Sleep Promotes, and Sleep Loss Inhibits, Selective Changes in Firing Rate, Response Properties and Functional Connectivity of Primary Visual Cortex Neurons

Brief sleep disruption alters synaptic structures among hippocampal and neocortical somatostatin-expressing interneurons

Brief sleep loss can disrupt cognition, including information processing in neocortex and hippocampus. Recent studies have identified alterations in synaptic structures of principal neurons within these circuits 1-3 . However, while in vivo recording and bioinformatic data suggest that inhibitory interneurons are more strongly affected by sleep loss 4-9 , it is unclear how sleep and sleep deprivation affect interneurons' synapses. Recent data suggest that activity among hippocampal somatostatin-expressing (SST+) interneurons is selectively increased by experimental sleep disruption 8 . We used Brainbow 3.0 10 to label SST+ interneurons in the dorsal hippocampus, prefrontal cortex, and visual cortex of SST-CRE transgenic mice, then compared synaptic structures in labeled neurons after a 6-h period of ad lib sleep, or gentle handling sleep deprivation (SD) starting at lights on. We find that dendritic spine density among SST+ interneurons in both hippocampus and neocortex was altered in a subregion-specific manner, with increased overall and thin spine density in CA1, decreased mushroom spine density in CA3, and decreased overall and stubby spine density in V1 after SD. Spine size also changed significantly after SD, with dramatic increases in spine volume and surface area in CA3, and small but significant decreases in CA1, PFC and V1. Together, our data suggest that the synaptic connectivity of SST+ interneurons is significantly altered, in a brain region-specific manner, by a few hours of sleep loss. Further, they suggest that sleep loss can disrupt cognition by altering the balance of excitation and inhibition in hippocampal and neocortical networks.

Significance Statement

Changes to the function of somatostatin-expressing (SST+) interneurons have been implicated in the etiology of psychiatric and neurological disorders in which both cognition and sleep behavior are affected. Here, we measure the effects of very brief experimental sleep deprivation on synaptic structures of SST+ interneurons in hippocampus and neocortex, in brain structures critical for sleep-dependent memory processing. We find that only six hours of sleep deprivation restructures SST+ interneurons' dendritic spines, causing widespread and subregion-specific changes to spine density and spine size. These changes have the potential to dramatically alter excitatory-inhibitory balance across these brain networks, leading to cognitive disruptions commonly associated with sleep loss.

Sleep-dependent engram reactivation during hippocampal memory consolidation associated with subregion-specific biosynthetic changes

Post-learning sleep is essential for hippocampal memory processing, including contextual fear memory consolidation. We labeled context-encoding engram neurons in the hippocampal dentate gyrus (DG) and assessed reactivation of these neurons after fear learning. Post-learning sleep deprivation (SD) selectively disrupted reactivation of inferior blade DG engram neurons, linked to SD-induced suppression of neuronal activity in the inferior, but not superior DG blade. Subregion-specific spatial profiling of transcripts revealed that transcriptomic responses to SD differed greatly between hippocampal CA1, CA3, and DG inferior blade, superior blade, and hilus. Activity-driven transcripts, and those associated with cytoskeletal remodeling, were selectively suppressed in the inferior blade. Critically, learning-driven transcriptomic changes differed dramatically between the DG blades and were absent from all other regions. Together, these data suggest that the DG is critical for sleep-dependent memory consolidation, and that the effects of sleep loss on the hippocampus are highly subregion-specific.

Neuromodulation via muscarinic acetylcholine pathway can facilitate distinct, complementary, and sequential roles for NREM and REM states during sleep-dependent memory consolidation

Across vertebrate species, sleep consists of repeating cycles of NREM followed by REM. However, the respective functions of NREM, REM, and their stereotypic cycling pattern are not well understood. Using a simplified biophysical network model, we show that NREM and REM sleep can play differential and critical roles in memory consolidation primarily regulated, based on state-specific changes in cholinergic signaling. Within this network, decreasing and increasing muscarinic acetylcholine (ACh) signaling during bouts of NREM and REM, respectively, differentially alters neuronal excitability and excitatory/inhibitory balance. During NREM, deactivation of inhibitory neurons leads to network-wide disinhibition and bursts of synchronized activity led by firing in engram neurons. These features strengthen connections from the original engram neurons to less-active network neurons. In contrast, during REM, an increase in network inhibition suppresses firing in all but the most-active excitatory neurons, leading to competitive strengthening/pruning of the memory trace. We tested the predictions of the model against in vivo recordings from mouse hippocampus during active sleep-dependent memory storage. Consistent with modeling results, we find that functional connectivity between CA1 neurons changes differentially at transition from NREM to REM sleep during learning. Returning to the model, we find that an iterative sequence of state-specific activations during NREM/REM cycling is essential for memory storage in the network, serving a critical role during simultaneous consolidation of multiple memories. Together these results provide a testable mechanistic hypothesis for the respective roles of NREM and REM sleep, and their universal relative timing, in memory consolidation.

Significance statement

Using a simplified computational model and in vivo recordings from mouse hippocampus, we show that NREM and REM sleep can play differential roles in memory consolidation. The specific neurophysiological features of the two sleep states allow for expansion of memory traces (during NREM) and prevention of overlap between different memory traces (during REM). These features are likely essential in the context of storing more than one new memory simultaneously within a brain network.

Brain state transitions primarily impact the spontaneous rate of slow-firing neurons

The spontaneous firing of neurons is modulated by brain state. Here, we examine how such modulation impacts the overall distribution of firing rates in neuronal populations of neocortical, hippocampal, and thalamic areas across natural and pharmacologically driven brain state transitions. We report that across all the examined combinations of brain area and state transition category, the structure of rate modulation is similar, with almost all fast-firing neurons experiencing proportionally weak modulation, while slow-firing neurons exhibit high inter-neuron variability in the modulation magnitude, leading to a stronger modulation on average. We further demonstrate that this modulation structure is linked to the left-skewed distribution of firing rates on the logarithmic scale and is recapitulated by bivariate log-gamma, but not Gaussian, distributions. Our findings indicate that a preconfigured log-rate distribution with rigid fast-firing neurons and a long left tail of malleable slow-firing neurons is a generic property of forebrain neuronal circuits.

Familiarization with ambulatory sleep and blood pressure monitoring is necessary for representative data collection

Ambulatory sleep and blood pressure monitoring are gaining popularity as these can be completed in an individual's home. Little is known regarding the reliability of data and the time it takes to acclimate to the equipment. This study aimed to determine how many nights of wearing the monitoring equipment were required to restore sleep architecture and blood pressure data to baseline. It was hypothesized familiarization would be demonstrated by night 3. Ten male and 10 female subjects completed three nights of sleep and blood pressure recordings. At visit 1, the subjects were familiarized with the equipment and instructed to wear the Sleep Profiler{trade mark, serif} and SunTech Medical Oscar2 ambulatory blood pressure cuff simultaneously for three consecutive nights, then subjects returned the equipment. The percent of time spent in rapid eye-movement (REM) sleep was statistically different on night 3 when compared to night 1. Wake-after-sleep onset and sleep latency were not statistically different between nights 1, 2, and 3. Systolic, diastolic, and pulse pressure were all significantly lower on night 3 compared to night 1. Cortical and autonomic arousals were statistically different on night 3. Ambulatory sleep and blood pressure monitoring need at least 3 nights for familiarization. The percent of time spent in REM sleep was statistically different on night 3 when compared to night 1. Systolic blood pressure, diastolic blood pressure, and pulse pressure were all significantly lower on night 3 compared to night 1. Cortical and autonomic arousals were statistically different on nights 3 and 2, respectively compared to night 1. Based on these findings, ambulatory sleep and blood pressure monitoring takes three nights before the data are reliable and the person is familiarized with the mode of measurement. Therefore, it is recommended to use at least three nights of data collection when using the Sleep Profiler and Oscar2 ambulatory blood pressure cuff in order for results to be valid and reliable.

Spontaneous and Visual Stimulation Evoked Firing Sequences Are Distinct Under Desflurane Anesthesia

Recurring spike sequences are thought to underlie cortical computations and may be essential for information processing in the conscious state. How anesthesia at graded levels may influence spontaneous and stimulus-related spike sequences in visual cortex has not been fully elucidated. We recorded extracellular single-unit activity in the rat primary visual cortex in vivo during wakefulness and three levels of anesthesia produced by desflurane. The latencies of spike sequences within 0-200 ms from the onset of spontaneous UP states and visual flash-evoked responses were compared. During wakefulness, spike latency patterns linked to the local field potential theta cycle were similar to stimulus-evoked patterns. Under desflurane anesthesia, spontaneous UP state sequences differed from flash-evoked sequences due to the recruitment of low-firing excitatory neurons to the UP state. Flash-evoked spike sequences showed higher reliability and longer latency when stimuli were applied during DOWN states compared to UP states. At deeper levels, desflurane altered both UP state and flash-evoked spike sequences by selectively suppressing inhibitory neuron firing. The results reveal desflurane-induced complex changes in cortical firing sequences that may influence visual information processing.

Enriched binocular experience followed by sleep optimally restores binocular visual cortical responses in a mouse model of amblyopia

Studies of primary visual cortex have furthered our understanding of amblyopia, long-lasting visual impairment caused by imbalanced input from the two eyes during childhood, which is commonly treated by patching the dominant eye. However, the relative impacts of monocular vs. binocular visual experiences on recovery from amblyopia are unclear. Moreover, while sleep promotes visual cortex plasticity following loss of input from one eye, its role in recovering binocular visual function is unknown. Using monocular deprivation in juvenile male mice to model amblyopia, we compared recovery of cortical neurons' visual responses after identical-duration, identical-quality binocular or monocular visual experiences. We demonstrate that binocular experience is quantitatively superior in restoring binocular responses in visual cortex neurons. However, this recovery was seen only in freely-sleeping mice; post-experience sleep deprivation prevented functional recovery. Thus, both binocular visual experience and subsequent sleep help to optimally renormalize bV1 responses in a mouse model of amblyopia.

Do Sleep Disturbances have a Dual Effect on Alzheimer's Disease?

Sleep disturbances and Alzheimer's disease have deleterious effects on various physiological and cognitive functions including synaptic plasticity, oxidative stress, neuroinflammation, and memory. In addition, clock genes expression is significantly altered following sleep disturbances, which may be involved in the pathogenesis of Alzheimer's disease. In this review article, we aimed to discuss the role of sleep disturbances and Alzheimer's disease in the regulation of synaptic plasticity, oxidative stress, neuroinflammation, and clock genes expression. Also, we aimed to find significant relationships between sleep disturbances and Alzheimer's disease in the modulation of these mechanisms. We referred to the controversial effects of sleep disturbances (particularly those related to the duration of sleep deprivation) on the modulation of synaptic function and neuroinflammation. We aimed to know that, do sleep disturbances have a dual effect on the progression of Alzheimer's disease? Although numerous studies have discussed the association between sleep disturbances and Alzheimer's disease, the new point of this study was to focus on the controversial effects of sleep disturbances on different biological functions, and to evaluate the potential dualistic role of sleep disturbances in the pathogenesis of Alzheimer's disease.

Heterogeneous mechanisms for synchronization of networks of resonant neurons under different E/I balance regimes

Rhythmic synchronization of neuronal firing patterns is a widely present phenomenon in the brain-one that seems to be essential for many cognitive processes. A variety of mechanisms contribute to generation and synchronization of network oscillations, ranging from intrinsic cellular excitability to network mediated effects. However, it is unclear how these mechanisms interact together. Here, using computational modeling of excitatory-inhibitory neural networks, we show that different synchronization mechanisms dominate network dynamics at different levels of excitation and inhibition (i.e. E/I levels) as synaptic strength is systematically varied. Our results show that with low synaptic strength networks are sensitive to external oscillatory drive as a synchronizing mechanism-a hallmark of resonance. In contrast, in a strongly-connected regime, synchronization is driven by network effects via the direct interaction between excitation and inhibition, and spontaneous oscillations and cross-frequency coupling emerge. Unexpectedly, we find that while excitation dominates network synchrony at low excitatory coupling strengths, inhibition dominates at high excitatory coupling strengths. Together, our results provide novel insights into the oscillatory modulation of firing patterns in different excitation/inhibition regimes.

Site-dependent shaping of field potential waveforms

The activity of neuron populations gives rise to field potentials (FPs) that extend beyond the sources. Their mixing in the volume dilutes the original temporal motifs in a site-dependent manner, a fact that has received little attention. And yet, it potentially rids of physiological significance the time-frequency parameters of individual waves (amplitude, phase, duration). This is most likely to happen when a single source or a local origin is erroneously assumed. Recent studies using spatial treatment of these signals and anatomically realistic modeling of neuron aggregates provide convincing evidence for the multisource origin and site-dependent blend of FPs. Thus, FPs generated in primary structures like the neocortex and hippocampus reach far and cross-contaminate each other but also, they add and even impose their temporal traits on distant regions. Furthermore, both structures house neurons that act as spatially distinct (but overlapped) FP sources whose activation is state, region, and time dependent, making the composition of so-called local FPs highly volatile and strongly site dependent. Since the spatial reach cannot be predicted without source geometry, it is important to assess whether waveforms and temporal motifs arise from a single source; otherwise, those from each of the co-active sources should be sought.

Tinnitus: at a crossroad between phantom perception and sleep

Sensory disconnection from the environment is a hallmark of sleep and is crucial for sleep maintenance. It remains unclear, however, whether internally generated percepts—phantom percepts—may overcome such disconnection and, in turn, how sleep and its effect on sensory processing and brain plasticity may affect the function of the specific neural networks underlying such phenomena. A major hurdle in addressing this relationship is the methodological difficulty to study sensory phantoms, due to their subjective nature and lack of control over the parameters or neural activity underlying that percept. Here, we explore the most prevalent phantom percept, subjective tinnitus—or tinnitus for short—as a model to investigate this. Tinnitus is the permanent perception of a sound with no identifiable corresponding acoustic source. This review offers a novel perspective on the functional interaction between brain activity across the sleep–wake cycle and tinnitus. We discuss characteristic features of brain activity during tinnitus in the awake and the sleeping brain and explore its effect on sleep functions and homeostasis. We ask whether local changes in cortical activity in tinnitus may overcome sensory disconnection and prevent the occurrence of global restorative sleep and, in turn, how accumulating sleep pressure may temporarily alleviate the persistence of a phantom sound. Beyond an acute interaction between sleep and neural activity, we discuss how the effects of sleep on brain plasticity may contribute to aberrant neural circuit activity and promote tinnitus consolidation. Tinnitus represents a unique window into understanding the role of sleep in sensory processing. Clarification of the underlying relationship may offer novel insights into therapeutic interventions in tinnitus management.

Stimulus-Selective Response Plasticity in Primary Visual Cortex: Progress and Puzzles

Stimulus-selective response plasticity (SRP) is a robust and lasting modification of primary visual cortex (V1) that occurs in response to exposure to novel visual stimuli. It is readily observed as a pronounced increase in the magnitude of visual evoked potentials (VEPs) recorded in response to phase-reversing grating stimuli in neocortical layer 4. The expression of SRP at the individual neuron level is equally robust, but the qualities vary depending on the neuronal type and how activity is measured. This form of plasticity is highly selective for stimulus features such as stimulus orientation, spatial frequency, and contrast. Several key insights into the significance and underlying mechanisms of SRP have recently been made. First, it occurs concomitantly and shares core mechanisms with behavioral habituation, indicating that SRP reflects the formation of long-term familiarity that can support recognition of innocuous stimuli. Second, SRP does not manifest within a recording session but only emerges after an off-line period of several hours that includes sleep. Third, SRP requires not only canonical molecular mechanisms of Hebbian synaptic plasticity within V1, but also the opposing engagement of two key subclasses of cortical inhibitory neuron: the parvalbumin- and somatostatin-expressing GABAergic interneurons. Fourth, pronounced shifts in the power of cortical oscillations from high frequency (gamma) to low frequency (alpha/beta) oscillations provide respective readouts of the engagement of these inhibitory neuronal subtypes following familiarization. In this article we will discuss the implications of these findings and the outstanding questions that remain to gain a deeper understanding of this striking form of experience-dependent plasticity.

Roles for Sleep in Neural and Behavioral Plasticity: Reviewing Variation in the Consequences of Sleep Loss

Sleep is a vital physiological state that has been broadly conserved across the evolution of animal species. While the precise functions of sleep remain poorly understood, a large body of research has examined the negative consequences of sleep loss on neural and behavioral plasticity. While sleep disruption generally results in degraded neural plasticity and cognitive function, the impact of sleep loss can vary widely with age, between individuals, and across physiological contexts. Additionally, several recent studies indicate that sleep loss differentially impacts distinct neuronal populations within memory-encoding circuitry. These findings indicate that the negative consequences of sleep loss are not universally shared, and that identifying conditions that influence the resilience of an organism (or neuron type) to sleep loss might open future opportunities to examine sleep's core functions in the brain. Here, we discuss the functional roles for sleep in adaptive plasticity and review factors that can contribute to individual variations in sleep behavior and responses to sleep loss.

Molecular Mechanisms of Memory Consolidation That Operate During Sleep

The role of sleep for brain function has been in the focus of interest for many years. It is now firmly established that sleep and the corresponding brain activity is of central importance for memory consolidation. Less clear are the underlying molecular mechanisms and their specific contribution to the formation of long-term memory. In this review, we summarize the current knowledge of such mechanisms and we discuss the several unknowns that hinder a deeper appreciation of how molecular mechanisms of memory consolidation during sleep impact synaptic function and engram formation.

Dynamical Mechanism Underlying Scale-Free Network Reorganization in Low Acetylcholine States Corresponding to Slow Wave Sleep

Sleep is indispensable for most animals' cognitive functions, and is hypothesized to be a major factor in memory consolidation. Although we do not fully understand the mechanisms of network reorganisation driving memory consolidation, available data suggests that sleep-associated neurochemical changes may be important for such processes. In particular, global acetylcholine levels change across the sleep/wake cycle, with high cholinergic tone during wake and REM sleep and low cholinergic tone during slow wave sleep. Furthermore, experimental perturbation of cholinergic tone has been shown to impact memory storage. Through in silico modeling of neuronal networks, we show how spiking dynamics change in highly heterogenous networks under varying levels of cholinergic tone, with neuronal networks under high cholinergic modulation firing asynchronously and at high frequencies, while those under low cholinergic modulation exhibit synchronous patterns of activity. We further examined the network's dynamics and its reorganization mediated via changing levels of acetylcholine within the context of different scale-free topologies, comparing network activity within the hub cells, a small group of neurons having high degree connectivity, and with the rest of the network. We show a dramatic, state-dependent change in information flow throughout the network, with highly active hub cells integrating information in a high-acetylcholine state, and transferring it to rest of the network in a low-acetylcholine state. This result is experimentally corroborated by frequency-dependent frequency changes observed in vivo experiments. Together, these findings provide insight into how new neurons are recruited into memory traces during sleep, a mechanism which may underlie system memory consolidation.

Acetylcholine-gated current translates wake neuronal firing rate information into a spike timing-based code in Non-REM sleep, stabilizing neural network dynamics during memory consolidation

Sleep is critical for memory consolidation, although the exact mechanisms mediating this process are unknown. Combining reduced network models and analysis of in vivo recordings, we tested the hypothesis that neuromodulatory changes in acetylcholine (ACh) levels during non-rapid eye movement (NREM) sleep mediate stabilization of network-wide firing patterns, with temporal order of neurons’ firing dependent on their mean firing rate during wake. In both reduced models and in vivo recordings from mouse hippocampus, we find that the relative order of firing among neurons during NREM sleep reflects their relative firing rates during prior wake. Our modeling results show that this remapping of wake-associated, firing frequency-based representations is based on NREM-associated changes in neuronal excitability mediated by ACh-gated potassium current. We also show that learning-dependent reordering of sequential firing during NREM sleep, together with spike timing-dependent plasticity (STDP), reconfigures neuronal firing rates across the network. This rescaling of firing rates has been reported in multiple brain circuits across periods of sleep. Our model and experimental data both suggest that this effect is amplified in neural circuits following learning. Together our data suggest that sleep may bias neural networks from firing rate-based towards phase-based information encoding to consolidate memories.

We show that neuromodulatory changes during non-rapid eye movement (NREM) sleep generate stable spike timing relationships between neurons, the ordering of which reflects the neurons’ relative firing rates during wake. Learning-dependent ordering of firing in the hippocampus during NREM, acting in tandem with spike timing-dependent plasticity, reconfigures neuronal firing rates across the hippocampal network. This “rescaling” of neuronal firing rates has recently been reported in multiple brain circuits across periods of sleep. Together, our results suggest that the brain is remapping frequency-biased representations of information formed during wake into timing biased-representations during NREM sleep.

The Engram's Dark Horse: How Interneurons Regulate State-Dependent Memory Processing and Plasticity

Brain states such as arousal and sleep play critical roles in memory encoding, storage, and recall. Recent studies have highlighted the role of engram neurons-populations of neurons activated during learning-in subsequent memory consolidation and recall. These engram populations are generally assumed to be glutamatergic, and the vast majority of data regarding the function of engram neurons have focused on glutamatergic pyramidal or granule cell populations in either the hippocampus, amygdala, or neocortex. Recent data suggest that sleep and wake states differentially regulate the activity and temporal dynamics of engram neurons. Two potential mechanisms for this regulation are either via direct regulation of glutamatergic engram neuron excitability and firing, or via state-dependent effects on interneuron populations-which in turn modulate the activity of glutamatergic engram neurons. Here, we will discuss recent findings related to the roles of interneurons in state-regulated memory processes and synaptic plasticity, and the potential therapeutic implications of understanding these mechanisms.

The distinctive sleep pattern of the human calcarine cortex: a stereo-electroencephalographic study

STUDY OBJECTIVES

The aim of this study was to describe the spontaneous electroencephalographic (EEG) features of sleep in the human calcarine cortex, comparing them with the well-established pattern of the parietal cortex.

METHODS

We analyzed presurgical intracerebral EEG activity in calcarine and parietal cortices during non-rapid eye movement (NREM) and rapid eye movement (REM) sleep in seven patients with drug-resistant focal epilepsy. The time course of the EEG spectral power and NREM vs REM differences was assessed. Sleep spindles were automatically detected. To assess homeostatic dynamics, we considered the first vs second half of the night ratio in the delta frequency range (0.5-4 Hz) and the rise rate of delta activity during the first sleep cycle.

RESULTS

While the parietal area showed the classically described NREM and REM sleep hallmarks, the calcarine cortex exhibited a distinctive pattern characterized by: (1) the absence of sleep spindles; (2) a large similarity between EEG power spectra of NREM and REM; and (3) reduced signs of homeostatic dynamics, with a decreased delta ratio between the first and the second half of the night, a reduced rise rate of delta activity during the first NREM sleep cycle, and lack of correlation between these measures.

CONCLUSIONS

Besides describing for the first time the peculiar sleep EEG pattern in the human calcarine cortex, our findings provide evidence that different cortical areas may exhibit specific sleep EEG pattern, supporting the view of sleep as a local process and promoting the idea that the functional role of sleep EEG features should be considered at a regional level.

Visual Recognition Is Heralded by Shifts in Local Field Potential Oscillations and Inhibitory Networks in Primary Visual Cortex

Learning to recognize and filter familiar, irrelevant sensory stimuli eases the computational burden on the cerebral cortex. Inhibition is a candidate mechanism in this filtration process, and oscillations in the cortical local field potential (LFP) serve as markers of the engagement of different inhibitory neurons. We show here that LFP oscillatory activity in visual cortex is profoundly altered as male and female mice learn to recognize an oriented grating stimulus-low-frequency (∼15 Hz peak) power sharply increases, whereas high-frequency (∼65 Hz peak) power decreases. These changes report recognition of the familiar pattern as they disappear when the stimulus is rotated to a novel orientation. Two-photon imaging of neuronal activity reveals that parvalbumin-expressing inhibitory neurons disengage with familiar stimuli and reactivate to novelty, whereas somatostatin-expressing inhibitory neurons show opposing activity patterns. We propose a model in which the balance of two interacting interneuron circuits shifts as novel stimuli become familiar.SIGNIFICANCE STATEMENT Habituation, familiarity, and novelty detection are fundamental cognitive processes that enable organisms to adaptively filter meaningless stimuli and focus attention on potentially important elements of their environment. We have shown that this process can be studied fruitfully in the mouse primary visual cortex by using simple grating stimuli for which novelty and familiarity are defined by orientation and by measuring stimulus-evoked and continuous local field potentials. Altered event-related and spontaneous potentials, and deficient habituation, are well-documented features of several neurodevelopmental psychiatric disorders. The paradigm described here will be valuable to interrogate the origins of these signals and the meaning of their disruption more deeply.

Sleep, neuronal hyperexcitability, inflammation and neurodegeneration: Does early chronic short sleep trigger and is it the key to overcoming Alzheimer's disease?

Evidence links neuroinflammation to Alzheimer's disease (AD); however, its exact contribution to the onset and progression of the disease is poorly understood. Symptoms of AD can be seen as the tip of an iceberg, consisting of a neuropathological build-up in the brain of extracellular amyloid-β (Aβ) plaques and intraneuronal hyperphosphorylated aggregates of Tau (pTau), which are thought to stem from an imbalance between its production and clearance resulting in loss of synaptic health and dysfunctional cortical connectivity. The glymphatic drainage system, which is particularly active during sleep, plays a key role in the clearance of proteinopathies. Poor sleep can cause hyperexcitability and promote Aβ and tau pathology leading to systemic inflammation. The early neuronal hyperexcitability of γ-aminobutyric acid (GABA)-ergic inhibitory interneurons and impaired inhibitory control of cortical pyramidal neurons lie at the crossroads of excitatory/inhibitory imbalance and inflammation. We outline, with a prospective framework, a possible vicious spiral linking early chronic short sleep, neuronal hyperexcitability, inflammation and neurodegeneration. Understanding the early predictors of AD, through an integrative approach, may hold promise for reducing attrition in the late stages of neuroprotective drug development.

Sleep Loss Drives Brain Region-Specific and Cell Type-Specific Alterations in Ribosome-Associated Transcripts Involved in Synaptic Plasticity and Cellular Timekeeping

Sleep and sleep loss are thought to impact synaptic plasticity, and recent studies have shown that sleep and sleep deprivation (SD) differentially affect gene transcription and protein translation in the mammalian forebrain. However, much less is known regarding how sleep and SD affect these processes in different microcircuit elements within the hippocampus and neocortex, for example, in inhibitory versus excitatory neurons. Here, we use translating ribosome affinity purification (TRAP) and in situ hybridization to characterize the effects of sleep versus SD on abundance of ribosome-associated transcripts in Camk2a-expressing (Camk2a+) pyramidal neurons and parvalbumin-expressing (PV+) interneurons in the hippocampus and neocortex of male mice. We find that while both Camk2a+ neurons and PV+ interneurons in neocortex show concurrent SD-driven increases in ribosome-associated transcripts for activity-regulated effectors of plasticity and transcriptional regulation, these transcripts are minimally affected by SD in hippocampus. Similarly, we find that while SD alters several ribosome-associated transcripts involved in cellular timekeeping in neocortical Camk2a+ and PV+ neurons, effects on circadian clock transcripts in hippocampus are minimal, and restricted to Camk2a+ neurons. Taken together, our results indicate that SD effects on transcripts associated with translating ribosomes are both cell type-specific and brain region-specific, and that these effects are substantially more pronounced in the neocortex than the hippocampus. We conclude that SD-driven alterations in the strength of synapses, excitatory-inhibitory (E-I) balance, and cellular timekeeping are likely more heterogeneous than previously appreciated.SIGNIFICANCE STATEMENT Sleep loss-driven changes in transcript and protein abundance have been used as a means to better understand the function of sleep for the brain. Here, we use translating ribosome affinity purification (TRAP) to characterize changes in abundance of ribosome-associated transcripts in excitatory and inhibitory neurons in mouse hippocampus and neocortex after a brief period of sleep or sleep loss. We show that these changes are not uniform, but are generally more pronounced in excitatory neurons than inhibitory neurons, and more pronounced in neocortex than in hippocampus.

Cell-Type-Specific Dynamics of Calcium Activity in Cortical Circuits over the Course of Slow-Wave Sleep and Rapid Eye Movement Sleep

Sleep shapes cortical network activity, fostering global homeostatic downregulation of excitability while maintaining or even upregulating excitability in selected networks in a manner that supports memory consolidation. Here, we used two-photon calcium imaging of cortical layer 2/3 neurons in sleeping male mice to examine how these seemingly opposing dynamics are balanced in cortical networks. During slow-wave sleep (SWS) episodes, mean calcium activity of excitatory pyramidal (Pyr) cells decreased. Simultaneously, however, variance in Pyr population calcium activity increased, contradicting the notion of a homogenous downregulation of network activity. Indeed, we identified a subpopulation of Pyr cells distinctly upregulating calcium activity during SWS, which were highly active during sleep spindles known to support mnemonic processing. Rapid eye movement (REM) episodes following SWS were associated with a general downregulation of Pyr cells, including the subpopulation of Pyr cells active during spindles, which persisted into following stages of sleep and wakefulness. Parvalbumin-positive inhibitory interneurons (PV-In) showed an increase in calcium activity during SWS episodes, while activity remained unchanged during REM sleep episodes. This supports the view that downregulation of Pyr calcium activity during SWS results from increased somatic inhibition via PV-In, whereas downregulation during REM sleep is achieved independently of such inhibitory activity. Overall, our findings show that SWS enables upregulation of select cortical circuits (likely those which were involved in mnemonic processing) through a spindle-related process, whereas REM sleep mediates general downregulation, possibly through synaptic re-normalization.SIGNIFICANCE STATEMENT Sleep is thought to globally downregulate cortical excitability and, concurrently, to upregulate synaptic connections in neuron ensembles with newly encoded memory, with upregulation representing a function of sleep spindles. Using in vivo two-photon calcium imaging in combination with surface EEG recordings, we classified cells based on their calcium activity during sleep spindles. Spindle-active pyramidal (Pyr) cells persistently increased calcium activity during slow-wave sleep (SWS) episodes while spindle-inactive cells decreased calcium activity. Subsequent rapid eye movement (REM) sleep episodes profoundly reduced calcium activity in both cell clusters. Results indicate that SWS allows for a spindle-related differential upregulation of ensembles whereas REM sleep functions to globally downregulate networks.

Differential Effect of Anesthesia on Visual Cortex Neurons with Diverse Population Coupling

Cortical neurons display diverse firing patterns and synchronization properties. How anesthesia alters the firing response of different neuron groups relevant for sensory information processing is unclear. Here we investigated the graded effect of anesthesia on spontaneous and visual flash-induced spike activity of different neuron groups classified based on their spike waveform, firing rate, and population coupling (the extent neurons conform to population spikes). Single-unit activity was measured from multichannel extracellular recordings in deep layers of primary visual cortex of freely moving rats in wakefulness and at three concentrations of desflurane. Anesthesia generally decreased firing rate and increased population coupling and burstiness of neurons. Population coupling and firing rate became more correlated and the pairwise correlation between neurons became more predictable by their population coupling in anesthesia. During wakefulness, visual stimulation increased firing rate; this effect was the largest and the most prolonged in neurons that exhibited high population coupling and high firing rate. During anesthesia, the early increase in firing rate (20-150 ms post-stimulus) of these neurons was suppressed, their spike timing was delayed and split into two peaks. The late response (200-400 ms post-stimulus) of all neurons was also suppressed. We conclude that anesthesia alters the visual response of primarily high-firing highly coupled neurons, which may interfere with visual sensory processing. The increased association of population coupling and firing rate during anesthesia suggests a decrease in sensory information content.

State-Dependent Cortical Unit Activity Reflects Dynamic Brain State Transitions in Anesthesia

Understanding the effects of anesthesia on cortical neuronal spiking and information transfer could help illuminate the neuronal basis of the conscious state. Recent investigations suggest that the brain state identified by local field potential spectrum is not stationary but changes spontaneously at a fixed level of anesthetic concentration. How cortical unit activity changes with dynamically transitioning brain states under anesthesia is unclear. Extracellular unit activity was measured with 64-channel silicon microelectrode arrays in cortical layers 5/6 of the primary visual cortex of chronically instrumented, freely moving male rats (n = 7) during stepwise reduction of the anesthetic desflurane (6%, 4%, 2%, and 0%). Unsupervised machine learning applied to multiunit spike patterns revealed five distinct brain states. A novel desynchronized brain state with increased spike rate variability, sample entropy, and EMG activity occurred in 6% desflurane with 40.0% frequency. The other four brain states reflected graded levels of anesthesia. As anesthesia deepened the spike rate of neurons decreased regardless of their spike rate profile at baseline conscious state. Actively firing neurons with wide-spiking pattern showed increased bursting activity along with increased spike timing variability, unit-to-population correlation, and unit-to-unit transfer entropy, despite the overall decrease in transfer entropy. The narrow-spiking neurons showed similar changes but to a lesser degree. These results suggest that (1) anesthetic effect on spike rate is distinct from sleep, (2) synchronously fragmented spiking pattern is a signature of anesthetic-induced unconsciousness, and (3) the paradoxical, desynchronized brain state in deep anesthesia contends the generally presumed monotonic, dose-dependent anesthetic effect on the brain.SIGNIFICANCE STATEMENT Recent studies suggest that spontaneous changes in brain state occur under anesthesia. However, the spiking behavior of cortical neurons associated with such state changes has not been investigated. We found that local brain states defined by multiunit activity had a nonunitary relationship with the current anesthetic level. A paradoxical brain state displaying asynchronous firing pattern and high EMG activity was found unexpectedly in deep anesthesia. In contrast, the synchronous fragmentation of neuronal spiking appeared to be a robust signature of the state of anesthesia. The findings challenge the assumption of monotonic, anesthetic dose-dependent behavior of cortical neuron populations. They enhance the interpretation of neuroscientific data obtained under anesthesia and the understanding of the neuronal basis of anesthetic-induced state of unconsciousness.

Distinct Laminar Requirements for NMDA Receptors in Experience-Dependent Visual Cortical Plasticity

Primary visual cortex (V1) is the locus of numerous forms of experience-dependent plasticity. Restricting visual stimulation to one eye at a time has revealed that many such forms of plasticity are eye-specific, indicating that synaptic modification occurs prior to binocular integration of thalamocortical inputs. A common feature of these forms of plasticity is the requirement for NMDA receptor (NMDAR) activation in V1. We therefore hypothesized that NMDARs in cortical layer 4 (L4), which receives the densest thalamocortical input, would be necessary for all forms of NMDAR-dependent and input-specific V1 plasticity. We tested this hypothesis in awake mice using a genetic approach to selectively delete NMDARs from L4 principal cells. We found, unexpectedly, that both stimulus-selective response potentiation and potentiation of open-eye responses following monocular deprivation (MD) persist in the absence of L4 NMDARs. In contrast, MD-driven depression of deprived-eye responses was impaired in mice lacking L4 NMDARs, as was L4 long-term depression in V1 slices. Our findings reveal a crucial requirement for L4 NMDARs in visual cortical synaptic depression, and a surprisingly negligible role for them in cortical response potentiation. These results demonstrate that NMDARs within distinct cellular subpopulations support different forms of experience-dependent plasticity.

Experience and sleep-dependent synaptic plasticity: from structure to activity

Synaptic plasticity is important for learning and memory. With increasing evidence linking sleep states to changes in synaptic strength, an emerging view is that sleep promotes learning and memory by facilitating experience-induced synaptic plasticity. In this review, we summarize the recent progress on the function of sleep in regulating cortical synaptic plasticity. Specifically, we outline the electroencephalogram signatures of sleep states (e.g. slow-wave sleep, rapid eye movement sleep, spindles), sleep state-dependent changes in gene and synaptic protein expression, synaptic morphology, and neuronal and network activity. We highlight studies showing that post-experience sleep potentiates experience-induced synaptic changes and discuss the potential mechanisms that may link sleep-related brain activity to synaptic structural remodelling. We conclude that both synapse formation or strengthening and elimination or weakening occur across sleep. This sleep-dependent synaptic plasticity plays an important role in neuronal circuit refinement during development and after learning, while sleep disorders may contribute to or exacerbate the development of common neurological diseases. This article is part of the Theo Murphy meeting issue 'Memory reactivation: replaying events past, present and future'.

Opposing Somatic and Dendritic Expression of Stimulus-Selective Response Plasticity in Mouse Primary Visual Cortex

Daily exposure of awake mice to a phase-reversing visual grating stimulus leads to enhancement of the visual-evoked potential (VEP) in layer 4 of the primary visual cortex (V1). This stimulus-selective response potentiation (SRP) resembles and shares mechanistic requirements with canonical long-term synaptic potentiation (LTP). However, it remains to be determined how this augmentation of a population response translates into altered neuronal activity of individual V1 neurons. To address this question, we performed longitudinal calcium imaging of layer 4 excitatory neurons in V1 and tracked changes associated with the induction and expression of SRP. We found no evidence for a net change in the fraction of visually responsive neurons as the stimulus became familiar. However, endoscopic calcium imaging of layer 4 principal neurons revealed that somatic calcium transients in response to phase-reversals of the familiar visual stimulus are reduced and undergo strong within-session adaptation. Conversely, neuropil calcium responses and VEPs are enhanced during familiar stimulus viewing, and the VEPs show reduced within-session adaptation. Consistent with the exquisite selectivity of SRP, the plasticity of cellular responses to phase-reversing gratings did not translate into altered orientation selectivity to drifting gratings. Our findings suggest a model in which augmentation of fast, short-latency synaptic (dendritic) responses, manifested as enhanced layer 4 VEPs, recruits inhibition to suppress cellular activity. Reduced cellular activity to the familiar stimulus may account for the behavioral correlate of SRP, orientation-selective long-term habituation.

Performance on the mouse vibration actuating search task is compromised by sleep deprivation

As we go about our daily routines we are continuously bombarded with environmental feedback that requires appraisal and response. Sleep loss can compromise the efficiency by which these cognitive processes function. Operationally, poor performance caused by insufficient sleep translates to increased health and safety risks in settings where attention and timely and/or accurate decisions to respond are critical (e.g., at work, on the road, etc.). Current rodent tasks that assess altered cognition after sleep deprivation (SD) do not accurately model the continuous multisensory feedback that informs goal-oriented behavior in humans. Herein, we describe the vibration actuating search task (VAST), which consists of a vibrating open field with pseudo-randomly selected entrance and target destination points. To successfully complete a trial, mice use feedback from rotary motor-induced floor vibrations to navigate from the entrance point to the target destination. Sets of 20 trials were conducted on 3 consecutive days, and before testing on the third day control mice were undisturbed while other mice were sleep deprived for 10 h. On the first 2 days mice learned the task with high success rates. Alternatively, VAST performance was compromised following SD as measured by increased failures in task completion, time to target, time spent immobile, and decreased speed as compared with undisturbed mice. The VAST enables the analysis of continuous feedback via multiple sensory modalities in mice and is applicable to a variety of operational settings.NEW & NOTEWORTHY The vibration actuating search task (VAST) is a novel performance assay that uses continuous auditory and haptic feedback to motivate and direct search behaviors in mice. The VAST is rapidly acquired by mice and performance is disrupted by sleep deprivation. The VAST has practical application in occupational settings. The cognitive aspects of the sensorimotor integration in the VAST may prove useful for rodent models of neurodegenerative disease.

Acetylcholine Mediates Dynamic Switching Between Information Coding Schemes in Neuronal Networks

Rate coding and phase coding are the two major coding modes seen in the brain. For these two modes, network dynamics must either have a wide distribution of frequencies for rate coding, or a narrow one to achieve stability in phase dynamics for phase coding. Acetylcholine (ACh) is a potent regulator of neural excitability. Acting through the muscarinic receptor, ACh reduces the magnitude of the potassium M-current, a hyperpolarizing current that builds up as neurons fire. The M-current contributes to several excitability features of neurons, becoming a major player in facilitating the transition between Type 1 (integrator) and Type 2 (resonator) excitability. In this paper we argue that this transition enables a dynamic switch between rate coding and phase coding as levels of ACh release change. When a network is in a high ACh state variations in synaptic inputs will lead to a wider distribution of firing rates across the network and this distribution will reflect the network structure or pattern of external input to the network. When ACh is low, network frequencies become narrowly distributed and the structure of a network or pattern of external inputs will be represented through phase relationships between firing neurons. This work provides insights into how modulation of neuronal features influences network dynamics and information processing across brain states.

How rhythms of the sleeping brain tune memory and synaptic plasticity

Decades of neurobehavioral research has linked sleep-associated rhythms in various brain areas to improvements in cognitive performance. However, it remains unclear what synaptic changes might underlie sleep-dependent declarative memory consolidation and procedural task improvement, and why these same changes appear not to occur across a similar interval of wake. Here we describe recent research on how one specific feature of sleep-network rhythms characteristic of rapid eye movement and non-rapid eye movement-could drive synaptic strengthening or weakening in specific brain circuits. We provide an overview of how these rhythms could affect synaptic plasticity individually and in concert. We also present an overarching hypothesis for how all network rhythms occurring across the sleeping brain could aid in encoding new information in neural circuits.

How Sleep Shapes Thalamocortical Circuit Function in the Visual System

Recent data have shown that sleep plays a beneficial role for cognitive functions such as declarative memory consolidation and perceptual learning. In this article, we review recent findings on the role of sleep in promoting adaptive visual response changes in the lateral geniculate nucleus and primary visual cortex following novel visual experiences. We discuss these findings in the context of what is currently known about how sleep affects the activity and function of thalamocortical circuits and current hypotheses regarding how sleep facilitates synaptic plasticity.

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.