaptic plasticity.

Computational models of memory consolidation and long-term synaptic plasticity during sleep

The brain stores memories by persistently changing the connectivity between neurons. Sleep is known to be critical for these changes to endure. Research on the neurobiology of sleep and the mechanisms of long-term synaptic plasticity has provided data in support of various theories of how brain activity during sleep affects long-term synaptic plasticity. The experimental findings - and therefore the theories - are apparently quite contradictory, with some evidence pointing to a role of sleep in the forgetting of irrelevant memories, whereas other results indicate that sleep supports the reinforcement of the most valuable recollections. A unified theoretical framework is in need. Computational modeling and simulation provide grounds for the quantitative testing and comparison of theoretical predictions and observed data, and might serve as a strategy to organize the rather complicated and diverse pool of data and methodologies used in sleep research. This review article outlines the emerging progress in the computational modeling and simulation of the main theories on the role of sleep in memory consolidation.

Memory corticalization triggered by REM sleep: mechanisms of cellular and systems consolidation

Once viewed as a passive physiological state, sleep is a heterogeneous and complex sequence of brain states with essential effects on synaptic plasticity and neuronal functioning. Rapid-eye-movement (REM) sleep has been shown to promote calcium-dependent plasticity in principal neurons of the cerebral cortex, both during memory consolidation in adults and during post-natal development. This article reviews the plasticity mechanisms triggered by REM sleep, with a focus on the emerging role of kinases and immediate-early genes for the progressive corticalization of hippocampus-dependent memories. The body of evidence suggests that memory corticalization triggered by REM sleep is a systemic phenomenon with cellular and molecular causes.

Short term changes in the proteome of human cerebral organoids induced by 5-MeO-DMT

Dimethyltryptamines are entheogenic serotonin-like molecules present in traditional Amerindian medicine recently associated with cognitive gains, antidepressant effects, and changes in brain areas related to attention. Legal restrictions and the lack of adequate experimental models have limited the understanding of how such substances impact human brain metabolism. Here we used shotgun mass spectrometry to explore proteomic differences induced by 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT) on human cerebral organoids. Out of the 6,728 identified proteins, 934 were found differentially expressed in 5-MeO-DMT-treated cerebral organoids. In silico analysis reinforced previously reported anti-inflammatory actions of 5-MeO-DMT and revealed modulatory effects on proteins associated with long-term potentiation, the formation of dendritic spines, including those involved in cellular protrusion formation, microtubule dynamics, and cytoskeletal reorganization. Our data offer the first insight about molecular alterations caused by 5-MeO-DMT in human cerebral organoids.

Cortical dendritic activity correlates with spindle-rich oscillations during sleep in rodents

How sleep influences brain plasticity is not known. In particular, why certain electroencephalographic (EEG) rhythms are linked to memory consolidation is poorly understood. Calcium activity in dendrites is known to be necessary for structural plasticity changes, but this has never been carefully examined during sleep. Here, we report that calcium activity in populations of neocortical dendrites is increased and synchronised during oscillations in the spindle range in naturally sleeping rodents. Remarkably, the same relationship is not found in cell bodies of the same neurons and throughout the cortical column. Spindles during sleep have been suggested to be important for brain development and plasticity. Our results provide evidence for a physiological link of spindles in the cortex specific to dendrites, the main site of synaptic plasticity.

Different stages of sleep, marked by particular electroencephalographic (EEG) signatures, have been linked to memory consolidation, but underlying mechanisms are poorly understood. Here, the authors show that dendritic calcium synchronisation correlates with spindle-rich sleep phases.

Dorsoventral and Proximodistal Hippocampal Processing Account for the Influences of Sleep and Context on Memory (Re)consolidation: A Connectionist Model

The context in which learning occurs is sufficient to reconsolidate stored memories and neuronal reactivation may be crucial to memory consolidation during sleep. The mechanisms of context-dependent and sleep-dependent memory (re)consolidation are unknown but involve the hippocampus. We simulated memory (re)consolidation using a connectionist model of the hippocampus that explicitly accounted for its dorsoventral organization and for CA1 proximodistal processing. Replicating human and rodent (re)consolidation studies yielded the following results. (1) Semantic overlap between memory items and extraneous learning was necessary to explain experimental data and depended crucially on the recurrent networks of dorsal but not ventral CA3. (2) Stimulus-free, sleep-induced internal reactivations of memory patterns produced heterogeneous recruitment of memory items and protected memories from subsequent interference. These simulations further suggested that the decrease in memory resilience when subjects were not allowed to sleep following learning was primarily due to extraneous learning. (3) Partial exposure to the learning context during simulated sleep (i.e., targeted memory reactivation) uniformly increased memory item reactivation and enhanced subsequent recall. Altogether, these results show that the dorsoventral and proximodistal organization of the hippocampus may be important components of the neural mechanisms for context-based and sleep-based memory (re)consolidations.

The epileptic amygdala: Toward the development of a neural prosthesis by temporally coded electrical stimulation

Many patients with epilepsy do not obtain proper control of their seizures through conventional treatment. We review aspects of the pathophysiology underlying epileptic phenomena, with a special interest in the role of the amygdala, stressing the importance of hypersynchronism in both ictogenesis and epileptogenesis. We then review experimental studies on electrical stimulation of mesiotemporal epileptogenic areas, the amygdala included, as a means to treat medically refractory epilepsy. Regular high-frequency stimulation (HFS) commonly has anticonvulsant effects and sparse antiepileptogenic properties. On the other hand, HFS is related to acute and long-term increases in excitability related to direct neuronal activation, long-term potentiation, and kindling, raising concerns regarding its safety and jeopardizing in-depth understanding of its mechanisms. In turn, the safer regular low-frequency stimulation (LFS) has a robust antiepileptogenic effect, but its pro- or anticonvulsant effect seems to vary at random among studies. As an alternative, studies by our group on the development and investigation of temporally unstructured electrical stimulation applied to the amygdala have shown that nonperiodic stimulation (NPS), which is a nonstandard form of LFS, is capable of suppressing both acute and chronic spontaneous seizures. We hypothesize two noncompetitive mechanisms for the therapeutic role of amygdala in NPS, 1) a direct desynchronization of epileptic circuitry in the forebrain and brainstem and 2) an indirect desynchronization/inhibition through nucleus accumbens activation. We conclude by reintroducing the idea that hypersynchronism, rather than hyperexcitability, may be the key for epileptic phenomena and epilepsy treatment.

The short- and long-term proteomic effects of sleep deprivation on the cortical and thalamic synapses

Acute total sleep deprivation (SD) impairs memory consolidation, attention, working memory and perception. Structural, electrophysiological and molecular experimental approaches provided evidences for the involvement of sleep in synaptic functions. Despite the wide scientific interest on the effects of sleep on the synapse, there is a lack of systematic investigation of sleep-related changes in the synaptic proteome. We isolated parietal cortical and thalamic synaptosomes of rats after 8h of total SD by gentle handling and 16h after the end of deprivation to investigate the short- and longer-term effects of SD on the synaptic proteome, respectively. The SD efficiency was verified by electrophysiology. Protein abundance alterations of the synaptosomes were analyzed by fluorescent two-dimensional differential gel electrophoresis and by tandem mass spectrometry. As several altered proteins were found to be involved in synaptic strength regulation, our data can support the synaptic homeostasis hypothesis function of sleep and highlight the long-term influence of SD after the recovery sleep period, mostly on cortical synapses. Furthermore, the large-scale and brain area-specific protein network change in the synapses may support both ideas of sleep-related synaptogenesis and molecular maintenance and reorganization in normal rat brain.

Levels of Interference in Long and Short-Term Memory Differentially Modulate Non-REM and REM Sleep

STUDY OBJECTIVES

It is commonly accepted that sleep is beneficial to memory processes, but it is still unclear if this benefit originates from improved memory consolidation or enhanced information processing. It has thus been proposed that sleep may also promote forgetting of undesirable and non-essential memories, a process required for optimization of cognitive resources. We tested the hypothesis that non-rapid eye movement sleep (NREMS) promotes forgetting of irrelevant information, more specifically when processing information in working memory (WM), while REM sleep (REMS) facilitates the consolidation of important information.

METHODS

We recorded sleep patterns of rats trained in a radial maze in three different tasks engaging either the long-term or short-term storage of information, as well as a gradual level of interference.

RESULTS

We observed a transient increase in REMS amount on the day the animal learned the rule of a long-term/reference memory task (RM), and, in contrast, a positive correlation between the performance of rats trained in a WM task involving an important processing of interference and the amount of NREMS or slow wave activity. Various oscillatory events were also differentially modulated by the type of training involved. Notably, NREMS spindles and REMS rapid theta increase with RM training, while sharp-wave ripples increase with all types of training.

CONCLUSIONS

These results suggest that REMS, but also rapid oscillations occurring during NREMS would be specifically implicated in the long-term memory in RM, whereas NREMS and slow oscillations could be involved in the forgetting of irrelevant information required for WM.

Cellular and System Biology of Memory: Timing, Molecules, and Beyond

The storage of information in the mammalian nervous systems is dependent on a delicate balance between change and stability of neuronal networks. The induction and maintenance of processes that lead to changes in synaptic strength to a multistep process which can lead to long-lasting changes, which starts and ends with a highly choreographed and perfectly timed dance of molecules in different cell types of the central nervous system. This is accompanied by synchronization of specific networks, resulting in the generation of characteristic "macroscopic" rhythmic electrical fields, whose characteristic frequencies correspond to certain activity and information-processing states of the brain. Molecular events and macroscopic fields influence each other reciprocally. We review here cellular processes of synaptic plasticity, particularly functional and structural changes, and focus on timing events that are important for the initial memory acquisition, as well as mechanisms of short- and long-term memory storage. Then, we cover the importance of epigenetic events on the long-time range. Furthermore, we consider how brain rhythms at the network level participate in processes of information storage and by what means they participating in it. Finally, we examine memory consolidation at the system level during processes of sleep.

Network Homeostasis and State Dynamics of Neocortical Sleep

Sleep exerts many effects on mammalian forebrain networks, including homeostatic effects on both synaptic strengths and firing rates. We used large-scale recordings to examine the activity of neurons in the frontal cortex of rats and first observed that the distribution of pyramidal cell firing rates was wide and strongly skewed toward high firing rates. Moreover, neurons from different parts of that distribution were differentially modulated by sleep substates. Periods of nonREM sleep reduced the activity of high firing rate neurons and tended to upregulate firing of slow-firing neurons. By contrast, the effect of REM was to reduce firing rates across the entire rate spectrum. Microarousals, interspersed within nonREM epochs, increased firing rates of slow-firing neurons. The net result of sleep was to homogenize the firing rate distribution. These findings are at variance with current homeostatic models and provide a novel view of sleep in adjusting network excitability.

Spindle Activity Orchestrates Plasticity during Development and Sleep

Spindle oscillations have been described during early brain development and in the adult brain. Besides similarities in temporal patterns and involved brain areas, neonatal spindle bursts (NSBs) and adult sleep spindles (ASSs) show differences in their occurrence, spatial distribution, and underlying mechanisms. While NSBs have been proposed to coordinate the refinement of the maturating neuronal network, ASSs are associated with the implementation of acquired information within existing networks. Along with these functional differences, separate synaptic plasticity mechanisms seem to be recruited. Here, we review the generation of spindle oscillations in the developing and adult brain and discuss possible implications of their differences for synaptic plasticity. The first part of the review is dedicated to the generation and function of ASSs with a particular focus on their role in healthy and impaired neuronal networks. The second part overviews the present knowledge of spindle activity during development and the ability of NSBs to organize immature circuits. Studies linking abnormal maturation of brain wiring with neurological and neuropsychiatric disorders highlight the importance to better elucidate neonatal plasticity rules in future research.

Impaired theta-gamma coupling in APP-deficient mice

Amyloid precursor protein (APP) is critically involved in the pathophysiology of Alzheimer's disease, but its physiological functions remain elusive. Importantly, APP knockout (APP-KO) mice exhibit cognitive deficits, suggesting that APP plays a role at the neuronal network level. To investigate this possibility, we recorded local field potentials (LFPs) from the posterior parietal cortex, dorsal hippocampus and lateral prefrontal cortex of freely moving APP-KO mice. Spectral analyses showed that network oscillations within the theta- and gamma-frequency bands were not different between APP-KO and wild-type mice. Surprisingly, however, while gamma amplitude coupled to theta phase in all recorded regions of wild-type animals, in APP-KO mice theta-gamma coupling was strongly diminished in recordings from the parietal cortex and hippocampus, but not in LFPs recorded from the prefrontal cortex. Thus, lack of APP reduces oscillatory coupling in LFP recordings from specific brain regions, despite not affecting the amplitude of the oscillations. Together, our findings reveal reduced cross-frequency coupling as a functional marker of APP deficiency at the network level.

Hippocampal sharp wave-ripple: A cognitive biomarker for episodic memory and planning

Sharp wave ripples (SPW-Rs) represent the most synchronous population pattern in the mammalian brain. Their excitatory output affects a wide area of the cortex and several subcortical nuclei. SPW-Rs occur during "off-line" states of the brain, associated with consummatory behaviors and non-REM sleep, and are influenced by numerous neurotransmitters and neuromodulators. They arise from the excitatory recurrent system of the CA3 region and the SPW-induced excitation brings about a fast network oscillation (ripple) in CA1. The spike content of SPW-Rs is temporally and spatially coordinated by a consortium of interneurons to replay fragments of waking neuronal sequences in a compressed format. SPW-Rs assist in transferring this compressed hippocampal representation to distributed circuits to support memory consolidation; selective disruption of SPW-Rs interferes with memory. Recently acquired and pre-existing information are combined during SPW-R replay to influence decisions, plan actions and, potentially, allow for creative thoughts. In addition to the widely studied contribution to memory, SPW-Rs may also affect endocrine function via activation of hypothalamic circuits. Alteration of the physiological mechanisms supporting SPW-Rs leads to their pathological conversion, "p-ripples," which are a marker of epileptogenic tissue and can be observed in rodent models of schizophrenia and Alzheimer's Disease. Mechanisms for SPW-R genesis and function are discussed in this review.

Formation and Dynamics of Waves in a Cortical Model of Cholinergic Modulation

Acetylcholine (ACh) is a regulator of neural excitability and one of the neurochemical substrates of sleep. Amongst the cellular effects induced by cholinergic modulation are a reduction in spike-frequency adaptation (SFA) and a shift in the phase response curve (PRC). We demonstrate in a biophysical model how changes in neural excitability and network structure interact to create three distinct functional regimes: localized asynchronous, traveling asynchronous, and traveling synchronous. Our results qualitatively match those observed experimentally. Cortical activity during slow wave sleep (SWS) differs from that during REM sleep or waking states. During SWS there are traveling patterns of activity in the cortex; in other states stationary patterns occur. Our model is a network composed of Hodgkin-Huxley type neurons with a M-current regulated by ACh. Regulation of ACh level can account for dynamical changes between functional regimes. Reduction of the magnitude of this current recreates the reduction in SFA the shift from a type 2 to a type 1 PRC observed in the presence of ACh. When SFA is minimal (in waking or REM sleep state, high ACh) patterns of activity are localized and easily pinned by network inhomogeneities. When SFA is present (decreasing ACh), traveling waves of activity naturally arise. A further decrease in ACh leads to a high degree of synchrony within traveling waves. We also show that the level of ACh determines how sensitive network activity is to synaptic heterogeneity. These regimes may have a profound functional significance as stationary patterns may play a role in the proper encoding of external input as memory and traveling waves could lead to synaptic regularization, giving unique insights into the role and significance of ACh in determining patterns of cortical activity and functional differences arising from the patterns.