Hippocampal neurons' cytosolic and membrane-bound ribosomal transcript profiles are differentially regulated by learning and subsequent sleep.

The hippocampus is essential for consolidating transient experiences into long-lasting memories. Memory consolidation is facilitated by postlearning sleep, although the underlying cellular mechanisms are largely unknown. We took an unbiased approach to this question by using a mouse model of hippocampally mediated, sleep-dependent memory consolidation (contextual fear memory). Because synaptic plasticity is associated with changes to both neuronal cell membranes (e.g., receptors) and cytosol (e.g., cytoskeletal elements), we characterized how these cell compartments are affected by learning and subsequent sleep or sleep deprivation (SD). Translating ribosome affinity purification was used to profile ribosome-associated RNAs in different subcellular compartments (cytosol and membrane) and in different cell populations (whole hippocampus, Camk2a+ neurons, or highly active neurons with phosphorylated ribosomal subunit S6 [pS6+]). We examined how transcript profiles change as a function of sleep versus SD and prior learning (contextual fear conditioning; CFC). While sleep loss altered many cytosolic ribosomal transcripts, CFC altered almost none, and CFC-driven changes were occluded by subsequent SD. In striking contrast, SD altered few transcripts on membrane-bound (MB) ribosomes, while learning altered many more (including long non-coding RNAs [lncRNAs]). The cellular pathways most affected by CFC were involved in structural remodeling. Comparisons of post-CFC MB transcript profiles between sleeping and SD mice implicated changes in cellular metabolism in Camk2a+ neurons and protein synthesis in highly active pS6+ (putative "engram") neurons as biological processes disrupted by SD. These findings provide insights into how learning affects hippocampal neurons and suggest that the effects of SD on memory consolidation are cell type and subcellular compartment specific.

Sleep loss drives acetylcholine- and somatostatin interneuron-mediated gating of hippocampal activity to inhibit memory consolidation.

Sleep loss disrupts consolidation of hippocampus-dependent memory. To characterize effects of learning and sleep loss, we quantified activity-dependent phosphorylation of ribosomal protein S6 (pS6) across the dorsal hippocampus of mice. We find that pS6 is enhanced in dentate gyrus (DG) following single-trial contextual fear conditioning (CFC) but is reduced throughout the hippocampus after brief sleep deprivation (SD; which disrupts contextual fear memory [CFM] consolidation). To characterize neuronal populations affected by SD, we used translating ribosome affinity purification sequencing to identify cell type-specific transcripts on pS6 ribosomes (pS6-TRAP). Cell type-specific enrichment analysis revealed that SD selectively activated hippocampal somatostatin-expressing (Sst+) interneurons and cholinergic and orexinergic hippocampal inputs. To understand the functional consequences of SD-elevated Sst+ interneuron activity, we used pharmacogenetics to activate or inhibit hippocampal Sst+ interneurons or cholinergic input from the medial septum. The activation of either cell population was sufficient to disrupt sleep-dependent CFM consolidation by gating activity in granule cells. The inhibition of either cell population during sleep promoted CFM consolidation and increased S6 phosphorylation among DG granule cells, suggesting their disinhibition by these manipulations. The inhibition of either population across post-CFC SD was insufficient to fully rescue CFM deficits, suggesting that additional features of sleeping brain activity are required for consolidation. Together, our data suggest that state-dependent gating of DG activity may be mediated by cholinergic input and local Sst+ interneurons. This mechanism could act as a sleep loss-driven inhibitory gate on hippocampal information processing.

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.

Theta-gamma coupling emerges from spatially heterogeneous cholinergic neuromodulation.

Theta and gamma rhythms and their cross-frequency coupling play critical roles in perception, attention, learning, and memory. Available data suggest that forebrain acetylcholine (ACh) signaling promotes theta-gamma coupling, although the mechanism has not been identified. Recent evidence suggests that cholinergic signaling is both temporally and spatially constrained, in contrast to the traditional notion of slow, spatially homogeneous, and diffuse neuromodulation. Here, we find that spatially constrained cholinergic stimulation can generate theta-modulated gamma rhythms. Using biophysically-based excitatory-inhibitory (E-I) neural network models, we simulate the effects of ACh on neural excitability by varying the conductance of a muscarinic receptor-regulated K+ current. In E-I networks with local excitatory connectivity and global inhibitory connectivity, we demonstrate that theta-gamma-coupled firing patterns emerge in ACh modulated network regions. Stable gamma-modulated firing arises within regions with high ACh signaling, while theta or mixed theta-gamma activity occurs at the peripheries of these regions. High gamma activity also alternates between different high-ACh regions, at theta frequency. Our results are the first to indicate a causal role for spatially heterogenous ACh signaling in the emergence of localized theta-gamma rhythmicity. Our findings also provide novel insights into mechanisms by which ACh signaling supports the brain region-specific attentional processing of sensory information.

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.

Resonance with subthreshold oscillatory drive organizes activity and optimizes learning in neural networks.

Network oscillations across and within brain areas are critical for learning and performance of memory tasks. While a large amount of work has focused on the generation of neural oscillations, their effect on neuronal populations' spiking activity and information encoding is less known. Here, we use computational modeling to demonstrate that a shift in resonance responses can interact with oscillating input to ensure that networks of neurons properly encode new information represented in external inputs to the weights of recurrent synaptic connections. Using a neuronal network model, we find that due to an input current-dependent shift in their resonance response, individual neurons in a network will arrange their phases of firing to represent varying strengths of their respective inputs. As networks encode information, neurons fire more synchronously, and this effect limits the extent to which further "learning" (in the form of changes in synaptic strength) can occur. We also demonstrate that sequential patterns of neuronal firing can be accurately stored in the network; these sequences are later reproduced without external input (in the context of subthreshold oscillations) in both the forward and reverse directions (as has been observed following learning in vivo). To test whether a similar mechanism could act in vivo, we show that periodic stimulation of hippocampal neurons coordinates network activity and functional connectivity in a frequency-dependent manner. We conclude that resonance with subthreshold oscillations provides a plausible network-level mechanism to accurately encode and retrieve information without overstrengthening connections between neurons.

Network and cellular mechanisms underlying heterogeneous excitatory/inhibitory balanced states.

Recent work has explored spatiotemporal relationships between excitatory (E) and inhibitory (I) signaling within neural networks, and the effect of these relationships on network activity patterns. Data from these studies have indicated that excitation and inhibition are maintained at a similar level across long time periods and that excitatory and inhibitory currents may be tightly synchronized. Disruption of this balance-leading to an aberrant E/I ratio-is implicated in various brain pathologies. However, a thorough characterization of the relationship between E and I currents in experimental settings is largely impossible, due to their tight regulation at multiple cellular and network levels. Here, we use biophysical neural network models to investigate the emergence and properties of balanced states by heterogeneous mechanisms. Our results show that a network can homeostatically regulate the E/I ratio through interactions among multiple cellular and network factors, including average firing rates, synaptic weights and average neural depolarization levels in excitatory/inhibitory populations. Complex and competing interactions between firing rates and depolarization levels allow these factors to alternately dominate network dynamics in different synaptic weight regimes. This leads to the emergence of distinct mechanisms responsible for determining a balanced state and its dynamical correlate. Our analysis provides a comprehensive picture of how E/I ratio changes when manipulating specific network properties, and identifies the mechanisms regulating E/I balance. These results provide a framework to explain the diverse, and in some cases, contradictory experimental observations on the E/I state in different brain states and conditions.

Cortically coordinated NREM thalamocortical oscillations play an essential, instructive role in visual system plasticity.

Two long-standing questions in neuroscience are how sleep promotes brain plasticity and why some forms of plasticity occur preferentially during sleep vs. wake. Establishing causal relationships between specific features of sleep (e.g., network oscillations) and sleep-dependent plasticity has been difficult. Here we demonstrate that presentation of a novel visual stimulus (a single oriented grating) causes immediate, instructive changes in the firing of mouse lateral geniculate nucleus (LGN) neurons, leading to increased firing-rate responses to the presented stimulus orientation (relative to other orientations). However, stimulus presentation alone does not affect primary visual cortex (V1) neurons, which show response changes only after a period of subsequent sleep. During poststimulus nonrapid eye movement (NREM) sleep, LGN neuron overall spike-field coherence (SFC) with V1 delta (0.5-4 Hz) and spindle (7-15 Hz) oscillations increased, with neurons most responsive to the presented stimulus showing greater SFC. To test whether coherent communication between LGN and V1 was essential for cortical plasticity, we first tested the role of layer 6 corticothalamic (CT) V1 neurons in coherent firing within the LGN-V1 network. We found that rhythmic optogenetic activation of CT V1 neurons dramatically induced coherent firing in LGN neurons and, to a lesser extent, in V1 neurons in the other cortical layers. Optogenetic interference with CT feedback to LGN during poststimulus NREM sleep (but not REM or wake) disrupts coherence between LGN and V1 and also blocks sleep-dependent response changes in V1. We conclude that NREM oscillations relay information regarding prior sensory experience between the thalamus and cortex to promote cortical plasticity.

Sleep loss disrupts Arc expression in dentate gyrus neurons.

Sleep loss affects many aspects of cognition, and memory consolidation processes occurring in the hippocampus seem particularly vulnerable to sleep loss. The immediate-early gene Arc plays an essential role in both synaptic plasticity and memory formation, and its expression is altered by sleep. Here, using a variety of techniques, we have characterized the effects of brief (3-h) periods of sleep vs. sleep deprivation (SD) on the expression of Arc mRNA and Arc protein in the mouse hippocampus and cortex. By comparing the relative abundance of mature Arc mRNA with unspliced pre-mRNA, we see evidence that during SD, increases in Arc across the cortex, but not hippocampus, reflect de novo transcription. Arc increases in the hippocampus during SD are not accompanied by changes in pre-mRNA levels, suggesting that increases in mRNA stability, not transcription, drives this change. Using in situ hybridization (together with behavioral observation to quantify sleep amounts), we find that in the dorsal hippocampus, SD minimally affects Arc mRNA expression, and decreases the number of dentate gyrus (DG) granule cells expressing Arc. This is in contrast to neighboring cortical areas, which show large increases in neuronal Arc expression after SD. Using immunohistochemistry, we find that Arc protein expression is also differentially affected in the cortex and DG with SD - while larger numbers of cortical neurons are Arc+, fewer DG granule cells are Arc+, relative to the same regions in sleeping mice. These data suggest that with regard to expression of plasticity-regulating genes, sleep (and SD) can have differential effects in hippocampal and cortical areas. This may provide a clue regarding the susceptibility of performance on hippocampus-dependent tasks to deficits following even brief periods of sleep loss.

Hippocampal Network Oscillations Rescue Memory Consolidation Deficits Caused by Sleep Loss.

Oscillations in the hippocampal network during sleep are proposed to play a role in memory storage by patterning neuronal ensemble activity. Here we show that following single-trial fear learning, sleep deprivation (which impairs memory consolidation) disrupts coherent firing rhythms in hippocampal area CA1. State-targeted optogenetic inhibition of CA1 parvalbumin-expressing (PV+) interneurons during postlearning NREM sleep, but not REM sleep or wake, disrupts contextual fear memory (CFM) consolidation in a manner similar to sleep deprivation. NREM-targeted inhibition disrupts CA1 network oscillations which predict successful memory storage. Rhythmic optogenetic activation of PV+ interneurons following learning generates CA1 oscillations with coherent principal neuron firing. This patterning of CA1 activity rescues CFM consolidation in sleep-deprived mice. Critically, behavioral and optogenetic manipulations that disrupt CFM also disrupt learning-induced stabilization of CA1 ensembles' communication patterns in the hours following learning. Conversely, manipulations that promote CFM also promote long-term stability of CA1 communication patterns. We conclude that sleep promotes memory consolidation by generating coherent rhythms of CA1 network activity, which provide consistent communication patterns within neuronal ensembles. Most importantly, we show that this rhythmic patterning of activity is sufficient to promote long-term memory storage in the absence of sleep.

Extracellular signal-regulated kinase (ERK) activity during sleep consolidates cortical plasticity in vivo.

Ocular dominance plasticity (ODP) in the cat primary visual cortex (V1) is induced during waking by monocular deprivation (MD) and consolidated during subsequent sleep. The mechanisms underlying this process are incompletely understood. Extracellular signal-regulated kinase (ERK) is activated in V1 during sleep after MD, but it is unknown whether ERK activation during sleep is necessary for ODP consolidation. We investigated the role of ERK in sleep-dependent ODP consolidation by inhibiting the ERK-activating enzyme MEK in V1 (via U0126) during post-MD sleep. ODP consolidation was then measured with extracellular microelectrode recordings. Western blot analysis was used to confirm the efficacy of U0126 and to examine proteins downstream of ERK. U0126 abolished ODP consolidation and reduced both phosphorylation of eukaryotic initiation factor 4E (eIF4E) and levels of the synaptic marker PSD-95. Furthermore, interfering with ERK-mediated translation by inhibiting MAP kinase-interacting kinase 1 (Mnk1) with CGP57380 mimicked the effects of U0126. These results demonstrate that ODP consolidation requires sleep-dependent activation of the ERK-Mnk1 pathway.

Visual experience and subsequent sleep induce sequential plastic changes in putative inhibitory and excitatory cortical neurons.

Ocular dominance plasticity in the developing primary visual cortex is initiated by monocular deprivation (MD) and consolidated during subsequent sleep. To clarify how visual experience and sleep affect neuronal activity and plasticity, we continuously recorded extragranular visual cortex fast-spiking (FS) interneurons and putative principal (i.e., excitatory) neurons in freely behaving cats across periods of waking MD and post-MD sleep. Consistent with previous reports in mice, MD induces two related changes in FS interneurons: a response shift in favor of the closed eye and depression of firing. Spike-timing-dependent depression of open-eye-biased principal neuron inputs to FS interneurons may mediate these effects. During post-MD nonrapid eye movement sleep, principal neuron firing increases and becomes more phase-locked to slow wave and spindle oscillations. Ocular dominance (OD) shifts in favor of open-eye stimulation--evident only after post-MD sleep--are proportional to MD-induced changes in FS interneuron activity and to subsequent sleep-associated changes in principal neuron activity. OD shifts are greatest in principal neurons that fire 40-300 ms after neighboring FS interneurons during post-MD slow waves. Based on these data, we propose that MD-induced changes in FS interneurons play an instructive role in ocular dominance plasticity, causing disinhibition among open-eye-biased principal neurons, which drive plasticity throughout the visual cortex during subsequent sleep.

Form and Function of Sleep Spindles across the Lifespan.

Since the advent of EEG recordings, sleep spindles have been identified as hallmarks of non-REM sleep. Despite a broad general understanding of mechanisms of spindle generation gleaned from animal studies, the mechanisms underlying certain features of spindles in the human brain, such as "global" versus "local" spindles, are largely unknown. Neither the topography nor the morphology of sleep spindles remains constant throughout the lifespan. It is likely that changes in spindle phenomenology during development and aging are the result of dramatic changes in brain structure and function. Across various developmental windows, spindle activity is correlated with general cognitive aptitude, learning, and memory; however, these correlations vary in strength, and even direction, depending on age and metrics used. Understanding these differences across the lifespan should further clarify how these oscillations are generated and their function under a variety of circumstances. We discuss these issues, and their translational implications for human cognitive function. Because sleep spindles are similarly affected in disorders of neurodevelopment (such as schizophrenia) and during aging (such as neurodegenerative conditions), both types of disorders may benefit from therapies based on a better understanding of spindle function.

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.

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.

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.

Hypnotic treatment improves sleep architecture and EEG disruptions and rescues memory deficits in a mouse model of fragile X syndrome.

Fragile X syndrome (FXS) is associated with disrupted cognition and sleep abnormalities. Sleep loss negatively impacts cognitive function, and one untested possibility is that disrupted cognition in FXS is exacerbated by abnormal sleep. We tested whether ML297, a hypnotic acting on G-protein-activated inward-rectifying potassium (GIRK) channels, could reverse sleep phenotypes and disrupted memory in Fmr1-/y mice. Fmr1-/y mice exhibit reduced non-rapid eye movement (NREM) sleep and fragmented NREM architecture, altered sleep electroencephalogram (EEG) oscillations, and reduced EEG coherence between cortical areas; these are partially reversed following ML297 administration. Treatment following contextual fear or spatial learning restores disrupted memory consolidation in Fmr1-/y mice. During memory recall, Fmr1-/y mice show an altered balance of activity among hippocampal principal neurons vs. parvalbumin-expressing interneurons; this is partially reversed by ML297. Because sleep disruption could impact neurophysiological phenotypes in FXS, augmenting sleep may improve disrupted cognition in this disorder.

Set and setting: how behavioral state regulates sensory function and plasticity.

Recently developed neuroimaging and electrophysiological techniques are allowing us to answer fundamental questions about how behavioral states regulate our perception of the external environment. Studies using these techniques have yielded surprising insights into how sensory processing is affected at the earliest stages by attention and motivation, and how new sensory information received during wakefulness (e.g., during learning) continues to affect sensory brain circuits (leading to plastic changes) during subsequent sleep. This review aims to describe how brain states affect sensory response properties among neurons in primary and secondary sensory cortices, and how this relates to psychophysical detection thresholds and performance on sensory discrimination tasks. This is not intended to serve as a comprehensive overview of all brain states, or all sensory systems, but instead as an illustrative description of how three specific state variables (attention, motivation, and vigilance [i.e., sleep vs. wakefulness]) affect sensory systems in which they have been best studied.

Atypical hypnotic compound ML297 restores sleep architecture immediately following emotionally valenced learning, to promote memory consolidation and hippocampal network activation during recall.

Sleep plays a critical role in consolidating many forms of hippocampus-dependent memory. While various classes of hypnotic drugs have been developed in recent years, it remains unknown whether, or how, some of them affect sleep-dependent memory consolidation mechanisms. We find that ML297, a recently developed candidate hypnotic agent targeting a new mechanism (activating GIRK1/2-subunit containing G-protein coupled inwardly rectifying potassium [GIRK] channels), alters sleep architecture in mice over the first 6 hr following a single-trial learning event. Following contextual fear conditioning (CFC), ML297 reversed post-CFC reductions in NREM sleep spindle power and REM sleep amounts and architecture, renormalizing sleep features to what was observed at baseline, prior to CFC. Renormalization of post-CFC REM sleep latency, REM sleep amounts, and NREM spindle power were all associated with improved contextual fear memory (CFM) consolidation. We find that improvements in CFM consolidation due to ML297 are sleep-dependent, and are associated with increased numbers of highly activated dentate gyrus (DG), CA1, and CA3 neurons during CFM recall. Together our findings suggest that GIRK1/2 channel activation restores normal sleep architecture- including REM sleep, which is normally suppressed following CFC-and increases the number of hippocampal neurons incorporated into the CFM engram during memory consolidation.

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.