Integration and Segregation of Activity in Entorhinal-Hippocampal Subregions by Neocortical Slow Oscillations

NREM sleep in the rodent neocortex and hippocampus reflects excitable dynamics

During non-rapid eye movement (NREM) sleep, neuronal populations in the mammalian forebrain alternate between periods of spiking and inactivity. Termed the slow oscillation in the neocortex and sharp wave-ripples in the hippocampus, these alternations are often considered separately but are both crucial for NREM functions. By directly comparing experimental observations of naturally-sleeping rats with a mean field model of an adapting, recurrent neuronal population, we find that the neocortical alternations reflect a dynamical regime in which a stable active state is interrupted by transient inactive states (slow waves) while the hippocampal alternations reflect a stable inactive state interrupted by transient active states (sharp waves). We propose that during NREM sleep in the rodent, hippocampal and neocortical populations are excitable: each in a stable state from which internal fluctuations or external perturbation can evoke the stereotyped population events that mediate NREM functions.

In Vivo Spiking Dynamics of Intra- and Extratelencephalic Projection Neurons in Rat Motor Cortex

In motor cortex, 2 types of deep layer pyramidal cells send their axons to other areas: intratelencephalic (IT)-type neurons specifically project bilaterally to the cerebral cortex and striatum, whereas neurons of the extratelencephalic (ET)-type, termed conventionally pyramidal tract-type, project ipsilaterally to the thalamus and other areas. Although they have totally different synaptic and membrane potential properties in vitro, little is known about the differences between them in ongoing spiking dynamics in vivo. We identified IT-type and ET-type neurons, as well as fast-spiking-type interneurons, using novel multineuronal analysis based on optogenetically evoked spike collision along their axons in behaving/resting rats expressing channelrhodopsin-2 (Multi-Linc method). We found "postspike suppression" (~100 ms) as a characteristic of ET-type neurons in spike auto-correlograms, and it remained constant independent of behavioral conditions in functionally different ET-type neurons. Postspike suppression followed even solitary spikes, and spike bursts significantly extended its duration. We also observed relatively strong spike synchrony in pairs containing IT-type neurons. Thus, spiking dynamics in IT-type and ET-type neurons may be optimized differently for precise and coordinated motor control.

Hippocampal CA1 replay becomes less prominent but more rigid without inputs from medial entorhinal cortex

The hippocampus is an essential brain area for learning and memory. However, the network mechanisms underlying memory storage, consolidation and retrieval remain incompletely understood. Place cell sequences during theta oscillations are thought to be replayed during non-theta states to support consolidation and route planning. In animals with medial entorhinal cortex (MEC) lesions, the temporal organization of theta-related hippocampal activity is disrupted, which allows us to test whether replay is also compromised. Two different analyses—comparison of co-activation patterns between running and rest epochs and analysis of the recurrence of place cell sequences—reveal that the enhancement of replay by behavior is reduced in MEC-lesioned versus control rats. In contrast, the degree of intrinsic network structure prior and subsequent to behavior remains unaffected by MEC lesions. The MEC-dependent temporal coordination during theta states therefore appears to facilitate behavior-related plasticity, but does not disrupt pre-existing functional connectivity.

Medial entorhinal cortex (MEC) is involved in memory processes that entail the replay of sequential firing of hippocampal place cells during rest periods and during behaviour. Here, the authors show that MEC lesioned animals show intact replay after an epoch of rats running on a linear track, while replay during the behavioral epoch is reduced.

Cholinergic modulation of hippocampal calcium activity across the sleep-wake cycle

Calcium is a critical second messenger in neurons that contributes to learning and memory, but how the coordination of action potentials of neuronal ensembles with the hippocampal local field potential (LFP) is reflected in dynamic calcium activity remains unclear. Here, we recorded hippocampal calcium activity with endoscopic imaging of the genetically encoded fluorophore GCaMP6 with concomitant LFP in freely behaving mice. Dynamic calcium activity was greater in exploratory behavior and REM sleep than in quiet wakefulness and slow wave sleep, behavioral states that differ with respect to theta and septal cholinergic activity, and modulated at sharp wave ripples (SWRs). Chemogenetic activation of septal cholinergic neurons expressing the excitatory hM3Dq DREADD increased calcium activity and reduced SWRs. Furthermore, inhibition of muscarinic acetylcholine receptors (mAChRs) reduced calcium activity while increasing SWRs. These results demonstrate that hippocampal dynamic calcium activity depends on behavioral and theta state as well as endogenous mAChR activation.

Brain Map of Intrinsic Functional Flexibility in Anesthetized Monkeys and Awake Humans

Emerging neuroimaging studies emphasize the dynamic organization of spontaneous brain activity in both human and non-human primates, even under anesthesia. In a recent study, we were able to characterize the heterogeneous architecture of intrinsic functional flexibility in the awake, resting human brain using time-resolved analysis and a probabilistic model. However, it is unknown whether this organizational principle is preserved in the anesthetized monkey brain, and how anesthesia affects dynamic and static measurements of spontaneous brain activity. To investigate these issues, we collected resting-state functional magnetic resonance imaging (fMRI) datasets from 178 awake humans and 11 anesthetized monkeys (all healthy). Our recently established method, a complexity measurement (i.e., Shannon entropy) of dynamic functional connectivity patterns of each brain region, was used to map the intrinsic functional flexibility across the cerebral cortex. To further explore the potential effects of anesthesia, we performed time series analysis and correlation analysis between dynamic and static measurements within awake human and anesthetized monkey brains, respectively. We observed a heterogeneous profile of intrinsic functional flexibility in the anesthetized monkey brain, which showed some similarities to that of awake humans (r = 0.30, p = 0.007). However, we found that brain activity in anesthetized monkeys generally shifted toward random fluctuations. Moreover, there is a negative correlation between nodal entropy for the distribution of dynamic functional connectivity patterns and static functional connectivity strength in anesthetized monkeys, but not in awake humans. Our findings indicate that the heterogeneous architecture of intrinsic functional flexibility across cortex probably reflects an evolutionarily conserved aspect of functional brain organization, which persists across levels of cognitive processing (states of consciousness). The coupling between nodal entropy for the distribution of dynamic functional connectivity patterns and static functional connectivity strength may serve as a potential signature of anesthesia. This study not only offers fresh insight into the evolution of brain functional architecture, but also advances our understanding of the dynamics of spontaneous brain activity.

Self-propagating, non-synaptic epileptiform activity recruits neurons by endogenous electric fields

It is well documented that synapses play a significant role in the transmission of information between neurons. However, in the absence of synaptic transmission, neural activity has been observed to continue to propagate. Previous studies have shown that propagation of epileptiform activity takes place in the absence of synaptic transmission and gap junctions and is outside the range of ionic diffusion and axonal conduction. Computer simulations indicate that electric field coupling could be responsible for the propagation of neural activity under pathological conditions such as epilepsy. Electric fields can modulate neuronal membrane voltage, but there is no experimental evidence suggesting that electric field coupling can mediate self-regenerating propagation of neural activity. Here we examine the role of electric field coupling by eliminating all forms of neural communications except electric field coupling with a cut through the neural tissue. We show that 4-AP induced activity generates an electric field capable of recruiting neurons on the distal side of the cut. Experiments also show that applied electric fields with amplitudes similar to endogenous values can induce propagating waves. Finally, we show that canceling the electrical field at a given point can block spontaneous propagation. The results from these in vitro electrophysiology experiments suggest that electric field coupling is a critical mechanism for non-synaptic neural propagation and therefore could contribute to the propagation of epileptic activity in the brain.

Lack of β-amyloid cleaving enzyme-1 (BACE1) impairs long-term synaptic plasticity but enhances granule cell excitability and oscillatory activity in the dentate gyrus in vivo

BACE1 is a β-secretase involved in the cleavage of amyloid precursor protein and the pathogenesis of Alzheimer's disease (AD). The entorhinal cortex and the dentate gyrus are important for learning and memory, which are affected in the early stages of AD. Since BACE1 is a potential target for AD therapy, it is crucial to understand its physiological role in these brain regions. Here, we examined the function of BACE1 in the dentate gyrus. We show that loss of BACE1 in the dentate gyrus leads to increased granule cell excitability, indicated by enhanced efficiency of synaptic potentials to generate granule cell spikes. The increase in granule cell excitability was accompanied by prolonged paired-pulse inhibition, altered network gamma oscillations, and impaired synaptic plasticity at entorhinal-dentate synapses of the perforant path. In summary, this is the first detailed electrophysiological study of BACE1 deletion at the network level in vivo. The results suggest that BACE1 is important for normal dentate gyrus network function. This has implications for the use of BACE1 inhibitors as therapeutics for AD therapy, since BACE1 inhibition could similarly disrupt synaptic plasticity and excitability in the entorhinal-dentate circuitry.

Neuronal firing rates diverge during REM and homogenize during non-REM

Neurons fire at highly variable intrinsic rates and recent evidence suggests that low- and high-firing rate neurons display different plasticity and dynamics. Furthermore, recent publications imply possibly differing rate-dependent effects in hippocampus versus neocortex, but those analyses were carried out separately and with potentially important differences. To more effectively synthesize these questions, we analyzed the firing rate dynamics of populations of neurons in both hippocampal CA1 and frontal cortex under one framework that avoids the pitfalls of previous analyses and accounts for regression to the mean (RTM). We observed several consistent effects across these regions. While rapid eye movement (REM) sleep was marked by decreased hippocampal firing and increased neocortical firing, in both regions firing rate distributions widened during REM due to differential changes in high- versus low-firing rate cells in parallel with increased interneuron activity. In contrast, upon non-REM (NREM) sleep, firing rate distributions narrowed while interneuron firing decreased. Interestingly, hippocampal interneuron activity closely followed the patterns observed in neocortical principal cells rather than the hippocampal principal cells, suggestive of long-range interactions. Following these undulations in variance, the net effect of sleep was a decrease in firing rates. These decreases were greater in lower-firing hippocampal neurons but also higher-firing frontal cortical neurons, suggestive of greater plasticity in these cell groups. Our results across two different regions, and with statistical corrections, indicate that the hippocampus and neocortex show a mixture of differences and similarities as they cycle between sleep states with a unifying characteristic of homogenization of firing during NREM and diversification during REM.

The Cortical States of Wakefulness

Cortical neurons process information on a background of spontaneous, ongoing activity with distinct spatiotemporal profiles defining different cortical states. During wakefulness, cortical states alter constantly in relation to behavioral context, attentional level or general motor activity. In this review article, we will discuss our current understanding of cortical states in awake rodents, how they are controlled, their impact on sensory processing, and highlight areas for future research. A common observation in awake rodents is the rapid change in spontaneous cortical activity from high-amplitude, low-frequency (LF) fluctuations, when animals are quiet, to faster and smaller fluctuations when animals are active. This transition is typically thought of as a change in global brain state but recent work has shown variation in cortical states across regions, indicating the presence of a fine spatial scale control system. In sensory areas, the cortical state change is mediated by at least two convergent inputs, one from the thalamus and the other from cholinergic inputs in the basal forebrain. Cortical states have a major impact on the balance of activity between specific subtypes of neurons, on the synchronization between nearby neurons, as well as the functional coupling between distant cortical areas. This reorganization of the activity of cortical networks strongly affects sensory processing. Thus cortical states provide a dynamic control system for the moment-by-moment regulation of cortical processing.

High-Density, Long-Lasting, and Multi-region Electrophysiological Recordings Using Polymer Electrode Arrays

The brain is a massive neuronal network, organized into anatomically distributed sub-circuits, with functionally relevant activity occurring at timescales ranging from milliseconds to years. Current methods to monitor neural activity, however, lack the necessary conjunction of anatomical spatial coverage, temporal resolution, and long-term stability to measure this distributed activity. Here we introduce a large-scale, multi-site, extracellular recording platform that integrates polymer electrodes with a modular stacking headstage design supporting up to 1,024 recording channels in freely behaving rats. This system can support months-long recordings from hundreds of well-isolated units across multiple brain regions. Moreover, these recordings are stable enough to track large numbers of single units for over a week. This platform enables large-scale electrophysiological interrogation of the fast dynamics and long-timescale evolution of anatomically distributed circuits, and thereby provides a new tool for understanding brain activity.

Hippocampal network oscillations at the interplay between innate anxiety and learned fear

The hippocampus plays a central role as a hub for episodic memory and as an integrator of multimodal sensory information in time and space. Thereby, it critically determines contextual setting and specificity of episodic memories. It is also a key site for the control of innate anxiety states and involved in psychiatric diseases with heightened anxiety and generalized fear memory such as post-traumatic stress disorder (PTSD). Expression of both innate "unlearned" anxiety and "learned" fear requires contextual processing and engagement of a brain-wide network including the hippocampus together with the amygdala and medial prefrontal cortex. Strikingly, the hippocampus is also the site of emergence of oscillatory rhythms that coordinate information processing and filtering in this network. Here, we review data on how the hippocampal network oscillations and their coordination with amygdalar and prefrontal oscillations are engaged in innate threat evaluation. We further explore how such innate oscillatory communication might have an impact on contextualization and specificity of "learned" fear. We illustrate the partial overlap of fear and anxiety networks that are built by the hippocampus in conjunction with amygdala and prefrontal cortex. We further propose that (mal)-adaptive interplay via (dis)-balanced oscillatory communication between the anxiety network and the fear network may determine the strength of fear memories and their resistance to extinction.

Slow periodic activity in the longitudinal hippocampal slice can self-propagate non-synaptically by a mechanism consistent with ephaptic coupling

KEY POINTS

Slow periodic activity can propagate with speeds around 0.1 m s-1 and be modulated by weak electric fields. Slow periodic activity in the longitudinal hippocampal slice can propagate without chemical synaptic transmission or gap junctions, but can generate electric fields which in turn activate neighbouring cells. Applying local extracellular electric fields with amplitude in the range of endogenous fields is sufficient to modulate or block the propagation of this activity both in the in silico and in the in vitro models. Results support the hypothesis that endogenous electric fields, previously thought to be too small to trigger neural activity, play a significant role in the self-propagation of slow periodic activity in the hippocampus. Experiments indicate that a neural network can give rise to sustained self-propagating waves by ephaptic coupling, suggesting a novel propagation mechanism for neural activity under normal physiological conditions.

ABSTRACT

Slow oscillations are a standard feature observed in the cortex and the hippocampus during slow wave sleep. Slow oscillations are characterized by low-frequency periodic activity (<1 Hz) and are thought to be related to memory consolidation. These waves are assumed to be a reflection of the underlying neural activity, but it is not known if they can, by themselves, be self-sustained and propagate. Previous studies have shown that slow periodic activity can be reproduced in the in vitro preparation to mimic in vivo slow oscillations. Slow periodic activity can propagate with speeds around 0.1 m s-1 and be modulated by weak electric fields. In the present study, we show that slow periodic activity in the longitudinal hippocampal slice is a self-regenerating wave which can propagate with and without chemical or electrical synaptic transmission at the same speeds. We also show that applying local extracellular electric fields can modulate or even block the propagation of this wave in both in silico and in vitro models. Our results support the notion that ephaptic coupling plays a significant role in the propagation of the slow hippocampal periodic activity. Moreover, these results indicate that a neural network can give rise to sustained self-propagating waves by ephaptic coupling, suggesting a novel propagation mechanism for neural activity under normal physiological conditions.

Origin of Gamma Frequency Power during Hippocampal Sharp-Wave Ripples

Hippocampal sharp-wave ripples (SPW-Rs) support consolidation of recently acquired episodic memories and planning future actions by generating ordered neuronal sequences of previous or future experiences. SPW-Rs are characterized by several spectral components: a slow (5-15 Hz) sharp-wave, a high-frequency "ripple" oscillation (150-200 Hz), and a slow "gamma" oscillation (20-40 Hz). Using laminar hippocampal recordings and optogenetic manipulations, we dissected the origin of these spectral components. We show that increased power in the 20-40 Hz band does not reflect an entrainment of CA1 and CA3 neurons at gamma frequency but the power envelope of overlapping ripples. Spike-local field potential coupling between unit firing in CA1 and CA3 regions during SPW-Rs is lowest in the gamma band. Longer SPW-Rs are preceded by increased firing in the entorhinal cortex. Thus, fusion of SPW-Rs leads to lengthening of their duration associated with increased power in the slow gamma band without the presence of true oscillation.

Function of local circuits in the hippocampal dentate gyrus-CA3 system

Anatomical observations, theoretical work and lesioning experiments have supported the idea that the CA3 in the hippocampus is important for encoding, storage and retrieval of memory while the dentate gyrus (DG) is important for the pattern separation of the incoming inputs from the entorhinal cortex. Study of the presumed function of the dentate gyrus in pattern separation has been hampered by the lack of reliable methods to identify different excitatory cell types in the DG. Recent papers have identified different cell types in the DG, in awake behaving animals, with more reliable methods. These studies have revealed each cell type's spatial representation as well as their involvement in pattern separation. Moreover, chronic electrophysiological recording from sleeping and waking animals also provided more insights into the operation of the DG-CA3 system for memory encoding and retrieval. This article will review the local circuit architectures and physiological properties of the DG-CA3 system and discuss how the local circuit in the DG-CA3 may function, incorporating recent physiological findings in the DG-CA3 system.

Highly Dynamic Spatiotemporal Organization of Low-Frequency Activities During Behavioral States in the Mouse Cerebral Cortex

Although low-frequency (LF < 10 Hz) activities have been considered as a hallmark of nonrapid eye movement (NREM) sleep, several studies have recently reported LF activities in the membrane potential of cortical neurons from different areas in awake mice. However, little is known about the spatiotemporal organization of LF activities across cortical areas during wakefulness and to what extent it differs during NREM sleep. We have thus investigated the dynamics of LF activities across cortical areas in awake and sleeping mice using chronic simultaneous local field potential recordings. We found that LF activities had higher amplitude in somatosensory and motor areas during quiet wakefulness and decreased in most areas during active wakefulness, resulting in a global state change that was overall correlated with motor activity. However, we also observed transient desynchronization of cortical states between areas, indicating a more local state regulation. During NREM sleep, LF activities had higher amplitude in all areas but slow-wave activity was only poorly correlated across cortical areas. Despite a maximal amplitude during NREM sleep, the coherence of LF activities between areas that are not directly connected dropped from wakefulness to NREM sleep, potentially reflecting a breakdown of long-range cortical integration associated with loss of consciousness.

Phase-amplitude coupling and epileptogenesis in an animal model of mesial temporal lobe epilepsy

Polyrhythmic coupling of oscillatory components in electrophysiological signals results from the interactions between neuronal sub-populations within and between cell assemblies. Since the mechanisms underlying epileptic disorders should affect such interactions, abnormal level of cross-frequency coupling is expected to provide a signal marker of epileptogenesis. We measured phase-amplitude coupling (PAC), a form of cross-frequency coupling between neural oscillations, in a rodent model of mesial temporal lobe epilepsy. Sprague-Dawley rats (n = 4, 250-300 g) were injected with pilocarpine (380 mg/kg, i.p) to induce a status epilepticus (SE) that was stopped after 1 h with diazepam (5 mg/kg, s.c.) and ketamine (50 mg/kg, s.c.). Control animals (n = 6) did not receive any injection or treatment. Three days after SE, all animals were implanted with bipolar electrodes in the hippocampal CA3 subfield, entorhinal cortex, dentate gyrus and subiculum. Continuous video/EEG recordings were performed 24/7 at a sampling rate of 2 kHz, over 15 consecutive days. Pilocarpine-treated animals showed interictal spikes (5.25 (±2.5) per minute) and seizures (n = 32) that appeared 7 (±0.8) days after SE. We found that CA3 was the seizure onset zone in most epileptic animals, with stronger ongoing PAC coupling between seizures than in controls (Kruskal-Wallis test: chi2 (1,36) = 46.3, Bonferroni corrected, p < 0.001). Strong PAC in CA3 occurred between the phase of slow-wave oscillations (<1 Hz) and the amplitude of faster rhythms (50-180 Hz), with the strongest bouts of high-frequency activity occurring preferentially on the ascending phase of the slow wave. We also identified that cross-frequency coupling in CA3 (rho = 0.44, p < 0.001) and subiculum (rho = 0.41, p < 0.001) was positively correlated with the daily number of seizures. Overall, our study demonstrates that cross-frequency coupling may represent a signal marker in epilepsy and suggests that this methodology could be transferred to clinical scalp MEG and EEG recordings.

The transformation of multi-sensory experiences into memories during sleep

Our everyday lives present us with a continuous stream of multi-modal sensory inputs. While most of this information is soon forgotten, sensory information associated with salient experiences can leave long-lasting memories in our minds. Extensive human and animal research has established that the hippocampus is critically involved in this process of memory formation and consolidation. However, the underlying mechanistic details are still only partially understood. Specifically, the hippocampus has often been suggested to encode information during experience, temporarily store it, and gradually transfer this information to the cortex during sleep. In rodents, ample evidence has supported this notion in the context of spatial memory, yet whether this process adequately describes the consolidation of multi-sensory experiences into memories is unclear. Here, focusing on rodent studies, I examine how multi-sensory experiences are consolidated into long term memories by hippocampal and cortical circuits during sleep. I propose that in contrast to the classical model of memory consolidation, the cortex is a "fast learner" that has a rapid and instructive role in shaping hippocampal-dependent memory consolidation. The proposed model may offer mechanistic insight into memory biasing using sensory cues during sleep.

New waves: Rhythmic electrical field stimulation systematically alters spontaneous slow dynamics across mouse neocortex

The signature rhythm of slow-wave forebrain activity is the large amplitude, slow oscillation (SO: ∼1 Hz) made up of alternating synchronous periods of activity and silence at the single cell and network levels. On each wave, the SO originates at a unique location and propagates across the neocortex. Attempts to manipulate SO activity using electrical fields have been shown to entrain cortical networks and enhance memory performance. However, neural activity during this manipulation has remained elusive due to methodological issues in typical electrical recordings. Here we took advantage of voltage-sensitive dye (VSD) imaging in a bilateral cortical preparation of urethane-anesthetized mice to track SO cortical activity and its modulation by sinusoidal electrical field stimulation applied to frontal regions. We show that under spontaneous conditions, the SO propagates in two main opposing directional patterns along an anterior lateral - posterior medial axis, displaying a rich variety of possible trajectories on any given wave. Under rhythmic field stimulation, new propagation patterns emerge, which are not observed under spontaneous conditions, reflecting stimulus-entrained activity with distributed and varied anterior initiation zones and a consistent termination zone in the posterior somatosensory cortex. Furthermore, stimulus-induced activity patterns tend to repeat cycle after cycle, showing higher stereotypy than during spontaneous activity. Our results show that slow electrical field stimulation robustly entrains and alters ongoing slow cortical dynamics during sleep-like states, suggesting a mechanism for targeting specific cortical representations to manipulate memory processes.

Low Activity Microstates During Sleep

Study Objectives:

To better understand the distinct activity patterns of the brain during sleep, we observed and investigated periods of diminished oscillatory and population spiking activity lasting for seconds during non-rapid eye movement (non-REM) sleep, which we call “LOW” activity sleep.

Methods:

We analyzed spiking and local field potential (LFP) activity of hippocampal CA1 region alongside neocortical electroencephalogram (EEG) and electromyogram (EMG) in 19 sessions from four male Long-Evans rats (260–360 g) during natural wake/sleep across the 24-hr cycle as well as data from other brain regions obtained from http://crcns.org.^1,2

Results:

LOW states lasted longer than OFF/DOWN states and were distinguished by a subset of “LOW-active” cells. LOW activity sleep was preceded and followed by increased sharp-wave ripple activity. We also observed decreased slow-wave activity and sleep spindles in the hippocampal LFP and neocortical EEG upon LOW onset, with a partial rebound immediately after LOW. LOW states demonstrated activity patterns consistent with sleep but frequently transitioned into microarousals and showed EMG and LFP differences from small-amplitude irregular activity during quiet waking. Their likelihood decreased within individual non-REM epochs yet increased over the course of sleep. By analyzing data from the entorhinal cortex of rats,¹ as well as the hippocampus, the medial prefrontal cortex, the postsubiculum, and the anterior thalamus of mice,² obtained from http://crcns.org, we confirmed that LOW states corresponded to markedly diminished activity simultaneously in all of these regions.

Conclusions:

We propose that LOW states are an important microstate within non-REM sleep that provide respite from high-activity sleep and may serve a restorative function.

Hippocampal network oscillations as mediators of behavioural metaplasticity: Insights from emotional learning

Behavioural metaplasticity is evident in experience-dependent changes of network activity patterns in neuronal circuits that connect the hippocampus, amygdala and medial prefrontal cortex. These limbic regions are key structures of a brain-wide neural network that translates emotionally salient events into persistent and vivid memories. Communication in this network by-and-large depends on behavioural state-dependent rhythmic network activity patterns that are typically generated and/or relayed via the hippocampus. In fact, specific hippocampal network oscillations have been implicated to the acquisition, consolidation and retrieval, as well as the reconsolidation and extinction of emotional memories. The hippocampal circuits that contribute to these network activities, at the same time, are subject to both Hebbian and non-Hebbian forms of plasticity during memory formation. Further, it has become evident that adaptive changes in the hippocampus-dependent network activity patterns provide an important means of adjusting synaptic plasticity. We here summarise our current knowledge on how these processes in the hippocampus in interaction with amygdala and medial prefrontal cortex mediate the formation and persistence of emotional memories.

The Nucleus Reuniens Controls Long-Range Hippocampo-Prefrontal Gamma Synchronization during Slow Oscillations

Gamma oscillations are involved in long-range coupling of distant regions that support various cognitive operations. Here we show in adult male rats that synchronized bursts of gamma oscillations bind the hippocampus (HPC) and prefrontal cortex (mPFC) during slow oscillations and slow-wave sleep, a brain state that is central for consolidation of memory traces. These gamma bursts entrained the firing of the local HPC and mPFC neuronal populations. Neurons of the nucleus reuniens (NR), which is a structural and functional hub between HPC and mPFC, demonstrated a specific increase in their firing before gamma burst onset, suggesting their involvement in HPC-mPFC binding. Chemical inactivation of NR disrupted the temporal pattern of gamma bursts and their synchronization, as well as mPFC neuronal firing. We propose that the NR drives long-range hippocampo-prefrontal coupling via gamma bursts providing temporal windows for information exchange between the HPC and mPFC during slow-wave sleep.SIGNIFICANCE STATEMENT Long-range coupling between hippocampus (HPC) and prefrontal cortex (mPFC) is believed to support numerous cognitive functions, including memory consolidation occurring during sleep. Gamma-band synchronization is a fundamental process in many neuronal operations and is instrumental in long-range coupling. Recent evidence highlights the role of nucleus reuniens (NR) in consolidation; however, how it influences hippocampo-prefrontal coupling is unknown. In this study, we show that HPC and mPFC are synchronized by gamma bursts during slow oscillations in anesthesia and natural sleep. By manipulating and recording the NR-HPC-mPFC network, we provide evidence that the NR actively promotes this long-range gamma coupling. This coupling provides the hippocampo-prefrontal circuit with a novel mechanism to exchange information during slow-wave sleep.

Clustering promotes switching dynamics in networks of noisy neurons

Macroscopic variability is an emergent property of neural networks, typically manifested in spontaneous switching between the episodes of elevated neuronal activity and the quiescent episodes. We investigate the conditions that facilitate switching dynamics, focusing on the interplay between the different sources of noise and heterogeneity of the network topology. We consider clustered networks of rate-based neurons subjected to external and intrinsic noise and derive an effective model where the network dynamics is described by a set of coupled second-order stochastic mean-field systems representing each of the clusters. The model provides an insight into the different contributions to effective macroscopic noise and qualitatively indicates the parameter domains where switching dynamics may occur. By analyzing the mean-field model in the thermodynamic limit, we demonstrate that clustering promotes multistability, which gives rise to switching dynamics in a considerably wider parameter region compared to the case of a non-clustered network with sparse random connection topology.

Learning-enhanced coupling between ripple oscillations in association cortices and hippocampus

Consolidation of declarative memories requires hippocampal-neocortical communication. Although experimental evidence supports the role of sharp-wave ripples in transferring hippocampal information to the neocortex, the exact cortical destinations and the physiological mechanisms of such transfer are not known. We used a conducting polymer-based conformable microelectrode array (NeuroGrid) to record local field potentials and neural spiking across the dorsal cortical surface of the rat brain, combined with silicon probe recordings in the hippocampus, to identify candidate physiological patterns. Parietal, midline, and prefrontal, but not primary cortical areas, displayed localized ripple (100 to 150 hertz) oscillations during sleep, concurrent with hippocampal ripples. Coupling between hippocampal and neocortical ripples was strengthened during sleep following learning. These findings suggest that ripple-ripple coupling supports hippocampal-association cortical transfer of memory traces.

Repeated anodal transcranial direct current stimulation induces neural plasticity-associated gene expression in the rat cortex and hippocampus

BACKGROUND

Anodal transcranial direct current stimulation (A-tDCS) induces a long-lasting increase in cortical excitability that can increase gene transcription in the brain.

OBJECTIVE

The purpose of this study was to evaluate the expression of genes related to activity-dependent neuronal plasticity in the sensorimotor cortex and hippocampus of young Sprague-Dawley rats following A-tDCS.

METHODS

We applied A-tDCS over the right sensorimotor cortex epicranially with a circular electrode (3 mm diameter) at 250 μA for 20 min per day for 7 consecutive days. Levels of mRNA for brain-derived neurotrophic factor (BDNF), cAMP response element-binding protein (CREB), synapsin I, Ca2+/calmodulin-dependent protein kinase II (CaMKII), activity-regulated cytoskeleton-associated protein (Arc), and c-Fos were analyzed using SYBR Green quantitative real-time polymerase chain reaction (PCR).

RESULTS

We found that 7 days of unilateral A-tDCS resulted in significant increases in transcription of all plasticity-related genes tested in the ipsilateral cortex. Daily A-tDCS also resulted in a significant increase in c-Fos mRNA in the ipsilateral hippocampus.

CONCLUSION

These results indicate that altered expression of plasticity-associated genes in the cortex and hippocampus is a molecular substrate of A-tDCS-induced neural plasticity.

Old Brains Come Uncoupled in Sleep: Slow Wave-Spindle Synchrony, Brain Atrophy, and Forgetting

The coupled interaction between slow-wave oscillations and sleep spindles during non-rapid-eye-movement (NREM) sleep has been proposed to support memory consolidation. However, little evidence in humans supports this theory. Moreover, whether such dynamic coupling is impaired as a consequence of brain aging in later life, contributing to cognitive and memory decline, is unknown. Combining electroencephalography (EEG), structural MRI, and sleep-dependent memory assessment, we addressed these questions in cognitively normal young and older adults. Directional cross-frequency coupling analyses demonstrated that the slow wave governs a precise temporal coordination of sleep spindles, the quality of which predicts overnight memory retention. Moreover, selective atrophy within the medial frontal cortex in older adults predicted a temporal dispersion of this slow wave-spindle coupling, impairing overnight memory consolidation and leading to forgetting. Prefrontal-dependent deficits in the spatiotemporal coordination of NREM sleep oscillations therefore represent one pathway explaining age-related memory decline.

The Roles of Cortical Slow Waves in Synaptic Plasticity and Memory Consolidation

Sleep plays important roles in sensory and motor memory consolidation. Sleep oscillations, reflecting neural population activity, involve the reactivation of learning-related neurons and regulate synaptic strength and, thereby affect memory consolidation. Among sleep oscillations, slow waves (0.5–4 Hz) are closely associated with memory consolidation. For example, slow-wave power is regulated in an experience-dependent manner and correlates with acquired memory. Furthermore, manipulating slow waves can enhance or impair memory consolidation. During slow wave sleep, inter-areal interactions between the cortex and hippocampus (HC) have been proposed to consolidate declarative memory; however, interactions for non-declarative (HC-independent) memory remain largely uninvestigated. We recently showed that the directional influence in a slow-wave range through a top-down cortical long-range circuit is involved in the consolidation of non-declarative memory. At the synaptic level, the average cortical synaptic strength is known to be potentiated during wakefulness and depressed during sleep. Moreover, learning causes plasticity in a subset of synapses, allocating memory to them. Sleep may help to differentiate synaptic strength between allocated and non-allocated synapses (i.e., improving the signal-to-noise ratio, which may facilitate memory consolidation). Herein, we offer perspectives on inter-areal interactions and synaptic plasticity for memory consolidation during sleep.

Hippocampal gamma-slow oscillation coupling in macaques during sedation and sleep

Behavioral and neurophysiological evidence suggests that the slow (≤1 Hz) oscillation (SO) during sleep plays a role in consolidating hippocampal (HIPP)-dependent memories. The effects of the SO on HIPP activity have been studied in rodents and cats both during natural sleep and during anesthetic administration titrated to mimic sleep-like slow rhythms. In this study, we sought to document these effects in primates. First, HIPP field potentials were recorded during ketamine-dexmedetomidine sedation and during natural sleep in three rhesus macaques. Sedation produced regionally-specific slow and gamma (∼40 Hz) oscillations with strong coupling between the SO phase and gamma amplitude. These same features were seen in slow-wave sleep (SWS), but the coupling was weaker and the coupled gamma oscillation had a higher frequency (∼70 Hz) during SWS. Second, electrical stimuli were delivered to HIPP afferents in the parahippocampal gyrus (PHG) during sedation to assess the effects of sleep-like SO on excitability. Gamma bursts after the peak of SO cycles corresponded to periods of increased gain of monosynaptic connections between the PHG and HIPP. However, the two PHG-HIPP connectivity gains during sedation were both substantially lower than when the animal was awake. We conclude that the SO is correlated with rhythmic excitation and inhibition of the PHG-HIPP network, modulating connectivity and gamma generators intrinsic to this network. Ketamine-dexmedetomidine sedation produces a similar effect, but with a decreased contribution of the PHG to HIPP activity and gamma generation.

Cortical Up states induce the selective weakening of subthreshold synaptic inputs

Slow-wave sleep is thought to be important for retuning cortical synapses, but the cellular mechanisms remain unresolved. During slow-wave activity, cortical neurons display synchronized transitions between depolarized Up states and hyperpolarized Down states. Here, using recordings from LIII pyramidal neurons from acute slices of mouse medial entorhinal cortex, we find that subthreshold inputs arriving during the Up state undergo synaptic weakening. This does not reflect a process of global synaptic downscaling, as it is dependent on presynaptic spiking, with network state encoded in the synaptically evoked spine Ca²⁺ responses. Our data indicate that the induction of synaptic weakening is under postsynaptic control, as it can be prevented by correlated postsynaptic spiking activity, and depends on postsynaptic NMDA receptors and GSK3β activity. This provides a mechanism by which slow-wave activity might bias synapses towards weakening, while preserving the synaptic connections within active neuronal assemblies.

Slow oscillations between cortical Up and Down states are a defining feature of deep sleep, but their function is not well understood. Here the authors study Up/Down states in acute slices of entorhinal cortex, and find that Up states promote the weakening of subthreshold synaptic inputs, while suprathreshold inputs are preserved or strengthened.

Physiological Ripples Associated with Sleep Spindles Differ in Waveform Morphology from Epileptic Ripples

High frequency oscillations (HFOs, 80–500[Formula: see text]Hz) serve as novel electroencephalography (EEG) markers of epileptic tissue. The differentiation of physiological and epileptic HFO is an important challenge and is complicated by the fact that both types are generated in mesiotemporal structures. This study aimed to identify oscillation features that serve to distinguish physiological ripples associated with sleep spindles and epileptic ripples. We studied 19 patients with chronic intracranial EEG(iEEG) with mesiotemporal implantation and simultaneous scalp EEG. Sleep spindles, ripples and spikes were visually marked during nonrapid eye movement sleep stage 2. Ripples co-occurring with spikes and in seizure onset zone (SOZ) channels but outside of spindles were considered epileptic. The SOZ is defined by the origin of clinical seizures in iEEG. Ripples co-occurring with spindles were considered as models for physiological ripples. A correlation analysis showed a significant ripple amplitude peak — spindle trough — coupling, thus proving their physiological linkage. Epileptic ripples showed significantly higher values in all amplitude features than spindle ripples. All amplitude features and peaks per sample length showed a predictive value for the classification between model physiological ripples and epileptic ripples but indicate that the specificity is not sufficient for a reliable discrimination of single ripple events. The presented results suggest that a secure identification of epileptic ripples may be available to help identify the epileptic focus in the future.

Gamma phase-synchrony in autobiographical memory: Evidence from magnetoencephalography and severely deficient autobiographical memory

The subjective sense of recollecting events from one's past is an essential feature of episodic memory, but the neural mechanisms supporting this capacity are poorly understood. We examined the role of large-scale patterns of neural synchrony using whole-head MEG recordings in healthy adults and S.M., who has severely deficient autobiographical memory (SDAM; Palombo et al., 2015), a syndrome in which autobiographical recollection is absent but other functions (including other mnemonic functions), are normal. MEG was conducted while participants listened to prospectively collected recordings documenting unique personal episodes (PE) that normally evoke rich recollection, as well as a condition including general semantic information that is non-specific in place or time (GS; Levine et al., 2004). We predicted that PE (and not GS) would be associated with changes in patterns of large-scale neural synchrony in comparison subjects. We found large-scale neural synchrony, specifically in the gamma frequency ranges (i.e., 27-45Hz), specific to PE and not GS. These synchrony differences between PE and GS were not apparent in S.M. Our findings provide empirical evidence for the supporting role of large-scale gamma neural synchrony underlying autobiographical recollection.

Coordinated Interaction between Hippocampal Sharp-Wave Ripples and Anterior Cingulate Unit Activity

Hippocampal-cortical interaction during sleep promotes transformation of memory for long-term storage in the cortex. In particular, hippocampal sharp-wave ripple-associated neural activation is important for this transformation during slow-wave sleep. The anterior cingulate cortex (ACC) has been shown to be crucial for expression and likely storage of long-term memory. However, little is known about how ACC activity is influenced by hippocampal ripple activity during sleep. We report here about coordinated interactions between hippocampal ripple activity and ACC neural firings. By recording from the ACC and hippocampal CA1 simultaneously in mice, we found that almost all ACC neurons showed increased activity before hippocampal ripple activity; moreover, a subpopulation (17%) displayed a further activation immediately after ripple activity. This postripple activation of ACC neurons correlated positively with ripple amplitude, and the same neurons were excited upon electrical stimulation of the CA1. Interestingly, the preripple activation of ACC neurons was present during the sleep state, but not during the awake state. These results suggest intimate interactions between hippocampal sharp-wave ripples and ACC neurons in a state-dependent manner. Importantly, sharp-wave ripples and associated activation appear to regulate activity of a small population of ACC neurons, a process that may play a critical role in memory consolidation.

SIGNIFICANCE STATEMENT

The hippocampus communicates with the cortex for memory transformation. Memories of previous experiences become less dependent on the hippocampus and increasingly dependent on cortical areas, such as the anterior cingulate cortex (ACC). However, little evidence is available to directly support this hippocampus-to-cortex information transduction hypothesis of memory consolidation. Here we show that a subpopulation of ACC neurons becomes active just after hippocampal ripple activity, and that electrical stimulation of the hippocampus excites the same ACC neurons. In addition, the majority of ACC neurons are activated just before ripple activity during the sleep state, but not during the awake state. These results provide evidence supporting the hypothesis of hippocampus-to-cortex information flow for memory consolidation as well as reciprocal interaction between the hippocampus and the cortex.

Endogenously Released Neuropeptide Y Suppresses Hippocampal Short-Term Facilitation and Is Impaired by Stress-Induced Anxiety

Neuropeptide Y (NPY) has robust anxiolytic properties and is reduced in patients with anxiety disorders. However, the mechanisms by which NPY modulates circuit function to reduce anxiety behavior are not known. Anxiolytic effects of NPY are mediated in the CA1 region of hippocampus, and NPY injection into hippocampus alleviates anxiety symptoms in the predator scent stress model of stress-induced anxiety. The mechanisms that regulate NPY release, and its effects on CA1 synaptic function, are not fully understood. Here we show in acute hippocampal slices from mice that endogenous NPY, released in response to optogenetic stimulation or synaptically evoked spiking of NPY+ cells, suppresses both of the feedforward pathways to CA1. Stimulation of temporoammonic synapses with a physiologically derived spike train causes NPY release that reduces short-term facilitation, whereas the release of NPY that modulates Schaffer collateral synapses requires integration of both the Schaffer collateral and temporoammonic pathways. Pathway specificity of NPY release is conferred by three functionally distinct NPY+ cell types, with differences in intrinsic excitability and short-term plasticity of their inputs. Predator scent stress abolishes the release of endogenous NPY onto temporoammonic synapses, a stress-sensitive pathway, thereby causing enhanced short-term facilitation. Our results demonstrate how stress alters CA1 circuit function through the impairment of endogenous NPY release, potentially contributing to heightened anxiety.

SIGNIFICANCE STATEMENT

Neuropeptide Y (NPY) has robust anxiolytic properties, and its levels are reduced in patients with post-traumatic stress disorder. The effects of endogenously released NPY during physiologically relevant stimulation, and the impact of stress-induced reductions in NPY on circuit function, are unknown. By demonstrating that NPY release modulates hippocampal synaptic plasticity and is impaired by predator scent stress, our results provide a novel mechanism by which stress-induced anxiety alters circuit function. These studies fill an important gap in knowledge between the molecular and behavioral effects of NPY. This article also advances the understanding of NPY+ cells and the factors that regulate their spiking, which could pave the way for new therapeutic targets to increase endogenous NPY release in patients in a spatially and temporally appropriate manner.

The beneficial role of memory reactivation for language learning during sleep: A review

Sleep is essential for diverse aspects of language learning. According to a prominent concept these beneficial effects of sleep rely on spontaneous reactivation processes. A series of recent studies demonstrated that inducing such reactivation processes by re-exposure to memory cues during sleep enhances foreign vocabulary learning. Building upon these findings, the present article reviews recent models and empirical findings concerning the beneficial effects of sleep on language learning. Consequently, the memory function of sleep, its neural underpinnings and the role of the sleeping brain in language learning will be summarized. Finally, we will propose a working model concerning the oscillatory requirements for successful reactivation processes and future research questions to advance our understanding of the role of sleep on language learning and memory processes in general.

Physiological Properties and Behavioral Correlates of Hippocampal Granule Cells and Mossy Cells

The hippocampal dentate gyrus is often viewed as a segregator of upstream information. Physiological support for such function has been hampered by a lack of well-defined characteristics that can identify granule cells and mossy cells. We developed an electrophysiology-based classification of dentate granule cells and mossy cells in mice that we validated by optogenetic tagging of mossy cells. Granule cells exhibited sparse firing, had a single place field, and showed only modest changes when the mouse was tested in different mazes in the same room. In contrast, mossy cells were more active, had multiple place fields and showed stronger remapping of place fields under the same conditions. Although the granule cell-mossy cell synapse was strong and facilitating, mossy cells rarely "inherited" place fields from single granule cells. Our findings suggest that the granule cells and mossy cells could be modulated separately and their joint action may be critical for pattern separation.

Spatial Representations of Granule Cells and Mossy Cells of the Dentate Gyrus

Granule cells in the dentate gyrus of the hippocampus are thought to be essential to memory function by decorrelating overlapping input patterns (pattern separation). A second excitatory cell type in the dentate gyrus, the mossy cell, forms an intricate circuit with granule cells, CA3c pyramidal cells, and local interneurons, but the influence of mossy cells on dentate function is often overlooked. Multiple tetrode recordings, supported by juxtacellular recording techniques, showed that granule cells fired very sparsely, whereas mossy cells in the hilus fired promiscuously in multiple locations and in multiple environments. The activity patterns of these cell types thus represent different environments through distinct computational mechanisms: sparse coding in granule cells and changes in firing field locations in mossy cells.

Common oscillatory mechanisms across multiple memory systems

The cortex, hippocampus, and striatum support dissociable forms of memory. While each of these regions contains specialized circuitry supporting their respective functions, all structure their activities across time with delta, theta, and gamma rhythms. We review how these oscillations are generated and how they coordinate distinct memory systems during encoding, consolidation, and retrieval. First, gamma oscillations occur in all regions and coordinate local spiking, compressing it into short population bursts. Second, gamma oscillations are modulated by delta and theta oscillations. Third, oscillatory dynamics in these memory systems can operate in either a 'slow' or 'fast' mode. The slow mode happens during slow-wave sleep (SWS) and is characterized by large irregular activity in the hippocampus and delta oscillations in cortical and striatal circuits. The fast mode occurs during active waking and REM and is characterized by theta oscillations in the hippocampus and its targets, along with gamma oscillations in the rest of cortex. In waking, the fast mode is associated with the efficacious encoding and retrieval of declarative and procedural memories. Theta and gamma oscillations have the similar relationships with encoding and retrieval across multiple forms of memory and brain regions, despite regional differences in microcircuitry and information content. Differences in the oscillatory coordination of memory systems during sleep might explain why the consolidation of some forms of memory is sensitive to SWS, while others depend on REM. In particular, theta oscillations appear to support the consolidation of certain types of procedural memories during REM, while delta oscillations during SWS seem to promote declarative and procedural memories.

Interaction of nucleus reuniens and entorhinal cortex projections in hippocampal field CA1 of the rat

The nucleus reuniens (RE) and entorhinal cortex (EC) provide monosynaptic excitatory inputs to the apical dendrites of pyramidal cells and to interneurons with dendrites in stratum lacunosum moleculare (LM) of hippocampal field CA1. However, whether the RE and EC inputs interact at the cellular level is unknown. In this electrophysiological in vivo study, low-frequency stimulation was used to selectively activate each projection at its origin; field excitatory postsynaptic potentials (fEPSPs) were recorded in CA1. We applied (1) paired pulses to RE or EC, (2) combined paired pulses to RE and EC, and (3) simultaneously paired pulses to RE/EC. The main findings are that: (a) stimulation of either RE- or EC-evoked subthreshold fEPSPs, displaying paired pulse facilitation (PPF), (b) subthreshold fEPSPs evoked by combined stimulation did not display heterosynaptic PPF, and (c) simultaneous stimulation of RE/EC resulted in enhanced subthreshold fEPSPs in proximal LM displaying a nonlinear interaction. CSD analyses of RE/EC-evoked depth profiles revealed a nonlinear enlargement of the 'LM sink-radiatum source' configuration and the appearance of an additional small sink-source pair close to stratum pyramidale, likely reflecting (peri)somatic inhibition. The nonlinear interaction between both inputs indicates that RE and EC axons form synapses, at least partly, onto the same dendritic compartments of CA1 pyramidal cells. We propose that low-frequency activation of the RE-CA1 input facilitates the entorhinal-hippocampal dialogue, and may synchronize the neocortical-hippocampal slow oscillation which is relevant for hippocampal-dependent memory consolidation.

Dorsal vs. ventral differences in fast Up-state-associated oscillations in the medial prefrontal cortex of the urethane-anesthetized rat

We demonstrate, in the urethane-anesthetized rat, that within the medial prefrontal cortex (mPFC) there are clear subregional differences in the fast network oscillations associated with the slow oscillation Up-state. These differences, particularly between the dorsal and ventral subregions of the mPFC, may reflect the different functions and connectivity of these subregions.

Cortical slow oscillations (0.1–1 Hz), which may play a role in memory consolidation, are a hallmark of non-rapid eye movement (NREM) sleep and also occur under anesthesia. During slow oscillations the neuronal network generates faster oscillations on the active Up-states and these nested oscillations are particularly prominent in the PFC. In rodents the medial prefrontal cortex (mPFC) consists of several subregions: anterior cingulate cortex (ACC), prelimbic (PrL), infralimbic (IL), and dorsal peduncular cortices (DP). Although each region has a distinct anatomy and function, it is not known whether slow or fast network oscillations differ between subregions in vivo. We have simultaneously recorded slow and fast network oscillations in all four subregions of the rodent mPFC under urethane anesthesia. Slow oscillations were synchronous between the mPFC subregions, and across the hemispheres, with no consistent amplitude difference between subregions. Delta (2–4 Hz) activity showed only small differences between subregions. However, oscillations in the spindle (6–15 Hz)-, beta (20–30 Hz), gamma (30–80 Hz)-, and high-gamma (80–150 Hz)-frequency bands were consistently larger in the dorsal regions (ACC and PrL) compared with ventral regions (IL and DP). In dorsal regions the peak power of spindle, beta, and gamma activity occurred early after onset of the Up-state. In the ventral regions, especially the DP, the oscillatory power in the spindle-, beta-, and gamma-frequency ranges peaked later in the Up-state. These results suggest variations in fast network oscillations within the mPFC that may reflect the different functions and connectivity of these subregions.

NEW & NOTEWORTHY We demonstrate, in the urethane-anesthetized rat, that within the medial prefrontal cortex (mPFC) there are clear subregional differences in the fast network oscillations associated with the slow oscillation Up-state. These differences, particularly between the dorsal and ventral subregions of the mPFC, may reflect the different functions and connectivity of these subregions.

A cortical-hippocampal-cortical loop of information processing during memory consolidation

Hippocampal replay during sharp-wave ripple events (SWRs) is thought to drive memory consolidation in hippocampal and cortical circuits. Changes in neocortical activity can precede SWR events, but whether and how these changes influence the content of replay remains unknown. Here we show that during sleep there is a rapid cortical-hippocampal-cortical loop of information flow around the times of SWRs. We recorded neural activity in auditory cortex (AC) and hippocampus of rats as they learned a sound-guided task and during sleep. We found that patterned activation in AC precedes and predicts the subsequent content of hippocampal activity during SWRs, while hippocampal patterns during SWRs predict subsequent AC activity. Delivering sounds during sleep biased AC activity patterns, and sound-biased AC patterns predicted subsequent hippocampal activity. These findings suggest that activation of specific cortical representations during sleep influences the identity of the memories that are consolidated into long-term stores.

The Effects of Realistic Synaptic Distribution and 3D Geometry on Signal Integration and Extracellular Field Generation of Hippocampal Pyramidal Cells and Inhibitory Neurons

In vivo and in vitro multichannel field and somatic intracellular recordings are frequently used to study mechanisms of network pattern generation. When interpreting these data, neurons are often implicitly considered as electrotonically compact cylinders with a homogeneous distribution of excitatory and inhibitory inputs. However, the actual distributions of dendritic length, diameter, and the densities of excitatory and inhibitory input are non-uniform and cell type-specific. We first review quantitative data on the dendritic structure and synaptic input and output distribution of pyramidal cells (PCs) and interneurons in the hippocampal CA1 area. Second, using multicompartmental passive models of four different types of neurons, we quantitatively explore the effect of differences in dendritic structure and synaptic distribution on the errors and biases of voltage clamp measurements of inhibitory and excitatory postsynaptic currents. Finally, using the 3-dimensional distribution of dendrites and synaptic inputs we calculate how different inhibitory and excitatory inputs contribute to the generation of local field potential in the hippocampus. We analyze these effects at different realistic background activity levels as synaptic bombardment influences neuronal conductance and thus the propagation of signals in the dendritic tree. We conclude that, since dendrites are electrotonically long and entangled in 3D, somatic intracellular and field potential recordings miss the majority of dendritic events in some cell types, and thus overemphasize the importance of perisomatic inhibitory inputs and belittle the importance of complex dendritic processing. Modeling results also suggest that PCs and inhibitory neurons probably use different input integration strategies. In PCs, second- and higher-order thin dendrites are relatively well-isolated from each other, which may support branch-specific local processing as suggested by studies of active dendritic integration. In the electrotonically compact parvalbumin- and cholecystokinincontaining interneurons, synaptic events are visible in the whole dendritic arbor, and thus the entire dendritic tree may form a single integrative element. Calretinin-containing interneurons were found to be electrotonically extended, which suggests the possibility of complex dendritic processing in this cell type. Our results also highlight the need for the integration of methods that allow the measurement of dendritic processes into studies of synaptic interactions and dynamics in neural networks.

Human cortical-hippocampal dialogue in wake and slow-wave sleep

Declarative memory consolidation is hypothesized to require a two-stage, reciprocal cortical-hippocampal dialogue. According to this model, higher frequency signals convey information from the cortex to hippocampus during wakefulness, but in the reverse direction during slow-wave sleep (SWS). Conversely, lower-frequency activity propagates from the information "receiver" to the "sender" to coordinate the timing of information transfer. Reversal of sender/receiver roles across wake and SWS implies that higher- and lower-frequency signaling should reverse direction between the cortex and hippocampus. However, direct evidence of such a reversal has been lacking in humans. Here, we use human resting-state fMRI and electrocorticography to demonstrate that δ-band activity and infraslow activity propagate in opposite directions between the hippocampus and cerebral cortex. Moreover, both δ activity and infraslow activity reverse propagation directions between the hippocampus and cerebral cortex across wake and SWS. These findings provide direct evidence for state-dependent reversals in human cortical-hippocampal communication.

Temporal coordination of olfactory cortex sharp-wave activity with up- and downstates in the orbitofrontal cortex during slow-wave sleep

During slow-wave sleep, interareal communications via coordinated, slow oscillatory activities occur in the large-scale networks of the mammalian neocortex. Because olfactory cortex (OC) areas, which belong to paleocortex, show characteristic sharp-wave (SPW) activity during slow-wave sleep, we examined whether OC SPWs in freely behaving rats occur in temporal coordination with up- and downstates of the orbitofrontal cortex (OFC) slow oscillation. Simultaneous recordings of local field potentials and spike activities in the OC and OFC showed that during the downstate in the OFC, the OC also exhibited downstate with greatly reduced neuronal activity and suppression of SPW generation. OC SPWs occurred during two distinct phases of the upstate of the OFC: early-phase SPWs occurred at the start of upstate shortly after the down-to-up transition in the OFC, whereas late-phase SPWs were generated at the end of upstate shortly before the up-to-down transition. Such temporal coordination between neocortical up- and downstates and olfactory system SPWs was observed between the prefrontal cortex areas (OFC and medial prefrontal cortex) and the OC areas (anterior piriform cortex and posterior piriform cortex). These results suggest that during slow-wave sleep, OC and OFC areas communicate preferentially in specific time windows shortly after the down-to-up transition and shortly before the up-to-down transition.

NEW & NOTEWORTHY

Simultaneous recordings of local field potentials and spike activities in the anterior piriform cortex (APC) and orbitofrontal cortex (OFC) during slow-wave sleep showed that APC sharp waves tended to occur during two distinct phases of OFC upstate: early phase, shortly after the down-to-up transition, and late phase, shortly before the up-to-down transition, suggesting that during slow-wave sleep, olfactory cortex and OFC areas communicate preferentially in the specific time windows.

Synaptic Mechanisms of Memory Consolidation during Sleep Slow Oscillations

Sleep is critical for regulation of synaptic efficacy, memories, and learning. However, the underlying mechanisms of how sleep rhythms contribute to consolidating memories acquired during wakefulness remain unclear. Here we studied the role of slow oscillations, 0.2-1 Hz rhythmic transitions between Up and Down states during stage 3/4 sleep, on dynamics of synaptic connectivity in the thalamocortical network model implementing spike-timing-dependent synaptic plasticity. We found that the spatiotemporal pattern of Up-state propagation determines the changes of synaptic strengths between neurons. Furthermore, an external input, mimicking hippocampal ripples, delivered to the cortical network results in input-specific changes of synaptic weights, which persisted after stimulation was removed. These synaptic changes promoted replay of specific firing sequences of the cortical neurons. Our study proposes a neuronal mechanism on how an interaction between hippocampal input, such as mediated by sharp wave-ripple events, cortical slow oscillations, and synaptic plasticity, may lead to consolidation of memories through preferential replay of cortical cell spike sequences during slow-wave sleep.

SIGNIFICANCE STATEMENT

Sleep is critical for memory and learning. Replay during sleep of temporally ordered spike sequences related to a recent experience was proposed to be a neuronal substrate of memory consolidation. However, specific mechanisms of replay or how spike sequence replay leads to synaptic changes that underlie memory consolidation are still poorly understood. Here we used a detailed computational model of the thalamocortical system to report that interaction between slow cortical oscillations and synaptic plasticity during deep sleep can underlie mapping hippocampal memory traces to persistent cortical representation. This study provided, for the first time, a mechanistic explanation of how slow-wave sleep may promote consolidation of recent memory events.

Midline thalamic neurons are differentially engaged during hippocampus network oscillations

The midline thalamus is reciprocally connected with the medial temporal lobe, where neural circuitry essential for spatial navigation and memory formation resides. Yet, little information is available on the dynamic relationship between activity patterns in the midline thalamus and medial temporal lobe. Here, we report on the functional heterogeneity of anatomically-identified thalamic neurons and the differential modulation of their activity with respect to dorsal hippocampal rhythms in the anesthetized mouse. Midline thalamic neurons expressing the calcium-binding protein calretinin, irrespective of their selective co-expression of calbindin, discharged at overall low levels, did not increase their activity during hippocampal theta oscillations, and their firing rates were inhibited during hippocampal sharp wave-ripples. Conversely, thalamic neurons lacking calretinin discharged at higher rates, increased their activity during hippocampal theta waves, but remained unaffected during sharp wave-ripples. Our results indicate that the midline thalamic system comprises at least two different classes of thalamic projection neuron, which can be partly defined by their differential engagement by hippocampal pathways during specific network oscillations that accompany distinct behavioral contexts. Thus, different midline thalamic neuronal populations might be selectively recruited to support distinct stages of memory processing, consistent with the thalamus being pivotal in the dialogue of cortical circuits.

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.