Rewarded outcomes enhance reactivation of experience in the hippocampus

Inhibitory plasticity supports replay generalization in the hippocampus

Memory consolidation assimilates recent experiences into long-term memory. This process requires the replay of learned sequences, although the content of these sequences remains controversial. Recent work has shown that the statistics of replay deviate from those of experience: stimuli that are experientially salient may be either recruited or suppressed from sharp-wave ripples. In this study, we found that this phenomenon can be explained parsimoniously and biologically plausibly by a Hebbian spike-time-dependent plasticity rule at inhibitory synapses. Using models at three levels of abstraction-leaky integrate-and-fire, biophysically detailed and abstract binary-we show that this rule enables efficient generalization, and we make specific predictions about the consequences of intact and perturbed inhibitory dynamics for network dynamics and cognition. Finally, we use optogenetics to artificially implant non-generalizable representations into the network in awake behaving mice, and we find that these representations also accumulate inhibition during sharp-wave ripples, experimentally validating a major prediction of our model. Our work outlines a potential direct link between the synaptic and cognitive levels of memory consolidation, with implications for both normal learning and neurological disease.

Event boundaries drive norepinephrine release and distinctive neural representations of space in the rodent hippocampus

Episodic memories are temporally segmented around event boundaries that tend to coincide with moments of environmental change. During these times, the state of the brain should change rapidly, or reset, to ensure that the information encountered before and after an event boundary is encoded in different neuronal populations. Norepinephrine (NE) is thought to facilitate this network reorganization. However, it is unknown whether event boundaries drive NE release in the hippocampus and, if so, how NE release relates to changes in hippocampal firing patterns. The advent of the new GRABNE sensor now allows for the measurement of NE binding with sub-second resolution. Using this tool in mice, we tested whether NE is released into the dorsal hippocampus during event boundaries defined by unexpected transitions between spatial contexts and presentations of novel objections. We found that NE binding dynamics were well explained by the time elapsed after each of these environmental changes, and were not related to conditioned behaviors, exploratory bouts of movement, or reward. Familiarity with a spatial context accelerated the rate in which phasic NE binding decayed to baseline. Knowing when NE is elevated, we tested how hippocampal coding of space differs during these moments. Immediately after context transitions we observed relatively unique patterns of neural spiking which settled into a modal state at a similar rate in which NE returned to baseline. These results are consistent with a model wherein NE release drives hippocampal representations away from a steady-state attractor. We hypothesize that the distinctive neural codes observed after each event boundary may facilitate long-term memory and contribute to the neural basis for the primacy effect.

Pain recognition and pain empathy from a human-centered AI perspective

Sensory and emotional experiences are essential for mental and physical well-being, especially within the realm of psychiatry. This article highlights recent advances in cognitive neuroscience, emphasizing the significance of pain recognition and empathic artificial intelligence (AI) in healthcare. We provide an overview of the recent development process in computational pain recognition and cognitive neuroscience regarding the mechanisms of pain and empathy. Through a comprehensive discussion, the article delves into critical questions such as the methodologies for AI in recognizing pain from diverse sources of information, the necessity for AI to exhibit empathic responses, and the associated advantages and obstacles linked with the development of empathic AI. Moreover, insights into the prospects and challenges are emphasized in relation to fostering artificial empathy. By delineating potential pathways for future research, the article aims to contribute to developing effective assistants equipped with empathic capabilities, thereby introducing safe and meaningful interactions between humans and AI, particularly in the context of mental health and psychiatry.

Differential stability of task variable representations in retrosplenial cortex

Cortical neurons store information across different timescales, from seconds to years. Although information stability is variable across regions, it can vary within a region as well. Association areas are known to multiplex behaviorally relevant variables, but the stability of their representations is not well understood. Here, we longitudinally recorded the activity of neuronal populations in the mouse retrosplenial cortex (RSC) during the performance of a context-choice association task. We found that the activity of neurons exhibits different levels of stability across days. Using linear classifiers, we quantified the stability of three task-relevant variables. We find that RSC representations of context and trial outcome display higher stability than motor choice, both at the single cell and population levels. Together, our findings show an important characteristic of association areas, where diverse streams of information are stored with varying levels of stability, which may balance representational reliability and flexibility according to behavioral demands.

Selective reactivation of value- and place-dependent information during sharp-wave ripples in the intermediate and dorsal hippocampus

Reactivating place cells during sharp-wave ripples in the hippocampus is important for memory consolidation. However, whether hippocampal reactivation is affected by the values of events experienced by the animal is largely unknown. Here, we investigated whether place cells in the dorsal (dHP) and intermediate hippocampus (iHP) of rats are differentially reactivated depending on the value associated with a place during the learning of places associated with higher-value rewards in a T-maze. Place cells in the iHP representing the high-value location were reactivated significantly more frequently than those representing the low-value location, characteristics not observed in the dHP. In contrast, the activities of place cells in the dHP coding the routes leading to high-value locations were replayed more than those in the iHP. Our findings suggest that value-based differential reactivation patterns along the septotemporal axis of the hippocampus may play essential roles in optimizing goal-directed spatial learning for maximal reward.

Learning, Fast and Slow: Single- and Many-Shot Learning in the Hippocampus

The hippocampus is critical for memory and spatial navigation. The ability to map novel environments, as well as more abstract conceptual relationships, is fundamental to the cognitive flexibility that humans and other animals require to survive in a dynamic world. In this review, we survey recent advances in our understanding of how this flexibility is implemented anatomically and functionally by hippocampal circuitry, during both active exploration (online) and rest (offline). We discuss the advantages and limitations of spike timing-dependent plasticity and the more recently discovered behavioral timescale synaptic plasticity in supporting distinct learning modes in the hippocampus. Finally, we suggest complementary roles for these plasticity types in explaining many-shot and single-shot learning in the hippocampus and discuss how these rules could work together to support the learning of cognitive maps.

Spatial localization of hippocampal replay requires dopamine signaling

Sequenced reactivations of hippocampal neurons called replays, concomitant with sharp-wave ripples in the local field potential, are critical for the consolidation of episodic memory, but whether replays depend on the brain's reward or novelty signals is unknown. Here we combined chemogenetic silencing of dopamine neurons in ventral tegmental area (VTA) and simultaneous electrophysiological recordings in dorsal hippocampal CA1, in freely behaving rats experiencing changes to reward magnitude and environmental novelty. Surprisingly, VTA silencing did not prevent ripple increases where reward was increased, but caused dramatic, aberrant ripple increases where reward was unchanged. These increases were associated with increased reverse-ordered replays. On familiar tracks this effect disappeared, and ripples tracked reward prediction error, indicating that non-VTA reward signals were sufficient to direct replay. Our results reveal a novel dependence of hippocampal replay on dopamine, and a role for a VTA-independent reward prediction error signal that is reliable only in familiar environments.

Closed-loop modulation of remote hippocampal representations with neurofeedback

Humans can remember specific events without acting on them and can influence which memories are retrieved based on internal goals. However, current animal models of memory typically present sensory cues to trigger retrieval and assess retrieval based on action 1-5 . As a result, it is difficult to determine whether measured patterns of neural activity relate to the cue(s), the retrieved memory, or the behavior. We therefore asked whether we could develop a paradigm to isolate retrieval-related neural activity in animals without retrieval cues or the requirement of a behavioral report. To do this, we focused on hippocampal "place cells." These cells primarily emit spiking patterns that represent the animal's current location (local representations), but they can also generate representations of previously visited locations distant from the animal's current location (remote representations) 6-13 . It is not known whether animals can deliberately engage specific remote representations, and if so, whether this engagement would occur during specific brain states. So, we used a closed-loop neurofeedback system to reward expression of remote representations that corresponded to uncued, experimenter-selected locations, and found that rats could increase the prevalence of these specific remote representations over time; thus, demonstrating memory retrieval modulated by internal goals in an animal model. These representations occurred predominately during periods of immobility but outside of hippocampal sharp-wave ripple (SWR) 13-15 events. This paradigm enables future direct studies of memory retrieval mechanisms in the healthy brain and in models of neurological disorders.

Memory for rewards guides retrieval

Rewards paid out for successful retrieval motivate the formation of long-term memory. However, it has been argued that the Motivated Learning Task does not measure reward effects on memory strength but decision-making during retrieval. We report three large-scale online experiments in healthy participants (N = 200, N = 205, N = 187) that inform this debate. In experiment 1, we found that explicit stimulus-reward associations formed during encoding influence response strategies at retrieval. In experiment 2, reward affected memory strength and decision-making strategies. In experiment 3, reward affected decision-making strategies only. These data support a theoretical framework that assumes that promised rewards not only increase memory strength, but additionally lead to the formation of stimulus-reward associations that influence decisions at retrieval.

Disruption of awake sharp-wave ripples does not affect memorization of locations in repeated-acquisition spatial memory tasks

Storing and accessing memories is required to successfully perform day-to-day tasks, for example for engaging in a meaningful conversation. Previous studies in both rodents and primates have correlated hippocampal cellular activity with behavioral expression of memory. A key role has been attributed to awake hippocampal replay - a sequential reactivation of neurons representing a trajectory through space. However, it is unclear if awake replay impacts immediate future behavior, gradually creates and stabilizes long-term memories over a long period of time (hours and longer), or enables the temporary memorization of relevant events at an intermediate time scale (seconds to minutes). In this study, we aimed to address the uncertainty around the timeframe of impact of awake replay by collecting causal evidence from behaving rats. We detected and disrupted sharp wave ripples (SWRs) - signatures of putative replay events - using electrical stimulation of the ventral hippocampal commissure in rats that were trained on three different spatial memory tasks. In each task, rats were required to memorize a new set of locations in each trial or each daily session. Interestingly, the rats performed equally well with or without SWR disruptions. These data suggest that awake SWRs - and potentially replay - does not affect the immediate behavior nor the temporary memorization of relevant events at a short timescale that are required to successfully perform the spatial tasks. Based on these results, we hypothesize that the impact of awake replay on memory and behavior is long-term and cumulative over time.

Prioritizing replay when future goals are unknown

Although hippocampal place cells replay nonlocal trajectories, the computational function of these events remains controversial. One hypothesis, formalized in a prominent reinforcement learning account, holds that replay plans routes to current goals. However, recent puzzling data appear to contradict this perspective by showing that replayed destinations lag current goals. These results may support an alternative hypothesis that replay updates route information to build a "cognitive map." Yet no similar theory exists to formalize this view, and it is unclear how such a map is represented or what role replay plays in computing it. We address these gaps by introducing a theory of replay that learns a map of routes to candidate goals, before reward is available or when its location may change. Our work extends the planning account to capture a general map-building function for replay, reconciling it with data, and revealing an unexpected relationship between the seemingly distinct hypotheses.

Cortical reactivations predict future sensory responses

Many theories of offline memory consolidation posit that the pattern of neurons activated during a salient sensory experience will be faithfully reactivated, thereby stabilizing the pattern1,2. However, sensory-evoked patterns are not stable but, instead, drift across repeated experiences3-6. Here, to investigate the relationship between reactivations and the drift of sensory representations, we imaged the calcium activity of thousands of excitatory neurons in the mouse lateral visual cortex. During the minute after a visual stimulus, we observed transient, stimulus-specific reactivations, often coupled with hippocampal sharp-wave ripples. Stimulus-specific reactivations were abolished by local cortical silencing during the preceding stimulus. Reactivations early in a session systematically differed from the pattern evoked by the previous stimulus-they were more similar to future stimulus response patterns, thereby predicting both within-day and across-day representational drift. In particular, neurons that participated proportionally more or less in early stimulus reactivations than in stimulus response patterns gradually increased or decreased their future stimulus responses, respectively. Indeed, we could accurately predict future changes in stimulus responses and the separation of responses to distinct stimuli using only the rate and content of reactivations. Thus, reactivations may contribute to a gradual drift and separation in sensory cortical response patterns, thereby enhancing sensory discrimination7.

Reward Expectation Reduces Representational Drift in the Hippocampus

Spatial memory in the hippocampus involves dynamic neural patterns that change over days, termed representational drift. While drift may aid memory updating, excessive drift could impede retrieval. Memory retrieval is influenced by reward expectation during encoding, so we hypothesized that diminished reward expectation would exacerbate representational drift. We found that high reward expectation limited drift, with CA1 representations on one day gradually re-emerging over successive trials the following day. Conversely, the absence of reward expectation resulted in increased drift, as the gradual re-emergence of the previous day's representation did not occur. At the single cell level, lowering reward expectation caused an immediate increase in the proportion of place-fields with low trial-to-trial reliability. These place fields were less likely to be reinstated the following day, underlying increased drift in this condition. In conclusion, heightened reward expectation improves memory encoding and retrieval by maintaining reliable place fields that are gradually reinstated across days, thereby minimizing representational drift.

Proactive and reactive construction of memory-based preferences

We are often faced with decisions we have never encountered before, requiring us to infer possible outcomes before making a choice. Computational theories suggest that one way to make these types of decisions is by accessing and linking related experiences stored in memory. Past work has shown that such memory-based preference construction can occur at a number of different timepoints relative to the moment a decision is made. Some studies have found that memories are integrated at the time a decision is faced (reactively) while others found that memory integration happens earlier, when memories are encoded (proactively). Here we offer a resolution to this inconsistency. We demonstrate behavioral and neural evidence for both strategies and for how they tradeoff rationally depending on the associative structure of memory. Using fMRI to decode patterns of brain responses unique to categories of images in memory, we found that proactive memory access is more common and allows more efficient inference. However, participants also use reactive access when choice options are linked to more numerous memory associations. Together, these results indicate that the brain judiciously conducts proactive inference by accessing memories ahead of time in conditions when this strategy is most favorable.

The role of experience in prioritizing hippocampal replay

During sleep, recent memories are replayed by the hippocampus, leading to their consolidation, with a higher priority given to salient experiences. To examine the role of replay in the selective strengthening of memories, we recorded large ensembles of hippocampal place cells while male rats ran repeated spatial trajectories on two linear tracks, differing in either their familiarity or number of laps run. We observed that during sleep, the rate of replay events for a given track increased proportionally with the number of spatial trajectories run by the animal. In contrast, the rate of sleep replay events decreased if the animal was more familiar with the track. Furthermore, we find that the cumulative number of awake replay events occurring during behavior, influenced by both the novelty and duration of an experience, predicts which memories are prioritized for sleep replay, providing a more parsimonious neural correlate for the selective strengthening of memories.

Hippocampal place code plasticity in CA1 requires postsynaptic membrane fusion

Rapid delivery of glutamate receptors to the postsynaptic membrane via vesicle fusion is a central component of synaptic plasticity. However, it is unknown how this process supports specific neural computations during behavior. To bridge this gap, we combined conditional genetic deletion of a component of the postsynaptic membrane fusion machinery, Syntaxin3 (Stx3), in hippocampal CA1 neurons of mice with population in vivo calcium imaging. This approach revealed that Stx3 is necessary for forming the neural dynamics that support novelty processing, spatial reward memory and offline memory consolidation. In contrast, CA1 Stx3 was dispensable for maintaining aspects of the neural code that exist presynaptic to CA1 such as representations of context and space. Thus, manipulating postsynaptic membrane fusion identified computations that specifically require synaptic restructuring via membrane trafficking in CA1 and distinguished them from neural representation that could be inherited from upstream brain regions or learned through other mechanisms.

Dual credit assignment processes underlie dopamine signals in a complex spatial environment

Animals frequently make decisions based on expectations of future reward ("values"). Values are updated by ongoing experience: places and choices that result in reward are assigned greater value. Yet, the specific algorithms used by the brain for such credit assignment remain unclear. We monitored accumbens dopamine as rats foraged for rewards in a complex, changing environment. We observed brief dopamine pulses both at reward receipt (scaling with prediction error) and at novel path opportunities. Dopamine also ramped up as rats ran toward reward ports, in proportion to the value at each location. By examining the evolution of these dopamine place-value signals, we found evidence for two distinct update processes: progressive propagation of value along taken paths, as in temporal difference learning, and inference of value throughout the maze, using internal models. Our results demonstrate that within rich, naturalistic environments dopamine conveys place values that are updated via multiple, complementary learning algorithms.

The role of the hippocampus in the consolidation of emotional memories during sleep

Episodic memory relies on the hippocampus, a heterogeneous brain region with distinct functions. Spatial representations in the dorsal hippocampus (dHPC) are crucial for contextual memory, while the ventral hippocampus (vHPC) is more involved in emotional processing. Here, we review the literature in rodents highlighting the anatomical and functional properties of the hippocampus along its dorsoventral axis that underlie its role in contextual and emotional memory encoding, consolidation, and retrieval. We propose that the coordination between the dorsal and vHPC through theta oscillations during rapid eye movement (REM) sleep, and through sharp-wave ripples during non-REM (NREM) sleep, might facilitate the transfer of contextual information for integration with valence-related processing in other structures of the network. Further investigation into the physiology of the vHPC and its connections with other brain areas is needed to deepen the current understanding of emotional memory consolidation during sleep.

Awake hippocampal synchronous events are incorporated into offline neuronal reactivation

Learning novel experiences reorganizes hippocampal neuronal circuits, represented as coordinated reactivation patterns in post-experience offline states for memory consolidation. This study examines how awake synchronous events during a novel run are related to post-run reactivation patterns. The disruption of awake sharp-wave ripples inhibited experience-induced increases in the contributions of neurons to post-experience synchronous events. Hippocampal place cells that participate more in awake synchronous events are more strongly reactivated during post-experience synchronous events. Awake synchronous neuronal patterns, in cooperation with place-selective firing patterns, determine cell ensembles that undergo pronounced increases and decreases in their correlated spikes. Taken together, awake synchronous events are fundamental for identifying hippocampal neuronal ensembles to be incorporated into synchronous reactivation during subsequent offline states, thereby facilitating memory consolidation.

Offline memory replay in recurrent neuronal networks emerges from constraints on online dynamics

During spatial exploration, neural circuits in the hippocampus store memories of sequences of sensory events encountered in the environment. When sensory information is absent during 'offline' resting periods, brief neuronal population bursts can 'replay' sequences of activity that resemble bouts of sensory experience. These sequences can occur in either forward or reverse order, and can even include spatial trajectories that have not been experienced, but are consistent with the topology of the environment. The neural circuit mechanisms underlying this variable and flexible sequence generation are unknown. Here we demonstrate in a recurrent spiking network model of hippocampal area CA3 that experimental constraints on network dynamics such as population sparsity, stimulus selectivity, rhythmicity and spike rate adaptation, as well as associative synaptic connectivity, enable additional emergent properties, including variable offline memory replay. In an online stimulus-driven state, we observed the emergence of neuronal sequences that swept from representations of past to future stimuli on the timescale of the theta rhythm. In an offline state driven only by noise, the network generated both forward and reverse neuronal sequences, and recapitulated the experimental observation that offline memory replay events tend to include salient locations like the site of a reward. These results demonstrate that biological constraints on the dynamics of recurrent neural circuits are sufficient to enable memories of sensory events stored in the strengths of synaptic connections to be flexibly read out during rest and sleep, which is thought to be important for memory consolidation and planning of future behaviour. KEY POINTS: A recurrent spiking network model of hippocampal area CA3 was optimized to recapitulate experimentally observed network dynamics during simulated spatial exploration. During simulated offline rest, the network exhibited the emergent property of generating flexible forward, reverse and mixed direction memory replay events. Network perturbations and analysis of model diversity and degeneracy identified associative synaptic connectivity and key features of network dynamics as important for offline sequence generation. Network simulations demonstrate that population over-representation of salient positions like the site of reward results in biased memory replay.

Organizing memories for generalization in complementary learning systems

Memorization and generalization are complementary cognitive processes that jointly promote adaptive behavior. For example, animals should memorize safe routes to specific water sources and generalize from these memories to discover environmental features that predict new ones. These functions depend on systems consolidation mechanisms that construct neocortical memory traces from hippocampal precursors, but why systems consolidation only applies to a subset of hippocampal memories is unclear. Here we introduce a new neural network formalization of systems consolidation that reveals an overlooked tension-unregulated neocortical memory transfer can cause overfitting and harm generalization in an unpredictable world. We resolve this tension by postulating that memories only consolidate when it aids generalization. This framework accounts for partial hippocampal-cortical memory transfer and provides a normative principle for reconceptualizing numerous observations in the field. Generalization-optimized systems consolidation thus provides new insight into how adaptive behavior benefits from complementary learning systems specialized for memorization and generalization.

Experience alters hippocampal and cortical network communication via a KIBRA-dependent mechanism

Synaptic plasticity is hypothesized to underlie "replay" of salient experience during hippocampal sharp-wave/ripple (SWR)-based ensemble activity and to facilitate systems-level memory consolidation coordinated by SWRs and cortical sleep spindles. It remains unclear how molecular changes at synapses contribute to experience-induced modification of network function. The synaptic protein KIBRA regulates plasticity and memory. To determine the impact of KIBRA-regulated plasticity on circuit dynamics, we recorded in vivo neural activity from wild-type (WT) mice and littermates lacking KIBRA and examined circuit function before, during, and after novel experience. In WT mice, experience altered population activity and oscillatory dynamics in a manner consistent with incorporation of new information content in replay and enhanced hippocampal-cortical communication. While baseline SWR features were normal in KIBRA conditional knockout (cKO) mice, experience-dependent alterations in SWRs were absent. Furthermore, intra-hippocampal and hippocampal-cortical communication during SWRs was disrupted following KIBRA deletion. These results indicate molecular mechanisms that underlie network-level adaptations to experience.

A deep network-based model of hippocampal memory functions under normal and Alzheimer's disease conditions

We present a deep network-based model of the associative memory functions of the hippocampus. The proposed network architecture has two key modules: (1) an autoencoder module which represents the forward and backward projections of the cortico-hippocampal projections and (2) a module that computes familiarity of the stimulus and implements hill-climbing over the familiarity which represents the dynamics of the loops within the hippocampus. The proposed network is used in two simulation studies. In the first part of the study, the network is used to simulate image pattern completion by autoassociation under normal conditions. In the second part of the study, the proposed network is extended to a heteroassociative memory and is used to simulate picture naming task in normal and Alzheimer's disease (AD) conditions. The network is trained on pictures and names of digits from 0 to 9. The encoder layer of the network is partly damaged to simulate AD conditions. As in case of AD patients, under moderate damage condition, the network recalls superordinate words ("odd" instead of "nine"). Under severe damage conditions, the network shows a null response ("I don't know"). Neurobiological plausibility of the model is extensively discussed.

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.

Hippocampal spatial view cells for memory and navigation, and their underlying connectivity in humans

Hippocampal and parahippocampal gyrus spatial view neurons in primates respond to the spatial location being looked at. The representation is allocentric, in that the responses are to locations "out there" in the world, and are relatively invariant with respect to retinal position, eye position, head direction, and the place where the individual is located. The underlying connectivity in humans is from ventromedial visual cortical regions to the parahippocampal scene area, leading to the theory that spatial view cells are formed by combinations of overlapping feature inputs self-organized based on their closeness in space. Thus, although spatial view cells represent "where" for episodic memory and navigation, they are formed by ventral visual stream feature inputs in the parahippocampal gyrus in what is the parahippocampal scene area. A second "where" driver of spatial view cells are parietal inputs, which it is proposed provide the idiothetic update for spatial view cells, used for memory recall and navigation when the spatial view details are obscured. Inferior temporal object "what" inputs and orbitofrontal cortex reward inputs connect to the human hippocampal system, and in macaques can be associated in the hippocampus with spatial view cell "where" representations to implement episodic memory. Hippocampal spatial view cells also provide a basis for navigation to a series of viewed landmarks, with the orbitofrontal cortex reward inputs to the hippocampus providing the goals for navigation, which can then be implemented by hippocampal connectivity in humans to parietal cortex regions involved in visuomotor actions in space. The presence of foveate vision and the highly developed temporal lobe for object and scene processing in primates including humans provide a basis for hippocampal spatial view cells to be key to understanding episodic memory in the primate and human hippocampus, and the roles of this system in primate including human navigation.

Spatiotemporal Precision of Neuroimaging in Psychiatry

Aberrant patterns of cognition, perception, and behavior seen in psychiatric disorders are thought to be driven by a complex interplay of neural processes that evolve at a rapid temporal scale. Understanding these dynamic processes in vivo in humans has been hampered by a trade-off between spatial and temporal resolutions inherent to current neuroimaging technology. A recent trend in psychiatric research has been the use of high temporal resolution imaging, particularly magnetoencephalography, often in conjunction with sophisticated machine learning decoding techniques. Developments here promise novel insights into the spatiotemporal dynamics of cognitive phenomena, including domains relevant to psychiatric illnesses such as reward and avoidance learning, memory, and planning. This review considers recent advances afforded by exploiting this increased spatiotemporal precision, with specific reference to applications that seek to drive a mechanistic understanding of psychopathology and the realization of preclinical translation.

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.

Enhanced Reactivation of Remapping Place Cells during Aversive Learning

Study of the hippocampal place cell system has greatly enhanced our understanding of memory encoding for distinct places, but how episodic memories for distinct experiences occurring within familiar environments are encoded is less clear. We developed a spatial decision-making task in which male rats learned to navigate a multiarm maze to a goal location for food reward while avoiding maze arms in which aversive stimuli were delivered. Task learning induced partial remapping in CA1 place cells, allowing us to identify both remapping and stable cell populations. Remapping cells were recruited into sharp-wave ripples and associated replay events to a greater extent than stable cells, despite having similar firing rates during navigation of the maze. Our results suggest that recruitment into replay events may be a mechanism to incorporate new contextual information into a previously formed and stabilized spatial representation.SIGNIFICANCE STATEMENT Hippocampal place cells provide a map of space that animals use to navigate. This map can change to reflect changes in the physical properties of the environment in which the animal finds itself, and also in response to nonphysical contextual changes, such as changes in the valence of specific locations within that environment. We show here that cells which change their spatial tuning after a change in context are preferentially recruited into sharp-wave ripple-associated replay events compared with stable nonremapping cells. Thus, our data lend strong support to the hypothesis that replay is a mechanism for the storage of new spatial maps.

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.

Dual credit assignment processes underlie dopamine signals in a complex spatial environment

Dopamine in the nucleus accumbens helps motivate behavior based on expectations of future reward ("values"). These values need to be updated by experience: after receiving reward, the choices that led to reward should be assigned greater value. There are multiple theoretical proposals for how this credit assignment could be achieved, but the specific algorithms that generate updated dopamine signals remain uncertain. We monitored accumbens dopamine as freely behaving rats foraged for rewards in a complex, changing environment. We observed brief pulses of dopamine both when rats received reward (scaling with prediction error), and when they encountered novel path opportunities. Furthermore, dopamine ramped up as rats ran towards reward ports, in proportion to the value at each location. By examining the evolution of these dopamine place-value signals, we found evidence for two distinct update processes: progressive propagation along taken paths, as in temporal-difference learning, and inference of value throughout the maze, using internal models. Our results demonstrate that within rich, naturalistic environments dopamine conveys place values that are updated via multiple, complementary learning algorithms.

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.

Place cells are nonrandomly clustered by field location in CA1 hippocampus

A challenge in both modern and historic neuroscience has been achieving an understanding of neuron circuits, and determining the computational and organizational principles that underlie these circuits. Deeper understanding of the organization of brain circuits and cell types, including in the hippocampus, is required for advances in behavioral and cognitive neuroscience, as well as for understanding principles governing brain development and evolution. In this manuscript, we pioneer a new method to analyze the spatial clustering of active neurons in the hippocampus. We use calcium imaging and a rewarded navigation task to record from 100 s of place cells in the CA1 of freely moving rats. We then use statistical techniques developed for and in widespread use in geographic mapping studies, global Moran's I, and local Moran's I to demonstrate that cells that code for similar spatial locations tend to form small spatial clusters. We present evidence that this clustering is not the result of artifacts from calcium imaging, and show that these clusters are primarily formed by cells that have place fields around previously rewarded locations. We go on to show that, although cells with similar place fields tend to form clusters, there is no obvious topographic mapping of environmental location onto the hippocampus, such as seen in the visual cortex. Insights into hippocampal organization, as in this study, can elucidate mechanisms underlying motivational behaviors, spatial navigation, and memory formation.

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.

Plasticity of synapses and reward circuit function in the genesis and treatment of depression

What changes in brain function cause the debilitating symptoms of depression? Can we use the answers to this question to invent more effective, faster acting antidepressant drug therapies? This review provides an overview and update of the converging human and preclinical evidence supporting the hypothesis that changes in the function of excitatory synapses impair the function of the circuits they are embedded in to give rise to the pathological changes in mood, hedonic state, and thought processes that characterize depression. The review also highlights complementary human and preclinical findings that classical and novel antidepressant drugs relieve the symptoms of depression by restoring the functions of these same synapses and circuits. These findings offer a useful path forward for designing better antidepressant compounds.

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.

Offline neuronal activity and synaptic plasticity during sleep and memory consolidation

After initial formation during learning, memories are further processed in the brain during subsequent days for long-term consolidation, with sleep playing a key role in this process. Studies have shown that neuronal activity patterns during the awake period are repeated in the hippocampus during sleep, which may coordinate brain-wide reactivation leading to memory consolidation. Consistently, perturbation of this activity blocks the formation of long-term memory. This 'replay' of activity during sleep likely triggers plastic changes in synaptic transmission, a cellular substrate of memory, in multiple brain regions, which likely plays a critical role in long-term memory. Two forms of synaptic plasticity, potentiation and depression of synaptic transmission, are induced in parallel during sleep and is termed "offline synaptic plasticity", as opposed to the "online synaptic plasticity" that occurs immediately following a memory event.

Fast network oscillations during non-REM sleep support memory consolidation

The neocortex is disconnected from the outside world during sleep, which has been hypothesized to be relevant for synaptic reorganization involved in memory consolidation. Fast network oscillations, such as hippocampal sharp-wave ripples, cortical ripples, and amygdalar high-frequency oscillations, are prominent during non-REM sleep. Although these oscillations are thought to be generated by local circuit mechanisms, their occurrence rates and amplitudes are modulated by thalamocortical spindles and neocortical slow oscillations during non-REM sleep, suggesting that fast network oscillations and slower oscillations cooperatively work to facilitate memory consolidation. This review discusses the recent progress in understanding the generation, coordination, and functional roles of fast network oscillations. Further, it outlines how fast network oscillations in distinct brain regions synergistically support memory consolidation and retrieval by hosting cross-regional coactivation of memory-related neuronal ensembles.

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'.

The Role of Intra-Amygdaloid Neurotensin and Dopamine Interaction in Spatial Learning and Memory

Neurotransmitter and neuromodulator neurotensin (NT) has been proved to facilitate spatial and passive avoidance learning after microinjected into the rat central nucleus of amygdala (CeA). These previous studies of our laboratory also revealed that neurotensin-1 receptor (NTS1) is involved in the mentioned actions of NT. Extensive literature confirms the interaction between neurotensinergic and dopaminergic systems, and our research group also suppose that the mesolimbic dopaminergic system (MLDS) is involved in the spatial learning and memory-facilitating effect of NT in the CeA. In the present work, NT and dopamine (DA) interaction has been examined in the Morris water maze and passive avoidance tests. Rats received 100 ng NT, 5 µg dopamine D2 receptor antagonist sulpiride in itself, sulpiride as a pretreatment before NT or vehicle solution into the CeA. NT microinjection significantly decreased target-finding latency in the Morris water maze test and significantly increased entrance latency in the passive avoidance test, as was expected based on our previous findings. The DA D2 receptor antagonist pretreatment was able to inhibit both effects of NT. The results confirm the facilitatory effect of NT on spatial learning and memory and let us conclude that these actions can be exerted via the DA D2 receptors.

Adult newborn granule cells confer emotional state-dependent adaptability in memory retrieval

Achieving optimal behavior requires animals to flexibly retrieve prior knowledge. Here, we show that adult newborn granule cells (anbGCs) mediate emotional state-dependent adaptability of memory retrieval. We find that acute social reward (aSR) enhances memory retrieval by increasing the reactivation of engram cells, while acute social stress (aSS) weakens retrieval and reduces the reactivation. Such bidirectional regulation relies on the activation of distinct populations of anbGCs by aSR and aSS, triggering opposing modifications of dDG activity, which is sufficient to regulate and predict the performance of memory retrieval. Concordantly, in emotional disorder models, aSR-dependent memory adaptability is impaired, while the effect of aSS remains intact. Together, our data revealed that anbGCs mediate adaptability of memory retrieval, allowing animals to flexibly retrieve memory according to the current emotional state, and suggested the essential roles of anbGCs in translating emotional information to the regulation of memory expression.

Reward expectation extinction restructures and degrades CA1 spatial maps through loss of a dopaminergic reward proximity signal

Hippocampal place cells support reward-related spatial memories by forming a cognitive map that over-represents reward locations. The strength of these memories is modulated by the extent of reward expectation during encoding. However, the circuit mechanisms underlying this modulation are unclear. Here we find that when reward expectation is extinguished in mice, they remain engaged with their environment, yet place cell over-representation of rewards vanishes, place field remapping throughout the environment increases, and place field trial-to-trial reliability decreases. Interestingly, Ventral Tegmental Area (VTA) dopaminergic axons in CA1 exhibit a ramping reward-proximity signal that depends on reward expectation and inhibiting VTA dopaminergic neurons largely replicates the effects of extinguishing reward expectation. We conclude that changing reward expectation restructures CA1 cognitive maps and determines map reliability by modulating the dopaminergic VTA-CA1 reward-proximity signal. Thus, internal states of high reward expectation enhance encoding of spatial memories by reinforcing hippocampal cognitive maps associated with reward.

Internally Triggered Experiences of Hedonic Valence in Nonhuman Animals: Cognitive and Welfare Considerations

Do any nonhuman animals have hedonically valenced experiences not directly caused by stimuli in their current environment? Do they, like us humans, experience anticipated or previously experienced pains and pleasures as respectively painful and pleasurable? We review evidence from comparative neuroscience about hippocampus-dependent simulation in relation to this question. Hippocampal sharp-wave ripples and theta oscillations have been found to instantiate previous and anticipated experiences. These hippocampal activations coordinate with neural reward and fear centers as well as sensory and cortical areas in ways that are associated with conscious episodic mental imagery in humans. Moreover, such hippocampal “re- and preplay” has been found to contribute to instrumental decision making, the learning of value representations, and the delay of rewards in rats. The functional and structural features of hippocampal simulation are highly conserved across mammals. This evidence makes it reasonable to assume that internally triggered experiences of hedonic valence (IHVs) are pervasive across (at least) all mammals. This conclusion has important welfare implications. Most prominently, IHVs act as a kind of “welfare multiplier” through which the welfare impacts of any given experience of pain or pleasure are increased through each future retrieval. However, IHVs also have practical implications for welfare assessment and cause prioritization.

Postsynaptic burst reactivation of hippocampal neurons enables associative plasticity of temporally discontiguous inputs

A fundamental unresolved problem in neuroscience is how the brain associates in memory events that are separated in time. Here, we propose that reactivation-induced synaptic plasticity can solve this problem. Previously, we reported that the reinforcement signal dopamine converts hippocampal spike timing-dependent depression into potentiation during continued synaptic activity (Brzosko et al., 2015). Here, we report that postsynaptic bursts in the presence of dopamine produce input-specific LTP in mouse hippocampal synapses 10 min after they were primed with coincident pre- and post-synaptic activity (post-before-pre pairing; Δt = -20 ms). This priming activity induces synaptic depression and sets an NMDA receptor-dependent silent eligibility trace which, through the cAMP-PKA cascade, is rapidly converted into protein synthesis-dependent synaptic potentiation, mediated by a signaling pathway distinct from that of conventional LTP. This synaptic learning rule was incorporated into a computational model, and we found that it adds specificity to reinforcement learning by controlling memory allocation and enabling both 'instructive' and 'supervised' reinforcement learning. We predicted that this mechanism would make reactivated neurons activate more strongly and carry more spatial information than non-reactivated cells, which was confirmed in freely moving mice performing a reward-based navigation task.

A model of bi-directional interactions between complementary learning systems for memory consolidation of sequential experiences

The standard theory of memory consolidation posits a dual-store memory system: a fast-learning fast-decaying hippocampus that transfers memories to slow-learning long-term cortical storage. Hippocampal lesions interrupt this transfer, so recent memories are more likely to be lost than more remote memories. Existing models of memory consolidation that simulate this temporally graded retrograde amnesia operate only on static patterns or unitary variables as memories and study only one-way interaction from the hippocampus to the cortex. However, the mechanisms underlying the consolidation of episodes, which are sequential in nature and comprise multiple events, are not well-understood. The representation of learning for sequential experiences in the cortical-hippocampal network as a self-consistent dynamical system is not sufficiently addressed in prior models. Further, there is evidence for a bi-directional interaction between the two memory systems during offline periods, whereby the reactivation of waking neural patterns originating in the cortex triggers time-compressed sequential replays in the hippocampus, which in turn drive the consolidation of the pertinent sequence in the cortex. We have developed a computational model of memory encoding, consolidation, and recall for storing temporal sequences that explores the dynamics of this bi-directional interaction and time-compressed replays in four simulation experiments, providing novel insights into whether hippocampal learning needs to be suppressed for stable memory consolidation and into how new and old memories compete for limited replay opportunities during offline periods. The salience of experienced events, based on factors such as recency and frequency of use, is shown to have considerable impact on memory consolidation because it biases the relative probability that a particular event will be cued in the cortex during offline periods. In the presence of hippocampal learning during sleep, our model predicts that the fast-forgetting hippocampus can continually refresh the memory traces of a given episodic sequence if there are no competing experiences to be replayed.

Learning from inhibition: Functional roles of hippocampal CA1 inhibition in spatial learning and memory

Hippocampal inhibitory interneurons exert a powerful influence on learning and memory. Inhibitory interneurons are known to play a major role in many diseases that affect memory, and to strongly influence brain functions required for memory-related tasks. While previous studies involving genetic, optogenetic, and pharmacological manipulations have shown that hippocampal interneurons play essential roles in spatial and episodic learning and memory, exactly how interneurons affect local circuit computations during spatial navigation is not well understood. Given the significant anatomical, morphological, and functional heterogeneity in hippocampal interneurons, one may suspect cell-type specific roles in circuit computations. Here, we review emerging evidence of CA1 hippocampal interneurons' role in local circuit computations that support spatial learning and memory and discuss open questions about CA1 interneurons in spatial learning.

A Brain-Inspired Model of Hippocampal Spatial Cognition Based on a Memory-Replay Mechanism

Since the hippocampus plays an important role in memory and spatial cognition, the study of spatial computation models inspired by the hippocampus has attracted much attention. This study relies mainly on reward signals for learning environments and planning paths. As reward signals in a complex or large-scale environment attenuate sharply, the spatial cognition and path planning performance of such models will decrease clearly as a result. Aiming to solve this problem, we present a brain-inspired mechanism, a Memory-Replay Mechanism, that is inspired by the reactivation function of place cells in the hippocampus. We classify the path memory according to the reward information and find the overlapping place cells in different categories of path memory to segment and reconstruct the memory to form a “virtual path”, replaying the memory by associating the reward information. We conducted a series of navigation experiments in a simple environment called a Morris water maze (MWM) and in a complex environment, and we compared our model with a reinforcement learning model and other brain-inspired models. The experimental results show that under the same conditions, our model has a higher rate of environmental exploration and more stable signal transmission, and the average reward obtained under stable conditions was 14.12% higher than RL with random-experience replay. Our model also shows good performance in complex maze environments where signals are easily attenuated. Moreover, the performance of our model at bifurcations is consistent with neurophysiological studies.

Contextual Expectations Shape Cortical Reinstatement of Sensory Representations

When making a turn at a familiar intersection, we know what items and landmarks will come into view. These perceptual expectations, or predictions, come from our knowledge of the context; however, it is unclear how memory and perceptual systems interact to support the prediction and reactivation of sensory details in cortex. To address this, human participants learned the spatial layout of animals positioned in a cross maze. During fMRI, participants of both sexes navigated between animals to reach a target, and in the process saw a predictable sequence of five animal images. Critically, to isolate activity patterns related to item predictions, rather than bottom-up inputs, one-fourth of trials ended early, with a blank screen presented instead. Using multivariate pattern similarity analysis, we reveal that activity patterns in early visual cortex, posterior medial regions, and the posterior hippocampus showed greater similarity when seeing the same item compared with different items. Further, item effects in posterior hippocampus were specific to the sequence context. Critically, activity patterns associated with seeing an item in visual cortex and posterior medial cortex, were also related to activity patterns when an item was expected, but omitted, suggesting sequence predictions were reinstated in these regions. Finally, multivariate connectivity showed that patterns in the posterior hippocampus at one position in the sequence were related to patterns in early visual cortex and posterior medial cortex at a later position. Together, our results support the idea that hippocampal representations facilitate sensory processing by modulating visual cortical activity in anticipation of expected items.SIGNIFICANCE STATEMENT Our visual world is a series of connected events, where we can predict what we might see next based on our recent past. Understanding the neural circuitry and mechanisms of the perceptual and memory systems that support these expectations is fundamental to revealing how we perceive and act in our world. Using brain imaging, we studied what happens when we expect to see specific visual items, and how such expectations relate to top-down memory signals. We find both visual and memory systems reflect item predictions, and moreover, we show that hippocampal activity supports predictions of future expected items. This demonstrates that the hippocampus acts to predict upcoming items, and reinstates such predictions in cortex.

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.

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.

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.