Hippocampal place cells are not controlled by visual input during the small irregular activity state in the rat

Three brain states in the hippocampus and cortex

Contemporary brain research seeks to understand how cognition is reducible to neural activity. Crucially, much of this effort is guided by a scientific paradigm that views neural activity as essentially driven by external stimuli. In contrast, recent perspectives argue that this paradigm is by itself inadequate and that understanding patterns of activity intrinsic to the brain is needed to explain cognition. Yet, despite this critique, the stimulus-driven paradigm still dominates-possibly because a convincing alternative has not been clear. Here, we review a series of findings suggesting such an alternative. These findings indicate that neural activity in the hippocampus occurs in one of three brain states that have radically different anatomical, physiological, representational, and behavioral correlates, together implying different functional roles in cognition. This three-state framework also indicates that neural representations in the hippocampus follow a surprising pattern of organization at the timescale of ∼1 s or longer. Lastly, beyond the hippocampus, recent breakthroughs indicate three parallel states in the cortex, suggesting shared principles and brain-wide organization of intrinsic neural activity.

Hippocampal and cortical communication around micro-arousals in slow-wave sleep

Sleep plays a crucial role in the regulation of body homeostasis and rhythmicity in mammals. Recently, a specific component of the sleep structure has been proposed as part of its homeostatic mechanism, named micro-arousal. Here, we studied the unique progression of the dynamic behavior of cortical and hippocampal local field potentials (LFPs) during slow-wave sleep-related to motor-bursts (micro-arousals) in mice. Our main results comprised: (i) an abrupt drop in hippocampal LFP amplitude preceding micro-arousals which persisted until the end of motor-bursts (we defined as t interval, around 4s) and a similar, but delayed amplitude reduction in cortical (S1/M1) LFP activity occurring at micro-arousal onset; (ii) two abrupt frequency jumps in hippocampal LFP activity: from Theta (6-12 Hz) to Delta (2-4 Hz), also t seconds before the micro-arousal onset, and followed by another frequency jump from Delta to Theta range (5-7 Hz), now occurring at micro-arousal onset; (iii) a pattern of cortico-hippocampal frequency communication precedes micro-arousals: the analysis between hippocampal and cortical LFP fluctuations reveal high coherence during τ interval in a broader frequency band (2-12 Hz), while at a lower frequency band (0.5-2 Hz) the coherence reaches its maximum after the onset of micro-arousals. In conclusion, these novel findings indicate that oscillatory dynamics pattern of cortical and hippocampal LFPs preceding micro-arousals could be part of the regulatory processes in sleep architecture.

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.

Cognitive and Physiologic Impacts of the Infraslow Oscillation

Brain states are traditionally recognized via sleep-wake cycles, but modern neuroscience is beginning to identify many sub-states within these larger arousal types. Multiple lines of converging evidence now point to the infraslow oscillation (ISO) as a mediator of brain sub-states, with impacts ranging from the creation of resting state networks (RSNs) in awake subjects to interruptions in neural activity during sleep. This review will explore first the basic characteristics of the ISO in human subjects before reviewing findings in sleep and in animals. Networks of consistently correlated brain regions known as RSNs seen in human functional neuroimaging studies oscillate together at infraslow frequencies. The infraslow rhythm subdivides nonREM in a manner that may correlate with plasticity. The mechanism of this oscillation may be found in the thalamus and may ultimately come from glial cells. Finally, I review the functional impacts of ISOs on brain phenomena ranging from higher frequency oscillations, to brain networks, to information representation and cognitive performance. ISOs represent a relatively understudied phenomenon with wide effects on the brain and behavior.

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.

Brain State Dependence of Hippocampal Subthreshold Activity in Awake Mice

Monitoring the membrane potential of individual neurons has uncovered how single-cell properties contribute to network processing across different brain states in neocortex. In contrast, the subthreshold modulation of hippocampal neurons by brain state has not been systematically characterized. To address this, we combined whole-cell recordings from dentate granule cells and CA1 pyramidal neurons with multisite extracellular recordings and behavioral measurements in awake mice. We show that the average membrane potential, amplitude of subthreshold fluctuations, and distance to spike threshold are all modulated by brain state. Furthermore, even within individual states, rapid variations in arousal are reflected in membrane potential fluctuations. These factors produce depolarizing ramps in the membrane potential of hippocampal neurons that precede ripples and mirror transitions to a network regime conducive for ripple generation. These results suggest that there are coordinated shifts in the subthreshold dynamics of individual neurons that underlie the transitions between distinct modes of hippocampal processing.

Hippocampal Remapping after Partial Inactivation of the Medial Entorhinal Cortex

Hippocampal place cells undergo remapping when the environment is changed. The mechanism of hippocampal remapping remains elusive but spatially modulated cells in the medial entorhinal cortex (MEC) have been identified as a possible contributor. Using pharmacogenetic and optogenetic approaches, we tested the role of MEC cells by examining in mice whether partial inactivation in MEC shifts hippocampal activity to a different subset of place cells with different receptive fields. The pharmacologically selective designer Gi-protein-coupled muscarinic receptor hM4D or the light-responsive microbial proton pump archaerhodopsin (ArchT) was expressed in MEC, and place cells were recorded after application of the inert ligand clozapine-N-oxide (CNO) or light at appropriate wavelengths. CNO or light caused partial inactivation of the MEC. The inactivation was followed by substantial remapping in the hippocampus, without disruption of the spatial firing properties of individual neurons. The results point to MEC input as an element of the mechanism for remapping in place cells.

Place cell rate remapping by CA3 recurrent collaterals

Episodic-like memory is thought to be supported by attractor dynamics in the hippocampus. A possible neural substrate for this memory mechanism is rate remapping, in which the spatial map of place cells encodes contextual information through firing rate variability. To test whether memories are stored as multimodal attractors in populations of place cells, recent experiments morphed one familiar context into another while observing the responses of CA3 cell ensembles. Average population activity in CA3 was reported to transition gradually rather than abruptly from one familiar context to the next, suggesting a lack of attractive forces associated with the two stored representations. On the other hand, individual CA3 cells showed a mix of gradual and abrupt transitions at different points along the morph sequence, and some displayed hysteresis which is a signature of attractor dynamics. To understand whether these seemingly conflicting results are commensurate with attractor network theory, we developed a neural network model of the CA3 with attractors for both position and discrete contexts. We found that for memories stored in overlapping neural ensembles within a single spatial map, position-dependent context attractors made transitions at different points along the morph sequence. Smooth transition curves arose from averaging across the population, while a heterogeneous set of responses was observed on the single unit level. In contrast, orthogonal memories led to abrupt and coherent transitions on both population and single unit levels as experimentally observed when remapping between two independent spatial maps. Strong recurrent feedback entailed a hysteretic effect on the network which diminished with the amount of overlap in the stored memories. These results suggest that context-dependent memory can be supported by overlapping local attractors within a spatial map of CA3 place cells. Similar mechanisms for context-dependent memory may also be found in other regions of the cerebral cortex.

The activity of ‘place cells’ in hippocampal area CA3 systematically changes as a function of the animal's position in an arena as well as contextual variables like the color or shape of enclosing walls. Large changes to the local environment, e.g. moving the animal to a different room, can induce a complete reorganization of place-cell firing locations. Such ‘global remapping’ reveals that memory for different environments is encoded as separate spatial maps. Smaller changes to features within an environment can induce a modulation of place cell firing rates without affecting their firing locations. This kind of ‘rate remapping’ is still poorly understood. In this paper we describe a computational model in which discrete memories for contextual features were stored locally within a spatial map of place cells. This network structure supports retrieval of both positional and contextual information from an arbitrary cue, as required by an episodic memory structure. The activity of the network qualitatively matches empirical data from rate remapping experiments, both on the population level and the level of single place cells. The results support the idea that CA3 rate remapping reflects content-addressable memories stored as multimodal attractor states in the hippocampus.

An inside look at hippocampal silent cells

Hippocampal pyramidal cells can be divided into place cells, which fire action potentials when an animal is in specific locations, and silent cells, which are not spatially selective. In this issue of Neuron, Epsztein et al. find intracellular differences between place and silent cells by using whole-cell recordings in freely moving rats.

Understanding memory through hippocampal remapping

Memory interference is a common cause of forgetting. Interference is a byproduct of the need to balance the formation of well-differentiated representations against the ability to retrieve memories from cues that are not identical to the original experience. How the brain accomplishes this has remained elusive. Here we review how insights can be gained from studies of an apparently unrelated phenomenon in the rodent brain--remapping in hippocampal place cells. Remapping refers to the formation of distinct representations in populations of place cells after minor changes in inputs to the hippocampus. Remapping might reflect processes involved generally in decorrelation of overlapping signals. These processes might be crucial for storing large numbers of similar experiences with only minimal interference.

Median Raphe Stimulation Disrupts Hippocampal Theta Via Rapid Inhibition and State-Dependent Phase Reset of Theta-Related Neural Circuitry

Evidence has accumulated suggesting that the median raphe (MR) mediates hippocampal theta desynchronization. However, few studies have evaluated theta-related neural circuitry during MR manipulation. In urethane-anesthetized rats, we investigated the effects of MR stimulation on hippocampal field and cell activity using high-frequency (100 Hz), theta burst (TBS), and slow-frequency electrical stimulation (0.5 Hz). We demonstrated that high-frequency stimulation of the MR did not elicit deactivated patterns in the forebrain, but rather elicited low-voltage activity in the neocortex and small-amplitude irregular activity (SIA) in the hippocampus. Both hippocampal phasic theta-on and -off cells were inhibited by high-frequency MR stimulation, although MR stimulation failed to affect cells that had neither state or phase relationships with theta field activity. TBS of the MR-induced theta field activity phase locked to the stimulation. Slow-frequency stimulation elicited a state-dependent reset of theta phase through a short-latency inhibition (5 ms) in phasic theta-on cells. Subpopulations of phasic theta-on cells responded in either oscillatory or nonoscillatory patterns to MR pulses, depending on their intraburst interval. off cells exhibited a state-dependent modulation of cell firing occurring preferentially during nontheta. The magnitude of MR-induced reset varied as a function of the phase of the theta oscillation when the pulse was administered. Therefore high-frequency stimulation of the MR appears to disrupt hippocampal theta through a state-dependent, short-latency inhibition of rhythmic cell populations in the hippocampus functioning to switch theta oscillations to an activated SIA field state.

Spontaneous rhythmic field potentials of isolated mouse hippocampal-subicular-entorhinal cortices in vitro

The rodent hippocampal circuit is capable of exhibiting in vitro spontaneous rhythmic field potentials (SRFPs) of 1-4 Hz that originate from the CA3 area and spread to the CA1 area. These SRFPs are largely correlated with GABA-A IPSPs in pyramidal neurons and repetitive discharges in inhibitory interneurons. As such, their generation is thought to result from cooperative network activities involving both pyramidal neurons and GABAergic interneurons. Considering that the hippocampus, subiculum and entorhinal cortex function as an integrated system crucial for memory and cognition, it is of interest to know whether similar SRFPs occur in hippocampal output structures (that is, the subiculum and entorhinal cortex), and if so, to understand the cellular basis of these subicular and entorhinal SRFPs as well as their temporal relation to hippocampal SRFPs. We explored these issues in the present study using thick hippocampal-subicular-entorhinal cortical slices prepared from adult mice. SRFPs were found to spread from the CA1 area to the subicular and entorhinal cortical areas. Subicular and entorhinal cortical SRFPs were correlated with mixed IPSPs/EPSPs in local pyramidal neurons, and their generation was dependent upon the activities of GABA-A and AMPA glutamate receptors. In addition, the isolated subicular circuit could elicit SRFPs independent of CA3 inputs. We hypothesize that the SRFPs represent a basal oscillatory activity of the hippocampal-subicular-entorhinal cortices and that the subiculum functions as both a relay and an amplifier, spreading the SRFPs from the hippocampus to the entorhinal cortex.

Tracking Route Progression in the Posterior Parietal Cortex

Quick and efficient traversal of learned routes is critical to the survival of many animals. Routes can be defined by both the ordering of navigational epochs, such as continued forward motion or execution of a turn, and the distances separating them. The neural substrates conferring the ability to fluidly traverse complex routes are not well understood, but likely entail interactions between frontal, parietal, and rhinal cortices and the hippocampus. This paper demonstrates that posterior parietal cortical neurons map both individual and multiple navigational epochs with respect to their order in a route. In direct contrast to spatial firing patterns of hippocampal neurons, parietal neurons discharged in a place- and direction-independent fashion. Parietal route maps were scalable and versatile in that they were independent of the size and spatial configuration of navigational epochs. The results provide a framework in which to consider parietal function in spatial cognition.

Organizing principles of real-time memory encoding: neural clique assemblies and universal neural codes

Recent identification of network-level coding units, termed neural cliques, in the hippocampus has enabled real-time patterns of memory traces to be mathematically described, directly visualized, and dynamically deciphered. These memory coding units are functionally organized in a categorical and hierarchical manner, suggesting that internal representations of external events in the brain is achieved not by recording exact details of those events, but rather by recreating its own selective pictures based on cognitive importance. This neural-clique-based hierarchical-extraction and parallel-binding process enables the brain to acquire not only large storage capacity but also abstraction and generalization capability. In addition, activation patterns of the neural clique assemblies can be converted to strings of binary codes that would permit universal categorizations of internal brain representations across individuals and species.

Place-Selective Firing of CA1 Pyramidal Cells during Sharp Wave/Ripple Network Patterns in Exploratory Behavior

We observed sharp wave/ripples (SWR) during exploration within brief (<2.4 s) interruptions of or during theta oscillations. CA1 network responses of SWRs occurring during exploration (eSWR) and SWRs detected in waking immobility or sleep were similar. However, neuronal activity during eSWR was location dependent, and eSWR-related firing was stronger inside the place field than outside. The eSPW-related firing increase was stronger than the baseline increase inside compared to outside, suggesting a "supralinear" summation of eSWR and place-selective inputs. Pairs of cells with similar place fields and/or correlated firing during exploration showed stronger coactivation during eSWRs and subsequent sleep-SWRs. Sequential activation of place cells was not required for the reactivation of waking co-firing patterns; cell pairs with symmetrical cross-correlations still showed reactivated waking co-firing patterns during sleep-SWRs. We suggest that place-selective firing during eSWRs facilitates initial associations between cells with similar place fields that enable place-related ensemble patterns to recur during subsequent sleep-SWRs.

Place cells, spatial maps and the population code for memory

The study of population dynamics in hippocampal place cells has emerged as one of the most powerful tools for understanding the encoding, storage and retrieval of declarative memory. Recent work has laid out the contours of an attractor-based hippocampal population code for memory in recurrent circuits of the hippocampus. The code is based on inputs from a topographically organized, path-integration-dependent spatial map that lies upstream in the medial entorhinal cortex. The recurrent networks of the hippocampal formation enable these spatial inputs to be synthesized with nonspatial event-related information.

Progressive Transformation of Hippocampal Neuronal Representations in “Morphed” Environments

Hippocampal neural codes for different, familiar environments are thought to reflect distinct attractor states, possibly implemented in the recurrent CA3 network. A defining property of an attractor network is its ability to undergo sharp and coherent transitions between pre-established (learned) representations when the inputs to the network are changed. To determine whether hippocampal neuronal ensembles exhibit such discontinuities, we recorded in CA3 and CA1 when a familiar square recording enclosure was morphed in quantifiable steps into a familiar circular enclosure while leaving other inputs constant. We observed a gradual noncoherent progression from the initial to the final network state. In CA3, the transformation was accompanied by significant hysteresis, resulting in more similar end states than when only square and circle were presented. These observations suggest that hippocampal cell assemblies are capable of incremental plastic deformation, with incongruous information being incorporated into pre-existing representations.

A simple neural network model of the hippocampus suggesting its pathfinding role in episodic memory retrieval

The goal of this work is to extend the theoretical understanding of the relationship between hippocampal spatial and memory functions to the level of neurophysiological mechanisms underlying spatial navigation and episodic memory retrieval. The proposed unifying theory describes both phenomena within a unique framework, as based on one and the same pathfinding function of the hippocampus. We propose a mechanism of reconstruction of the context of experience involving a search for a nearly shortest path in the space of remembered contexts. To analyze this concept in detail, we define a simple connectionist model consistent with available rodent and human neurophysiological data. Numerical study of the model begins with the spatial domain as a simple analogy for more complex phenomena. It is demonstrated how a nearly shortest path is quickly found in a familiar environment. We prove numerically that associative learning during sharp waves can account for the necessary properties of hippocampal place cells. Computational study of the model is extended to other cognitive paradigms, with the main focus on episodic memory retrieval. We show that the ability to find a correct path may be vital for successful retrieval. The model robustly exhibits the pathfinding capacity within a wide range of several factors, including its memory load (up to 30,000 abstract contexts), the number of episodes that become associated with potential target contexts, and the level of dynamical noise. We offer several testable critical predictions in both spatial and memory domains to validate the theory. Our results suggest that (1) the pathfinding function of the hippocampus, in addition to its associative and memory indexing functions, may be vital for retrieval of certain episodic memories, and (2) the hippocampal spatial navigation function could be a precursor of its memory function.