Awake replay of remote experiences in the hippocampus

Generalization of cognitive maps across space and time

Prominent theories posit that associative memory structures, known as cognitive maps, support flexible generalization of knowledge across cognitive domains. Here, we evince a representational account of cognitive map flexibility by quantifying how spatial knowledge formed one day was used predictively in a temporal sequence task 24 hours later, biasing both behavior and neural response. Participants learned novel object locations in distinct virtual environments. After learning, hippocampus and ventromedial prefrontal cortex (vmPFC) represented a cognitive map, wherein neural patterns became more similar for same-environment objects and more discriminable for different-environment objects. Twenty-four hours later, participants rated their preference for objects from spatial learning; objects were presented in sequential triplets from either the same or different environments. We found that preference response times were slower when participants transitioned between same- and different-environment triplets. Furthermore, hippocampal spatial map coherence tracked behavioral slowing at the implicit sequence transitions. At transitions, predictive reinstatement of virtual environments decreased in anterior parahippocampal cortex. In the absence of such predictive reinstatement after sequence transitions, hippocampus and vmPFC responses increased, accompanied by hippocampal-vmPFC functional decoupling that predicted individuals' behavioral slowing after a transition. Collectively, these findings reveal how expectations derived from spatial experience generalize to support temporal prediction.

The human brain reactivates context-specific past information at event boundaries of naturalistic experiences

Although we perceive the world in a continuous manner, our experience is partitioned into discrete events. However, to make sense of these events, they must be stitched together into an overarching narrative-a model of unfolding events. It has been proposed that such a stitching process happens in offline neural reactivations when rodents build models of spatial environments. Here we show that, while understanding a natural narrative, humans reactivate neural representations of past events. Similar to offline replay, these reactivations occur in the hippocampus and default mode network, where reactivations are selective to relevant past events. However, these reactivations occur, not during prolonged offline periods, but at the boundaries between ongoing narrative events. These results, replicated across two datasets, suggest reactivations as a candidate mechanism for binding temporally distant information into a coherent understanding of ongoing experience.

Execution of new trajectories toward a stable goal without a functional hippocampus

The hippocampus is a critical component of a mammalian spatial navigation system, with the firing sequences of hippocampal place cells during sleep or immobility constituting a "replay" of an animal's past trajectories. A novel spatial navigation task recently revealed that such "replay" sequences of place fields can also prospectively map onto imminent new paths to a goal that occupies a stable location during each session. It was hypothesized that such "prospective replay" sequences may play a causal role in goal-directed navigation. In the present study, we query this putative causal role in finding only minimal effects of muscimol-induced inactivation of the dorsal and intermediate hippocampus on the same spatial navigation task. The concentration of muscimol used demonstrably inhibited hippocampal cell firing in vivo and caused a severe deficit in a hippocampal-dependent "episodic-like" spatial memory task in a watermaze. These findings call into question whether "prospective replay" of an imminent and direct path is actually necessary for its execution in certain navigational tasks.

Anatomical organization of temporally correlated neural calcium activity in the hippocampal CA1 region

Hippocampal CA1 neuronal ensembles generate sequential patterns of firing activity that contribute to episodic memory formation and spatial cognition. Here we used in vivo calcium imaging to record neural ensemble activities in mouse hippocampal CA1 and identified CA1 excitatory neuron sub-populations whose members are active across the same second-long period of time. We identified groups of hippocampal neurons sharing temporally correlated neural calcium activity during behavioral exploration and found that they also organized as clusters in anatomical space. Such clusters vary in membership and activity dynamics with respect to movement in different environments, but also appear during immobility in the dark suggesting an internal dynamic. The strong covariance between dynamics and anatomical location within the CA1 sub-region reveals a previously unrecognized form of topographic representation in hippocampus that may guide generation of hippocampal sequences across time and therefore organize the content of episodic memory.

Grid Cells, Border Cells and Discrete Complex Analysis

We propose a mechanism enabling the appearance of border cells-neurons firing at the boundaries of the navigated enclosures. The approach is based on the recent discovery of discrete complex analysis on a triangular lattice, which allows constructing discrete epitomes of complex-analytic functions and making use of their inherent ability to attain maximal values at the boundaries of generic lattice domains. As it turns out, certain elements of the discrete-complex framework readily appear in the oscillatory models of grid cells. We demonstrate that these models can extend further, producing cells that increase their activity towards the frontiers of the navigated environments. We also construct a network model of neurons with border-bound firing that conforms with the oscillatory models.

Goal Choices Modify Frontotemporal Memory Representations

Adapting flexibly to changing circumstances is guided by memory of past choices, their outcomes in similar circumstances, and a method for choosing among potential actions. The hippocampus (HPC) is needed to remember episodes, and the prefrontal cortex (PFC) helps guide memory retrieval. Single-unit activity in the HPC and PFC correlates with such cognitive functions. Previous work recorded CA1 and mPFC activity as male rats performed a spatial reversal task in a plus maze that requires both structures, found that PFC activity helps reactivate HPC representations of pending goal choices but did not describe frontotemporal interactions after choices. We describe these interactions after choices here. CA1 activity tracked both current goal location and the past starting location of single trials; PFC activity tracked current goal location better than past start location. CA1 and PFC reciprocally modulated representations of each other both before and after goal choices. After choices, CA1 activity predicted changes in PFC activity in subsequent trials, and the magnitude of this prediction correlated with faster learning. In contrast, PFC start arm activity more strongly modulated CA1 activity after choices correlated with slower learning. Together, the results suggest post-choice HPC activity conveys retrospective signals to the PFC, which combines different paths to common goals into rules. In subsequent trials, prechoice mPFC activity modulates prospective CA1 signals informing goal selection.SIGNIFICANCE STATEMENT HPC and PFC activity supports cognitive flexibility in changing circumstances. HPC signals represent behavioral episodes that link the start, choice, and goal of paths. PFC signals represent rules that guide goal-directed actions. Although prior studies described HPC-PFC interactions preceding decisions in the plus maze, post-decision interactions were not investigated. Here, we show post-choice HPC and PFC activity distinguished the start and goal of paths, and CA1 signaled the past start of each trial more accurately than mPFC. Postchoice CA1 activity modulated subsequent PFC activity, so rewarded actions were more likely to occur. Together, the results show that in changing circumstances, HPC retrospective codes modulate subsequent PFC coding, which in turn modulates HPC prospective codes that predict choices.

Computational cross-species views of the hippocampal formation

The discovery of place cells and head direction cells in the hippocampal formation of freely foraging rodents has led to an emphasis of its role in encoding allocentric spatial relationships. In contrast, studies in head-fixed primates have additionally found representations of spatial views. We review recent experiments in freely moving monkeys that expand upon these findings and show that postural variables such as eye/head movements strongly influence neural activity in the hippocampal formation, suggesting that the function of the hippocampus depends on where the animal looks. We interpret these results in the light of recent studies in humans performing challenging navigation tasks which suggest that depending on the context, eye/head movements serve one of two roles-gathering information about the structure of the environment (active sensing) or externalizing the contents of internal beliefs/deliberation (embodied cognition). These findings prompt future experimental investigations into the information carried by signals flowing between the hippocampal formation and the brain regions controlling postural variables, and constitute a basis for updating computational theories of the hippocampal system to accommodate the influence of eye/head movements.

Sleep-A brain-state serving systems memory consolidation

Although long-term memory consolidation is supported by sleep, it is unclear how it differs from that during wakefulness. Our review, focusing on recent advances in the field, identifies the repeated replay of neuronal firing patterns as a basic mechanism triggering consolidation during sleep and wakefulness. During sleep, memory replay occurs during slow-wave sleep (SWS) in hippocampal assemblies together with ripples, thalamic spindles, neocortical slow oscillations, and noradrenergic activity. Here, hippocampal replay likely favors the transformation of hippocampus-dependent episodic memory into schema-like neocortical memory. REM sleep following SWS might balance local synaptic rescaling accompanying memory transformation with a sleep-dependent homeostatic process of global synaptic renormalization. Sleep-dependent memory transformation is intensified during early development despite the immaturity of the hippocampus. Overall, beyond its greater efficacy, sleep consolidation differs from wake consolidation mainly in that it is supported, rather than impaired, by spontaneous hippocampal replay activity possibly gating memory formation in neocortex.

Differential replay of reward and punishment paths predicts approach and avoidance

Neural replay is implicated in planning, where states relevant to a task goal are rapidly reactivated in sequence. It remains unclear whether, during planning, replay relates to an actual prospective choice. Here, using magnetoencephalography (MEG), we studied replay in human participants while they planned to either approach or avoid an uncertain environment containing paths leading to reward or punishment. We find evidence for forward sequential replay during planning, with rapid state-to-state transitions from 20 to 90 ms. Replay of rewarding paths was boosted, relative to aversive paths, before a decision to avoid and attenuated before a decision to approach. A trial-by-trial bias toward replaying prospective punishing paths predicted irrational decisions to approach riskier environments, an effect more pronounced in participants with higher trait anxiety. The findings indicate a coupling of replay with planned behavior, where replay prioritizes an online representation of a worst-case scenario for approaching or avoiding.

Memory reactivations during sleep: a neural basis of dream experiences?

Newly encoded memory traces are spontaneously reactivated during sleep. Since their discovery in the 1990s, these memory reactivations have been discussed as a potential neural basis for dream experiences. New results from animal and human research, as well as from the rapidly growing field of sleep and dream engineering, provide essential insights into this question, and reveal both strong parallels and disparities between the two phenomena. We suggest that, although memory reactivations may contribute to subjective experiences across different states of consciousness, they are not likely to be the primary neural basis of dreaming. We identify important limitations in current research paradigms and suggest novel strategies to address this question empirically.

Organization and Plasticity of Inhibition in Hippocampal Recurrent Circuits

Excitatory-inhibitory interactions structure recurrent network dynamics for efficient cortical computations. In the CA3 area of the hippocampus, recurrent circuit dynamics, including experience-induced plasticity at excitatory synapses, are thought to play a key role in episodic memory encoding and consolidation via rapid generation and flexible selection of neural ensembles. However, in vivo activity of identified inhibitory motifs supporting this recurrent circuitry has remained largely inaccessible, and it is unknown whether CA3 inhibition is also modifiable upon experience. Here we use large-scale, 3-dimensional calcium imaging and retrospective molecular identification in the mouse hippocampus to obtain the first comprehensive description of molecularly-identified CA3 interneuron dynamics during both spatial navigation and sharp-wave ripple (SWR)-associated memory consolidation. Our results uncover subtype-specific dynamics during behaviorally distinct brain-states. Our data also demonstrate predictive, reflective, and experience-driven plastic recruitment of specific inhibitory motifs during SWR-related memory reactivation. Together these results assign active roles for inhibitory circuits in coordinating operations and plasticity in hippocampal recurrent circuits.

How our understanding of memory replay evolves

Memory reactivations and replay, widely reported in the hippocampus and cortex across species, have been implicated in memory consolidation, planning, and spatial and skill learning. Technological advances in electrophysiology, calcium imaging, and human neuroimaging techniques have enabled neuroscientists to measure large-scale neural activity with increasing spatiotemporal resolution and have provided opportunities for developing robust analytic methods to identify memory replay. In this article, we first review a large body of historically important and representative memory replay studies from the animal and human literature. We then discuss our current understanding of memory replay functions in learning, planning, and memory consolidation and further discuss the progress in computational modeling that has contributed to these improvements. Next, we review past and present analytic methods for replay analyses and discuss their limitations and challenges. Finally, looking ahead, we discuss some promising analytic methods for detecting nonstereotypical, behaviorally nondecodable structures from large-scale neural recordings. We argue that seamless integration of multisite recordings, real-time replay decoding, and closed-loop manipulation experiments will be essential for delineating the role of memory replay in a wide range of cognitive and motor functions.

CA2 orchestrates hippocampal network dynamics

The hippocampus is composed of various subregions: CA1, CA2, CA3, and the dentate gyrus (DG). Despite the abundant hippocampal research literature, until recently, CA2 received little attention. The development of new genetic and physiological tools allowed recent studies characterizing the unique properties and functional roles of this hippocampal subregion. Despite its small size, the cellular content of CA2 is heterogeneous at the molecular and physiological levels. CA2 has been heavily implicated in social behaviors, including social memory. More generally, the mechanisms by which the hippocampus is involved in memory include the reactivation of neuronal ensembles following experience. This process is coordinated by synchronous network events known as sharp-wave ripples (SWRs). Recent evidence suggests that CA2 plays an important role in the generation of SWRs. The unique connectivity and physiological properties of CA2 pyramidal cells make this region a computational hub at the core of hippocampal information processing. Here, we review recent findings that support the role of CA2 in coordinating hippocampal network dynamics from a systems neuroscience perspective.

Behavioral status modulates CA2 influence on hippocampal network dynamics

Dynamic interactions between the subregions of the hippocampus are required for the encoding and consolidation of memory. While the interplay and contributions of the CA1 and CA3 regions are well understood, we continue to learn more about how CA2 differentially contributes to the organization of network function. For example, CA2 place cells have been reported to be less spatially tuned during exploration, but uniquely capable of coding place while an animal stops. Here we applied chemogenetics to transiently silence CA2 pyramidal cells and found that CA2 influences hippocampal dynamics in a state-dependent manner. We find that during rest, CA2 inhibition reduces synchronization across regions (CA1, CA2, CA3) and frequency bands (low-gamma- and ripple-band). Moreover, during new learning CA1 place field formation is slower in the absence of CA2 transmission and during pausing, CA1 pyramidal cells are less excitable without CA2 drive. On the network level, a novel convolutional neural network (SpikeDecoder) was employed to show subregion and state-dependent changes in spatial coding that agree with our observations on the single cell level. Together these data suggest additional novel roles for CA2 in governing and differentiating hippocampal dynamics under discrete behavioral states.

Synthetic Data Resource and Benchmarks for Time Cell Analysis and Detection Algorithms

Hippocampal CA1 cells take part in reliable, time-locked activity sequences in tasks that involve an association between temporally separated stimuli, in a manner that tiles the interval between the stimuli. Such cells have been termed time cells. Here, we adopt a first-principles approach to comparing diverse analysis and detection algorithms for identifying time cells. We generated synthetic activity datasets using calcium signals recorded in vivo from the mouse hippocampus using two-photon (2-P) imaging, as template response waveforms. We assigned known, ground truth values to perturbations applied to perfect activity signals, including noise, calcium event width, timing imprecision, hit trial ratio and background (untuned) activity. We tested a range of published and new algorithms and their variants on this dataset. We find that most algorithms correctly classify over 80% of cells, but have different balances between true and false positives, and different sensitivity to the five categories of perturbation. Reassuringly, most methods are reasonably robust to perturbations, including background activity, and show good concordance in classification of time cells. The same algorithms were also used to analyze and identify time cells in experimental physiology datasets recorded in vivo and most show good concordance.

Organization of hippocampal CA3 into correlated cell assemblies supports a stable spatial code

Hippocampal subfield CA3 is thought to stably store memories in assemblies of recurrently connected cells functioning as a collective. However, the collective hippocampal coding properties that are unique to CA3 and how such properties facilitate the stability or precision of the neural code remain unclear. Here, we performed large-scale Ca2+ imaging in hippocampal CA1 and CA3 of freely behaving mice that repeatedly explored the same, initially novel environments over weeks. CA3 place cells have more precise and more stable tuning and show a higher statistical dependence with their peers compared with CA1 place cells, uncovering a cell assembly organization in CA3. Surprisingly, although tuning precision and long-term stability are correlated, cells with stronger peer dependence exhibit higher stability but not higher precision. Overall, our results expose the three-way relationship between tuning precision, long-term stability, and peer dependence, suggesting that a cell assembly organization underlies long-term storage of information in the hippocampus.

The two tales of hippocampal sharp-wave ripple content: The rigid and the plastic

Sharp-wave ripples, prominently in the CA1 region of the hippocampus, are short oscillatory events accompanied by bursts of neural firing. Ripples and associated hippocampal place cell sequences communicate with cortical ensembles during slow-wave sleep, which has been shown to be critical for systems consolidation of episodic memories. This consolidation is not limited to a newly formed memory trace; instead, ripples appear to reactivate and consolidate memories spanning various experiences. Despite this broad spanning influence, ripples remain capable of producing precise memories. The underlying mechanisms that enable ripples to consolidate memories broadly and with specificity across experiences remain unknown. In this review, we discuss data that uncovers circuit-level processes that generate ripples and influence their characteristics during consolidation. Based on current knowledge, we propose that memory emerges from the integration of two parallel consolidation pathways in CA1: the rigid and plastic pathways. The rigid pathway generates ripples stochastically, providing a backbone upon which dynamic plastic pathway inputs carrying novel information are integrated.

Ripples in macaque V1 and V4 are modulated by top-down visual attention

Sharp-wave ripples (SWRs) are highly synchronous neuronal activity events. They have been predominantly observed in the hippocampus during offline states such as pause in exploration, slow-wave sleep, and quiescent wakefulness. SWRs have been linked to memory consolidation, spatial navigation, and spatial decision-making. Recently, SWRs have been reported during visual search, a form of remote spatial exploration, in macaque hippocampus. However, the association between SWRs and multiple forms of awake conscious and goal-directed behavior is unknown. We report that ripple activity occurs in macaque visual areas V1 and V4 during focused spatial attention. The occurrence of ripples is modulated by stimulus characteristics, increased by attention toward the receptive field, and by the size of the attentional focus. During attention cued to the receptive field, the monkey's reaction time in detecting behaviorally relevant events was reduced by ripples. These results show that ripple activity is not limited to hippocampal activity during offline states, rather they occur in the neocortex during active attentive states and vigilance behaviors.

Anteromedial Thalamus Gates the Selection & Stabilization of Long-Term Memories

Memories initially formed in hippocampus gradually stabilize to cortex, over weeks-to-months, for long-term storage. The mechanistic details of this brain re-organization process remain poorly understood. In this study, we developed a virtual-reality based behavioral task and observed neural activity patterns associated with memory reorganization and stabilization over weeks-long timescales. Initial photometry recordings in circuits that link hippocampus and cortex revealed a unique and prominent neural correlate of memory in anterior thalamus that emerged in training and persisted for several weeks. Inhibition of the anteromedial thalamus-to-anterior cingulate cortex projections during training resulted in substantial memory consolidation deficits, and gain amplification more strikingly, was sufficient to enhance consolidation of otherwise unconsolidated memories. To provide mechanistic insights, we developed a new behavioral task where mice form two memories, of which only the more salient memory is consolidated, and also a technology for simultaneous and longitudinal cellular resolution imaging of hippocampus, thalamus, and cortex throughout the consolidation window. We found that whereas hippocampus equally encodes multiple memories, the anteromedial thalamus forms preferential tuning to salient memories, and establishes inter-regional correlations with cortex, that are critical for synchronizing and stabilizing cortical representations at remote time. Indeed, inhibition of this thalamo-cortical circuit while imaging in cortex reveals loss of contextual tuning and ensemble synchrony in anterior cingulate, together with behavioral deficits in remote memory retrieval. We thus identify a thalamo-cortical circuit that gates memory consolidation and propose a mechanism suitable for the selection and stabilization of hippocampal memories into longer term cortical storage.

Rethinking retrosplenial cortex: Perspectives and predictions

The last decade has produced exciting new ideas about retrosplenial cortex (RSC) and its role in integrating diverse inputs. Here, we review the diversity in forms of spatial and directional tuning of RSC activity, temporal organization of RSC activity, and features of RSC interconnectivity with other brain structures. We find that RSC anatomy and dynamics are more consistent with roles in multiple sensorimotor and cognitive processes than with any isolated function. However, two more generalized categories of function may best characterize roles for RSC in complex cognitive processes: (1) shifting and relating perspectives for spatial cognition and (2) prediction and error correction for current sensory states with internal representations of the environment. Both functions likely take advantage of RSC's capacity to encode conjunctions among sensory, motor, and spatial mapping information streams. Together, these functions provide the scaffold for intelligent actions, such as navigation, perspective taking, interaction with others, and error detection.

Inhibition is a prevalent mode of activity in the neocortex around awake hippocampal ripples in mice

Coordinated peri-ripple activity in the hippocampal-neocortical network is essential for mnemonic information processing in the brain. Hippocampal ripples likely serve different functions in sleep and awake states. Thus, the corresponding neocortical activity patterns may differ in important ways. We addressed this possibility by conducting voltage and glutamate wide-field imaging of the neocortex with concurrent hippocampal electrophysiology in awake mice. Contrary to our previously published sleep results, deactivation and activation were dominant in post-ripple neocortical voltage and glutamate activity, respectively, especially in the agranular retrosplenial cortex (aRSC). Additionally, the spiking activity of aRSC neurons, estimated by two-photon calcium imaging, revealed the existence of two subpopulations of excitatory neurons with opposite peri-ripple modulation patterns: one increases and the other decreases firing rate. These differences in peri-ripple spatiotemporal patterns of neocortical activity in sleep versus awake states might underlie the reported differences in the function of sleep versus awake ripples.

Activity Patterns of Individual Neurons and Ensembles Correlated with Retrieval of a Contextual Memory in the Dorsal CA1 of Mouse Hippocampus

The hippocampus is crucial for retrieval of contextual memories. The activation of a subpopulation of neurons in the dorsal CA1 (dCA1) of the hippocampus is required for memory retrieval. Given that hippocampal neurons exhibit distinct patterns of response during memory retrieval, the activity patterns of individual neurons or ensembles may be critically involved in memory retrieval. However, this relation has been unclear. To investigate this question, we used an in vivo microendoscope calcium imaging technique to optically record neuronal activity in the dCA1 of male and female mice. We observed that a portion of dCA1 neurons increased their responses to the learned context after contextual fear conditioning (FC), resulting in overall increase in response of neuronal population compared with simple context exposure. Such increased response was specific to the conditioned context as it disappeared in neutral context. The magnitude of increase in neuronal responses by FC was proportional to memory strength during retrieval. The increases in activity preferentially occurred during the putative sharp wave ripple events and were not simply because of animal's movement and immobility. At the ensemble level, synchronous cell activity patterns were associated with memory retrieval. Accordingly, when such patterns were more similar between conditioned and neutral context, animals displayed proportionally more similar level of freezing. Together, these results indicate that increase in responses of individual neurons and synchronous cell activity patterns in the dCA1 neuronal network are critically involved in representing a contextual memory recall.SIGNIFICANCE STATEMENT Neurons in the dorsal CA1 of the hippocampus are crucial for memory retrieval. By using in vivo calcium imaging methods for recording neuronal activity, we demonstrate that dCA1 neurons increased their responses to the learned context specifically by FC and such changes correlated with memory strength during retrieval. Moreover, distinct synchronous cell activity patterns were formed by FC and involved in representing contextual memory retrieval. These findings reveal dynamic activity features of dCA1 neurons that are involved in contextual memory retrieval.

Compensatory cognition in neurological diseases and aging: A review of animal and human studies

Specialized individual circuits in the brain are recruited for specific functions. Interestingly, multiple neural circuitries continuously compete with each other to acquire the specialized function. However, the dominant among them compete and become the central neural network for that particular function. For example, the hippocampal principal neural circuitries are the dominant networks among many which are involved in learning processes. But, in the event of damage to the principal circuitry, many times, less dominant networks compensate for the primary network. This review highlights the psychopathologies of functional loss and the aspects of functional recuperation in the absence of the hippocampus.

Computational models of Idling brain activity for memory processing

Studying the underlying neural mechanisms of cognitive functions of the brain is one of the central questions in modern biology. Moreover, it has significantly impacted the development of novel technologies in artificial intelligence. Spontaneous activity is a unique feature of the brain and is currently lacking in many artificially constructed intelligent machines. Spontaneous activity may represent the brain's idling states, which are internally driven by neuronal networks and possibly participate in offline processing during awake, sleep, and resting states. Evidence is accumulating that the brain's spontaneous activity is not mere noise but part of the mechanisms to process information about previous experiences. A bunch of literature has shown how previous sensory and behavioral experiences influence the subsequent patterns of brain activity with various methods in various animals. It seems, however, that the patterns of neural activity and their computational roles differ significantly from area to area and from function to function. In this article, I review the various forms of the brain's spontaneous activity, especially those observed during memory processing, and some attempts to model the generation mechanisms and computational roles of such activities.

The expanded circuitry of hippocampal ripples and replay

The place cells and well-defined oscillatory population rhythms of the rodent hippocampus have served as a powerful model system in linking cells and circuits to memory function. While the initial three decades of place cell research primarily focused on the activity of neurons during exploration, the last twenty-five years have seen growing interest in the physiology of the hippocampus at rest. During slow-wave sleep and quiet wakefulness the hippocampus exhibits sharp-wave ripples (SWRs), short high-frequency, high-amplitude oscillations, that organize the reactivation or 'replay' of sequences of place cells, and interventions that disrupt SWRs impair learning. While the canonical model of SWRs generation have emphasized CA3 input to CA1 as the source of excitatory drive, recent work suggests there are multiple circuits, including the CA2 region, that can both influence, generate and organize SWRs, both from the oscillatory and information content perspectives in a task and state-dependent manner. This extended circuitry and its function must be considered for a true understanding of the role of the hippocampus in off-line processes such as planning and consolidation.

Imagination as a fundamental function of the hippocampus

Imagination is a biological function that is vital to human experience and advanced cognition. Despite this importance, it remains unknown how imagination is realized in the brain. Substantial research focusing on the hippocampus, a brain structure traditionally linked to memory, indicates that firing patterns in spatially tuned neurons can represent previous and upcoming paths in space. This work has generally been interpreted under standard views that the hippocampus implements cognitive abilities primarily related to actual experience, whether in the past (e.g. recollection, consolidation), present (e.g. spatial mapping) or future (e.g. planning). However, relatively recent findings in rodents identify robust patterns of hippocampal firing corresponding to a variety of alternatives to actual experience, in many cases without overt reference to the past, present or future. Given these findings, and others on hippocampal contributions to human imagination, we suggest that a fundamental function of the hippocampus is to generate a wealth of hypothetical experiences and thoughts. Under this view, traditional accounts of hippocampal function in episodic memory and spatial navigation can be understood as particular applications of a more general system for imagination. This view also suggests that the hippocampus contributes to a wider range of cognitive abilities than previously thought. This article is part of the theme issue 'Thinking about possibilities: mechanisms, ontogeny, functions and phylogeny'.

No evidence for a preferential role of sleep in episodic memory abstraction

Substantial evidence suggests that sleep has a role in declarative memory consolidation. An influential notion holds that such sleep-related memory consolidation is associated with a process of abstraction. The neural underpinnings of this putative process are thought to involve a hippocampo-neocortical dialogue. Specifically, the idea is that, during sleep, the statistical contingencies across episodes are re-coded to a less hippocampus-dependent format, while at the same time losing configural information. Two previous studies from our lab, however, failed to show a preferential role of sleep in either episodic memory decontextualisation or the formation of abstract knowledge across episodic exemplars. Rather these processes occurred over sleep and wake time alike. Here, we present two experiments that replicate and extend these previous studies and exclude some alternative interpretations. The combined data show that sleep has no preferential function in this respect. Rather, hippocampus-dependent memories are generalised to an equal extent across both wake and sleep time. The one point on which sleep outperforms wake is actually the preservation of episodic detail of memories stored prior to sleep.

Post-encoding Reactivation Is Related to Learning of Episodes in Humans

Prior animal and human studies have shown that post-encoding reinstatement plays an important role in organizing the temporal sequence of unfolding episodes in memory. Here, we investigated whether post-encoding reinstatement serves to promote the encoding of "one-shot" episodic learning beyond the temporal structure in humans. In Experiment 1, participants encoded sequences of pictures depicting unique and meaningful episodic-like events. We used representational similarity analysis on scalp EEG recordings during encoding and found evidence of rapid picture-elicited EEG pattern reinstatement at episodic offset (around 500 msec post-episode). Memory reinstatement was not observed between successive elements within an episode, and the degree of memory reinstatement at episodic offset predicted later recall for that episode. In Experiment 2, participants encoded a shuffled version of the picture sequences from Experiment 1, rendering each episode meaningless to the participant but temporally structured as in Experiment 1, and we found no evidence of memory reinstatement at episodic offset. These results suggest that post-encoding memory reinstatement is akin to the rapid formation of unique and meaningful episodes that unfold over time.

Context-independent expression of spatial code in hippocampus

The hippocampus plays a crucial role in the formation and retrieval of spatial memory across mammals and episodic memory in humans. Episodic and spatial memories can be retrieved irrespective of the subject's awake behavioral state and independently of its actual spatial context. However, the nature of hippocampal network activity during such out-context retrieval has not been described so far. Theoretically, context-independent spatial memory retrieval suggests a shift of the hippocampal spatial representations from coding the current spatial context to coding the remembered environment. In this study we show in rats that the CA3 neuronal population can switch spontaneously across representations and transiently activate another stored familiar spatial pattern without direct external sensory cuing. This phenomenon qualitatively differs from the well-described sharp wave-related pattern reactivations during immobility. Here, it occurs under the theta oscillatory state during active exploration and reflects the preceding experience of sudden environmental change. The respective out-context coding spikes appeared later in the theta cycle than the in-context ones. Finally, the experience also induced the emergence of population vectors with a co-expression of both codes segregated into different phases of the theta cycle.

Mesoscopic description of hippocampal replay and metastability in spiking neural networks with short-term plasticity

Bottom-up models of functionally relevant patterns of neural activity provide an explicit link between neuronal dynamics and computation. A prime example of functional activity patterns are propagating bursts of place-cell activities called hippocampal replay, which is critical for memory consolidation. The sudden and repeated occurrences of these burst states during ongoing neural activity suggest metastable neural circuit dynamics. As metastability has been attributed to noise and/or slow fatigue mechanisms, we propose a concise mesoscopic model which accounts for both. Crucially, our model is bottom-up: it is analytically derived from the dynamics of finite-size networks of Linear-Nonlinear Poisson neurons with short-term synaptic depression. As such, noise is explicitly linked to stochastic spiking and network size, and fatigue is explicitly linked to synaptic dynamics. To derive the mesoscopic model, we first consider a homogeneous spiking neural network and follow the temporal coarse-graining approach of Gillespie to obtain a "chemical Langevin equation", which can be naturally interpreted as a stochastic neural mass model. The Langevin equation is computationally inexpensive to simulate and enables a thorough study of metastable dynamics in classical setups (population spikes and Up-Down-states dynamics) by means of phase-plane analysis. An extension of the Langevin equation for small network sizes is also presented. The stochastic neural mass model constitutes the basic component of our mesoscopic model for replay. We show that the mesoscopic model faithfully captures the statistical structure of individual replayed trajectories in microscopic simulations and in previously reported experimental data. Moreover, compared to the deterministic Romani-Tsodyks model of place-cell dynamics, it exhibits a higher level of variability regarding order, direction and timing of replayed trajectories, which seems biologically more plausible and could be functionally desirable. This variability is the product of a new dynamical regime where metastability emerges from a complex interplay between finite-size fluctuations and local fatigue.

Neuronal signature of spatial decision-making during navigation by freely moving rats by using calcium imaging

A challenge in spatial memory is understanding how place cell firing contributes to decision-making in navigation. A spatial recency task was created in which freely moving rats first became familiar with a spatial context over several days and thereafter were required to encode and then selectively recall one of three specific locations within it that was chosen to be rewarded that day. Calcium imaging was used to record from more than 1,000 cells in area CA1 of the hippocampus of five rats during the exploration, sample, and choice phases of the daily task. The key finding was that neural activity in the startbox rose steadily in the short period prior to entry to the arena and that this selective population cell firing was predictive of the daily changing goal on correct trials but not on trials in which the animals made errors. Single-cell and population activity measures converged on the idea that prospective coding of neural activity can be involved in navigational decision-making.

Advanced age has dissociable effects on hippocampal CA1 ripples and CA3 high frequency events in male rats

Sharp wave/ripples/high frequency events (HFEs) are transient bursts of depolarization in hippocampal subregions CA3 and CA1 that occur during rest and pauses in behavior. Previous studies have reported that CA1 ripples in aged rats have lower frequency than those detected in young animals. While CA1 ripples are thought to be driven by CA3, HFEs in CA3 have not been examined in aged animals. The current study obtained simultaneous recordings from CA1 and CA3 in young and aged rats to examine sharp wave/ripples/HFEs in relation to age. While CA1 ripple frequency was reduced with age, there were no age differences in the frequency of CA3 HFEs, although power and length were lower in old animals. While there was a proportion of CA1 ripples that co-occurred with a CA3 HFE, none of the age-related differences in CA1 ripples could be explained by alterations in CA3 HFE characteristics. These findings suggest that age differences in CA1 are not due to altered CA3 activity, but instead reflect distinct mechanisms of ripple generation with age.

Experience-driven rate modulation is reinstated during hippocampal replay

Replay, the sequential reactivation within a neuronal ensemble, is a central hippocampal mechanism postulated to drive memory processing. While both rate and place representations are used by hippocampal place cells to encode behavioral episodes, replay has been largely defined by only the latter – based on the fidelity of sequential activity across neighboring place fields. Here, we show that dorsal CA1 place cells in rats can modulate their firing rate between replay events of two different contexts. This experience-dependent phenomenon mirrors the same pattern of rate modulation observed during behavior and can be used independently from place information within replay sequences to discriminate between contexts. Our results reveal the existence of two complementary neural representations available for memory processes.

How do our brains store memories? We now know that this is a complex and dynamic process, involving multiple regions of the brain. A brain region, called the hippocampus, plays an important role in memory formation. While we sleep, the hippocampus works to consolidate information, and eventually creates stable, long-term memories that are then stored in other parts of the brain.

But how does the hippocampus do this? Neuroscientists believe that it can replay the patterns of brain activity that represent particular memories. By repeatedly doing this while we sleep, the hippocampus can then direct the transfer of this information to the rest of the brain for storage.

The behaviour of nerve cells in the brain underpins these patterns of brain activity. When a nerve cell is active, it fires tiny electrical impulses that can be detected experimentally. The brain thus represents information in two ways: which nerve cells are active and when (sequential patterns); and how active the nerve cells are (how fast they fire electrical impulses or firing rate). For example, when an animal moves from one location to another, special place cells in the hippocampus become active in a distinct sequence. Depending on the context, they will also fire faster or slower.

We know that the hippocampus can replay sequential patterns of nerve cell activity during memory consolidation, but whether it can also replay the firing rates associated with a particular experience is still unknown. Tirole, Huelin Gorriz et al. set out to determine if the hippocampus could also preserve the information encoded by firing rate during replay.

In the experiments, rats explored two different environments that they had not seen before. The activity of the rats’ place cells was recorded before and after they explored, and also later while they were sleeping. Analysis of the recordings revealed that during replay, the rats’ hippocampi could indeed reproduce both the sequential patterns of activity and the firing rate of the place cells. It also confirmed that each environment was associated with unique firing rates – in other words, the firing rates were memory-specific.

These results contribute to our understanding of how the hippocampus represents and processes information about our experiences. More broadly, they also shed new light on how the brain lays down memories, by revealing a key part of the mechanism that it uses to consolidate that information.

Is the role of sleep in memory consolidation overrated?

Substantial empirical evidence suggests that sleep benefits the consolidation and reorganization of learned information. Consequently, the concept of "sleep-dependent memory consolidation" is now widely accepted by the scientific community, in addition to influencing public perceptions regarding the functions of sleep. There are, however, numerous studies that have presented findings inconsistent with the sleep-memory hypothesis. Here, we challenge the notion of "sleep-dependency" by summarizing evidence for effective memory consolidation independent of sleep. Plasticity mechanisms thought to mediate or facilitate consolidation during sleep (e.g., neuronal replay, reactivation, slow oscillations, neurochemical milieu) also operate during non-sleep states, particularly quiet wakefulness, thus allowing for the stabilization of new memories. We propose that it is not sleep per se, but the engagement of plasticity mechanisms, active during both sleep and (at least some) waking states, that constitutes the critical factor determining memory formation. Thus, rather than playing a "critical" role, sleep falls along a continuum of behavioral states that vary in their effectiveness to support memory consolidation at the neural and behavioral level.

Multiple-Timescale Representations of Space: Linking Memory to Navigation

When navigating through space, we must maintain a representation of our position in real time; when recalling a past episode, a memory can come back in a flash. Interestingly, the brain's spatial representation system, including the hippocampus, supports these two distinct timescale functions. How are neural representations of space used in the service of both real-world navigation and internal mnemonic processes? Recent progress has identified sequences of hippocampal place cells, evolving at multiple timescales in accordance with either navigational behaviors or internal oscillations, that underlie these functions. We review experimental findings on experience-dependent modulation of these sequential representations and consider how they link real-world navigation to time-compressed memories. We further discuss recent work suggesting the prevalence of these sequences beyond hippocampus and propose that these multiple-timescale mechanisms may represent a general algorithm for organizing cell assemblies, potentially unifying the dual roles of the spatial representation system in memory and navigation.

Altered brain rhythms and behaviour in the accelerated ovarian failure mouse model of human menopause

To date, potential mechanisms of menopause-related memory and cognitive deficits have not been elucidated. Therefore, we studied brain oscillations, their phase–amplitude coupling, sleep and vigilance state patterns, running wheel use and other behavioural measures in a translationally valid mouse model of menopause, the 4-vinylcyclohexene-diepoxide-induced accelerated ovarian failure. After accelerated ovarian failure, female mice show significant alterations in brain rhythms, including changes in the frequencies of θ (5–12 Hz) and γ (30–120 Hz) oscillations, a reversed phase–amplitude coupling, altered coupling of hippocampal sharp-wave ripples to medial prefrontal cortical sleep spindles and reduced δ oscillation (0.5–4 Hz) synchrony between the two regions during non-rapid eye movement sleep. In addition, we report on significant circadian variations in the frequencies of θ and γ oscillations, and massive synchronous δ oscillations during wheel running. Our results reveal novel and specific network alterations and feasible signs for diminished brain connectivity in the accelerated ovarian failure mouse model of menopause. Taken together, our results may have identified changes possibly responsible for some of the memory and cognitive deficits previously described in this model. Corresponding future studies in menopausal women could shed light on fundamental mechanisms underlying the neurological and psychiatric comorbidities present during this important transitional phase in women’s lives.

Model-Based and Model-Free Replay Mechanisms for Reinforcement Learning in Neurorobotics

Experience replay is widely used in AI to bootstrap reinforcement learning (RL) by enabling an agent to remember and reuse past experiences. Classical techniques include shuffled-, reversed-ordered- and prioritized-memory buffers, which have different properties and advantages depending on the nature of the data and problem. Interestingly, recent computational neuroscience work has shown that these techniques are relevant to model hippocampal reactivations recorded during rodent navigation. Nevertheless, the brain mechanisms for orchestrating hippocampal replay are still unclear. In this paper, we present recent neurorobotics research aiming to endow a navigating robot with a neuro-inspired RL architecture (including different learning strategies, such as model-based (MB) and model-free (MF), and different replay techniques). We illustrate through a series of numerical simulations how the specificities of robotic experimentation (e.g., autonomous state decomposition by the robot, noisy perception, state transition uncertainty, non-stationarity) can shed new lights on which replay techniques turn out to be more efficient in different situations. Finally, we close the loop by raising new hypotheses for neuroscience from such robotic models of hippocampal replay.

Learned Motor Patterns Are Replayed in Human Motor Cortex during Sleep

Consolidation of memory is believed to involve offline replay of neural activity. While amply demonstrated in rodents, evidence for replay in humans, particularly regarding motor memory, is less compelling. To determine whether replay occurs after motor learning, we sought to record from motor cortex during a novel motor task and subsequent overnight sleep. A 36-year-old man with tetraplegia secondary to cervical spinal cord injury enrolled in the ongoing BrainGate brain-computer interface pilot clinical trial had two 96-channel intracortical microelectrode arrays placed chronically into left precentral gyrus. Single- and multi-unit activity was recorded while he played a color/sound sequence matching memory game. Intended movements were decoded from motor cortical neuronal activity by a real-time steady-state Kalman filter that allowed the participant to control a neurally driven cursor on the screen. Intracortical neural activity from precentral gyrus and 2-lead scalp EEG were recorded overnight as he slept. When decoded using the same steady-state Kalman filter parameters, intracortical neural signals recorded overnight replayed the target sequence from the memory game at intervals throughout at a frequency significantly greater than expected by chance. Replay events occurred at speeds ranging from 1 to 4 times as fast as initial task execution and were most frequently observed during slow-wave sleep. These results demonstrate that recent visuomotor skill acquisition in humans may be accompanied by replay of the corresponding motor cortex neural activity during sleep.SIGNIFICANCE STATEMENT Within cortex, the acquisition of information is often followed by the offline recapitulation of specific sequences of neural firing. Replay of recent activity is enriched during sleep and may support the consolidation of learning and memory. Using an intracortical brain-computer interface, we recorded and decoded activity from motor cortex as a human research participant performed a novel motor task. By decoding neural activity throughout subsequent sleep, we find that neural sequences underlying the recently practiced motor task are repeated throughout the night, providing direct evidence of replay in human motor cortex during sleep. This approach, using an optimized brain-computer interface decoder to characterize neural activity during sleep, provides a framework for future studies exploring replay, learning, and memory.

GABAergic CA1 neurons are more stable following context changes than glutamatergic cells

The CA1 region of the hippocampus contains both glutamatergic pyramidal cells and GABAergic interneurons. Numerous reports have characterized glutamatergic CAMK2A cell activity, showing how these cells respond to environmental changes such as local cue rotation and context re-sizing. Additionally, the long-term stability of spatial encoding and turnover of these cells across days is also well-characterized. In contrast, these classic hippocampal experiments have never been conducted with CA1 GABAergic cells. Here, we use chronic calcium imaging of male and female mice to compare the neural activity of VGAT and CAMK2A cells during exploration of unaltered environments and also during exposure to contexts before and after rotating and changing the length of the context across multiple recording days. Intriguingly, compared to CAMK2A cells, VGAT cells showed decreased remapping induced by environmental changes, such as context rotations and contextual length resizing. However, GABAergic neurons were also less likely than glutamatergic neurons to remain active and exhibit consistent place coding across recording days. Interestingly, despite showing significant spatial remapping across days, GABAergic cells had stable speed encoding between days. Thus, compared to glutamatergic cells, spatial encoding of GABAergic cells is more stable during within-session environmental perturbations, but is less stable across days. These insights may be crucial in accurately modeling the features and constraints of hippocampal dynamics in spatial coding.

Neural kernels for recursive support vector regression as a model for episodic memory

Retrieval of episodic memories requires intrinsic reactivation of neuronal activity patterns. The content of the memories is thereby assumed to be stored in synaptic connections. This paper proposes a theory in which these are the synaptic connections that specifically convey the temporal order information contained in the sequences of a neuronal reservoir to the sensory-motor cortical areas that give rise to the subjective impression of retrieval of sensory motor events. The theory is based on a novel recursive version of support vector regression that allows for efficient continuous learning that is only limited by the representational capacity of the reservoir. The paper argues that hippocampal theta sequences are a potential neural substrate underlying this reservoir. The theory is consistent with confabulations and post hoc alterations of existing memories.

HectoSTAR μLED Optoelectrodes for Large-Scale, High-Precision In Vivo Opto-Electrophysiology

Dynamic interactions within and across brain areas underlie behavioral and cognitive functions. To understand the basis of these processes, the activities of distributed local circuits inside the brain of a behaving animal must be synchronously recorded while the inputs to these circuits are precisely manipulated. Even though recent technological advances have enabled such large-scale recording capabilities, the development of the high-spatiotemporal-resolution and large-scale modulation techniques to accompany those recordings has lagged. A novel neural probe is presented in this work that enables simultaneous electrical monitoring and optogenetic manipulation of deep neuronal circuits at large scales with a high spatiotemporal resolution. The "hectoSTAR" micro-light-emitting-diode (μLED) optoelectrode features 256 recording electrodes and 128 stimulation μLEDs monolithically integrated on the surface of its four 30-µm thick silicon micro-needle shanks, covering a large volume with 1.3-mm × 0.9-mm cross-sectional area located as deep as 6 mm inside the brain. The use of this device in behaving mice for dissecting long-distance network interactions across cortical layers and hippocampal regions is demonstrated. The recording-and-stimulation capabilities hectoSTAR μLED optoelectrodes enables will open up new possibilities for the cellular and circuit-based investigation of brain functions in behaving animals.

Impact of optogenetic pulse design on CA3 learning and replay: A neural model

Optogenetic manipulation of hippocampal circuitry is an important tool for investigating learning in vivo. Numerous approaches to pulse design have been employed to elicit desirable circuit and behavioral outcomes. Here, we systematically test the outcome of different single-pulse waveforms in a rate-based model of hippocampal memory function at the level of mnemonic replay extension and de novo synaptic weight formation in CA3 and CA1. Lower-power waveforms with long forward or forward and backward ramps yield more natural sequence replay dynamics and induce synaptic plasticity that allows for more natural memory replay timing, in contrast to square or backward ramps. These differences between waveform shape and amplitude are preserved with the addition of noise in membrane potential, light scattering, and protein expression, improving the potential validity of predictions for in vivo work. These results inform future optogenetic experimental design choices in the field of learning and memory.

Spatial Learning Drives Rapid Goal Representation in Hippocampal Ripples without Place Field Accumulation or Goal-Oriented Theta Sequences

The hippocampus is critical for rapid acquisition of many forms of memory, although the circuit-level mechanisms through which the hippocampus rapidly consolidates novel information are unknown. Here, the activity of large ensembles of hippocampal neurons in adult male Long-Evans rats was monitored across a period of rapid spatial learning to assess how the network changes during the initial phases of memory formation and retrieval. In contrast to several reports, the hippocampal network did not display enhanced representation of the goal location via accumulation of place fields or elevated firing rates at the goal. Rather, population activity rates increased globally as a function of experience. These alterations in activity were mirrored in the power of the theta oscillation and in the quality of theta sequences, without preferential encoding of paths to the learned goal location. In contrast, during brief "offline" pauses in movement, representation of a novel goal location emerged rapidly in ripples, preceding other changes in network activity. These data demonstrate that the hippocampal network can facilitate active navigation without enhanced goal representation during periods of active movement, and further indicate that goal representation in hippocampal ripples before movement onset supports subsequent navigation, possibly through activation of downstream cortical networks.SIGNIFICANCE STATEMENT Understanding the mechanisms through which the networks of the brain rapidly assimilate information and use previously learned knowledge are fundamental areas of focus in neuroscience. In particular, the hippocampal circuit is a critical region for rapid formation and use of spatial memory. In this study, several circuit-level features of hippocampal function were quantified while rats performed a spatial navigation task requiring rapid memory formation and use. During periods of active navigation, a general increase in overall network activity is observed during memory acquisition, which plateaus during memory retrieval periods, without specific enhanced representation of the goal location. During pauses in navigation, rapid representation of the distant goal well emerges before either behavioral improvement or changes in online activity.

A Variable Clock Underlies Internally Generated Hippocampal Sequences

Humans have the ability to store and retrieve memories with various degrees of specificity, and recent advances in reinforcement learning have identified benefits to learning when past experience is represented at different levels of temporal abstraction. How this flexibility might be implemented in the brain remains unclear. We analyzed the temporal organization of male rat hippocampal population spiking to identify potential substrates for temporally flexible representations. We examined activity both during locomotion and during memory-associated population events known as sharp-wave ripples (SWRs). We found that spiking during SWRs is rhythmically organized with higher event-to-event variability than spiking during locomotion-associated population events. Decoding analyses using clusterless methods further indicate that a similar spatial experience can be replayed in multiple SWRs, each time with a different rhythmic structure whose periodicity is sampled from a log-normal distribution. This variability increases with experience despite the decline in SWR rates that occurs as environments become more familiar. We hypothesize that the variability in temporal organization of hippocampal spiking provides a mechanism for storing experiences with various degrees of specificity.SIGNIFICANCE STATEMENT One of the most remarkable properties of memory is its flexibility: the brain can retrieve stored representations at varying levels of detail where, for example, we can begin with a memory of an entire extended event and then zoom in on a particular episode. The neural mechanisms that support this flexibility are not understood. Here we show that hippocampal sharp-wave ripples, which mark the times of memory replay and are important for memory storage, have a highly variable temporal structure that is well suited to support the storage of memories at different levels of detail.

Hippocampal replays appear after a single experience and incorporate greater detail with more experience

The hippocampus is implicated in memory formation, and neurons in the hippocampus take part in replay sequences that have been proposed to reflect memory of explored space. By recording from large ensembles of hippocampal neurons as rats explored various tracks, we show that sustained replay appears after a single experience. Further, we found that with repeated experience in a novel environment, replay slows down, taking more time to traverse the same trajectory. This effect was dependent on experience, not passage of time, and was environment specific. By investigating the slow-gamma (25-50 Hz) hover-and-jump dynamics within replays, we show that replay slows by adding more hover locations, increasing the resolution of the behavioral trajectory. We provide evidence that inhibition and cortical engagement both increase as replay slows. Thus, replays can reflect single experiences and evolve with re-exposure, in a manner consistent with the encoding of greater detail into replay memories with experience.

Goal discrimination in hippocampal nonplace cells when place information is ambiguous

SignificanceGoal-directed spatial navigation has been found to rely on hippocampal neurons that are spatially modulated. We show that "nonplace" cells without significant spatial modulation play a role in discriminating goals when environmental cues for goals are ambiguous. This nonplace cell activity is performance-dependent and is modulated by gamma oscillations. Finally, nonplace cell goal discrimination coding fails in a mouse model of Alzheimer's disease (AD). Together, these results show that nonplace cell firing can signal unique task-relevant information when spatial information is ambiguous; these signals depend on performance and are absent in a mouse model of AD.

Decoding cognition from spontaneous neural activity

In human neuroscience, studies of cognition are rarely grounded in non-task-evoked, 'spontaneous' neural activity. Indeed, studies of spontaneous activity tend to focus predominantly on intrinsic neural patterns (for example, resting-state networks). Taking a 'representation-rich' approach bridges the gap between cognition and resting-state communities: this approach relies on decoding task-related representations from spontaneous neural activity, allowing quantification of the representational content and rich dynamics of such activity. For example, if we know the neural representation of an episodic memory, we can decode its subsequent replay during rest. We argue that such an approach advances cognitive research beyond a focus on immediate task demand and provides insight into the functional relevance of the intrinsic neural pattern (for example, the default mode network). This in turn enables a greater integration between human and animal neuroscience, facilitating experimental testing of theoretical accounts of intrinsic activity, and opening new avenues of research in psychiatry.

Observational learning promotes hippocampal remote awake replay toward future reward locations

The neural circuit mechanisms underlying observational learning, learning through observing the behavior of others, are poorly understood. Hippocampal place cells are important for spatial learning, and awake replay of place cell patterns is involved in spatial decisions. Here we show that, in observer rats learning to run a maze by watching a demonstrator's spatial trajectories from a separate nearby observation box, place cell patterns during self-running in the maze are replayed remotely in the box. The contents of the remote awake replay preferentially target the maze's reward sites from both forward and reverse replay directions and reflect the observer's future correct trajectories in the maze. In contrast, under control conditions without a demonstrator, the remote replay is significantly reduced, and the preferences for reward sites and future trajectories disappear. Our results suggest that social observation directs the contents of remote awake replay to guide spatial decisions in observational learning.

High-frequency oscillations and sequence generation in two-population models of hippocampal region CA1

Hippocampal sharp wave/ripple oscillations are a prominent pattern of collective activity, which consists of a strong overall increase of activity with superimposed (140 − 200 Hz) ripple oscillations. Despite its prominence and its experimentally demonstrated importance for memory consolidation, the mechanisms underlying its generation are to date not understood. Several models assume that recurrent networks of inhibitory cells alone can explain the generation and main characteristics of the ripple oscillations. Recent experiments, however, indicate that in addition to inhibitory basket cells, the pattern requires in vivo the activity of the local population of excitatory pyramidal cells. Here, we study a model for networks in the hippocampal region CA1 incorporating such a local excitatory population of pyramidal neurons. We start by investigating its ability to generate ripple oscillations using extensive simulations. Using biologically plausible parameters, we find that short pulses of external excitation triggering excitatory cell spiking are required for sharp/wave ripple generation with oscillation patterns similar to in vivo observations. Our model has plausible values for single neuron, synapse and connectivity parameters, random connectivity and no strong feedforward drive to the inhibitory population. Specifically, whereas temporally broad excitation can lead to high-frequency oscillations in the ripple range, sparse pyramidal cell activity is only obtained with pulse-like external CA3 excitation. Further simulations indicate that such short pulses could originate from dendritic spikes in the apical or basal dendrites of CA1 pyramidal cells, which are triggered by coincident spike arrivals from hippocampal region CA3. Finally we show that replay of sequences by pyramidal neurons and ripple oscillations can arise intrinsically in CA1 due to structured connectivity that gives rise to alternating excitatory pulse and inhibitory gap coding; the latter denotes phases of silence in specific basket cell groups, which induce selective disinhibition of groups of pyramidal neurons. This general mechanism for sequence generation leads to sparse pyramidal cell and dense basket cell spiking, does not rely on synfire chain-like feedforward excitation and may be relevant for other brain regions as well.

Hippocampal sharp wave-ripples and the associated sequence replay emerge from structured synaptic interactions in a network model of area CA3

Hippocampal place cells are activated sequentially as an animal explores its environment. These activity sequences are internally recreated (‘replayed’), either in the same or reversed order, during bursts of activity (sharp wave-ripples [SWRs]) that occur in sleep and awake rest. SWR-associated replay is thought to be critical for the creation and maintenance of long-term memory. In order to identify the cellular and network mechanisms of SWRs and replay, we constructed and simulated a data-driven model of area CA3 of the hippocampus. Our results show that the chain-like structure of recurrent excitatory interactions established during learning not only determines the content of replay, but is essential for the generation of the SWRs as well. We find that bidirectional replay requires the interplay of the experimentally confirmed, temporally symmetric plasticity rule, and cellular adaptation. Our model provides a unifying framework for diverse phenomena involving hippocampal plasticity, representations, and dynamics, and suggests that the structured neural codes induced by learning may have greater influence over cortical network states than previously appreciated.