Prefrontal cortical ripples mediate top-down suppression of hippocampal reactivation during sleep memory consolidation.

Consolidation of initially encoded hippocampal representations in the neocortex through reactivation is crucial for long-term memory formation and is facilitated by the coordination of hippocampal sharp-wave ripples (SWRs) with cortical slow and spindle oscillations during non-REM sleep. Recent evidence suggests that high-frequency cortical ripples can also coordinate with hippocampal SWRs in support of consolidation; however, the contribution of cortical ripples to reactivation remains unclear. We used high-density, continuous recordings in the hippocampus (area CA1) and prefrontal cortex (PFC) over the course of spatial learning and show that independent PFC ripples dissociated from SWRs are prevalent in NREM sleep and predominantly suppress hippocampal activity. PFC ripples paradoxically mediate top-down suppression of hippocampal reactivation rather than coordination, and this suppression is stronger for assemblies that are reactivated during coordinated CA1-PFC ripples for consolidation of recent experiences. Further, we show non-canonical, serial coordination of independent cortical ripples with slow and spindle oscillations, which are known signatures of memory consolidation. These results establish a role for prefrontal cortical ripples in top-down regulation of behaviorally relevant hippocampal representations during consolidation.

Intrinsic dynamics of randomly clustered networks generate place fields and preplay of novel environments.

During both sleep and awake immobility, hippocampal place cells reactivate time-compressed versions of sequences representing recently experienced trajectories in a phenomenon known as replay. Intriguingly, spontaneous sequences can also correspond to forthcoming trajectories in novel environments experienced later, in a phenomenon known as preplay. Here, we present a model showing that sequences of spikes correlated with the place fields underlying spatial trajectories in both previously experienced and future novel environments can arise spontaneously in neural circuits with random, clustered connectivity rather than pre-configured spatial maps. Moreover, the realistic place fields themselves arise in the circuit from minimal, landmark-based inputs. We find that preplay quality depends on the network's balance of cluster isolation and overlap, with optimal preplay occurring in small-world regimes of high clustering yet short path lengths. We validate the results of our model by applying the same place field and preplay analyses to previously published rat hippocampal place cell data. Our results show that clustered recurrent connectivity can generate spontaneous preplay and immediate replay of novel environments. These findings support a framework whereby novel sensory experiences become associated with preexisting "pluripotent" internal neural activity patterns.

Protocol for geometric transformation of cognitive maps for generalization across hippocampal-prefrontal circuits.

Memory generalization is the ability to abstract knowledge from prior experiences and is critical for flexible behavior in novel situations. Here, we describe a protocol for simultaneous recording of hippocampal (area CA1)-prefrontal cortical neural ensembles in Long-Evans rats during task generalization across two distinct environments. We describe steps for building and assembling experimental apparatuses, animal preparation and surgery, and performing experiments. We then detail procedures for histology, data processing, and assessing population geometry using Uniform Manifold Approximation and Projection. For complete details on the use and execution of this protocol, please refer to Tang et al. (2023).1.

Geometric transformation of cognitive maps for generalization across hippocampal-prefrontal circuits.

The ability to abstract information to guide decisions during navigation across changing environments is essential for adaptation and requires the integrity of the hippocampal-prefrontal circuitry. The hippocampus encodes navigational information in a cognitive map, but it remains unclear how cognitive maps are transformed across hippocampal-prefrontal circuits to support abstraction and generalization. Here, we simultaneously record hippocampal-prefrontal ensembles as rats generalize navigational rules across distinct environments. We find that, whereas hippocampal representational maps maintain specificity of separate environments, prefrontal maps generalize across environments. Furthermore, while both maps are structured within a neural manifold of population activity, they have distinct representational geometries. Prefrontal geometry enables abstraction of rule-informative variables, a representational format that generalizes to novel conditions of existing variable classes. Hippocampal geometry lacks such abstraction. Together, these findings elucidate how cognitive maps are structured into distinct geometric representations to support abstraction and generalization while maintaining memory specificity.

Cortical ripples mediate top-down suppression of hippocampal reactivation during sleep memory consolidation.

Consolidation of initially encoded hippocampal representations in the neocortex through reactivation is crucial for long-term memory formation, and is facilitated by the coordination of hippocampal sharp-wave ripples (SWRs) with cortical oscillations during non-REM sleep. However, the contribution of high-frequency cortical ripples to consolidation is still unclear. We used continuous recordings in the hippocampus and prefrontal cortex (PFC) over the course of spatial learning and show that independent PFC ripples, when dissociated from SWRs, predominantly suppress hippocampal activity in non-REM sleep. PFC ripples paradoxically mediate top-down suppression of hippocampal reactivation, which is inversely related to reactivation strength during coordinated CA1-PFC ripples. Further, we show non-canonical, serial coordination of ripples with cortical slow and spindle oscillations. These results establish a role for cortical ripples in regulating consolidation.

Rhythmic coordination and ensemble dynamics in the hippocampal-prefrontal network during odor-place associative memory and decision making.

Memory-guided decision making involves long-range coordination across sensory and cognitive brain networks, with key roles for the hippocampus and prefrontal cortex (PFC). In order to investigate the mechanisms of such coordination, we monitored activity in hippocampus (CA1), PFC, and olfactory bulb (OB) in rats performing an odor-place associative memory guided decision task on a T-maze. During odor sampling, the beta (20-30 Hz) and respiratory (7-8 Hz) rhythms (RR) were prominent across the three regions, with beta and RR coherence between all pairs of regions enhanced during the odor-cued decision making period. Beta phase modulation of phase-locked CA1 and PFC neurons during this period was linked to accurate decisions, with a key role of CA1 interneurons in temporal coordination. Single neurons and ensembles in both CA1 and PFC encoded and predicted animals' upcoming choices, with different cell ensembles engaged during decision-making and decision execution on the maze. Our findings indicate that rhythmic coordination within the hippocampal-prefrontal-olfactory bulb network supports utilization of odor cues for memory-guided decision making.

Integrating Statistical and Machine Learning Approaches for Neural Classification.

Neurons can code for multiple variables simultaneously and neuroscientists are often interested in classifying neurons based on their receptive field properties. Statistical models provide powerful tools for determining the factors influencing neural spiking activity and classifying individual neurons. However, as neural recording technologies have advanced to produce simultaneous spiking data from massive populations, classical statistical methods often lack the computational efficiency required to handle such data. Machine learning (ML) approaches are known for enabling efficient large scale data analyses; however, they typically require massive training sets with balanced data, along with accurate labels to fit well. Additionally, model assessment and interpretation are often more challenging for ML than for classical statistical methods. To address these challenges, we develop an integrated framework, combining statistical modeling and machine learning approaches to identify the coding properties of neurons from large populations. In order to demonstrate this framework, we apply these methods to data from a population of neurons recorded from rat hippocampus to characterize the distribution of spatial receptive fields in this region.

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.

Efficient spline regression for neural spiking data.

Point process generalized linear models (GLMs) provide a powerful tool for characterizing the coding properties of neural populations. Spline basis functions are often used in point process GLMs, when the relationship between the spiking and driving signals are nonlinear, but common choices for the structure of these spline bases often lead to loss of statistical power and numerical instability when the signals that influence spiking are bounded above or below. In particular, history dependent spike train models often suffer these issues at times immediately following a previous spike. This can make inferences related to refractoriness and bursting activity more challenging. Here, we propose a modified set of spline basis functions that assumes a flat derivative at the endpoints and show that this limits the uncertainty and numerical issues associated with cardinal splines. We illustrate the application of this modified basis to the problem of simultaneously estimating the place field and history dependent properties of a set of neurons from the CA1 region of rat hippocampus, and compare it with the other commonly used basis functions. We have made code available in MATLAB to implement spike train regression using these modified basis functions.

Multiple time-scales of decision-making in the hippocampus and prefrontal cortex.

The prefrontal cortex and hippocampus are crucial for memory-guided decision-making. Neural activity in the hippocampus exhibits place-cell sequences at multiple timescales, including slow behavioral sequences (~seconds) and fast theta sequences (~100-200 ms) within theta oscillation cycles. How prefrontal ensembles interact with hippocampal sequences to support decision-making is unclear. Here, we examined simultaneous hippocampal and prefrontal ensemble activity in rats during learning of a spatial working-memory decision task. We found clear theta sequences in prefrontal cortex, nested within its behavioral sequences. In both regions, behavioral sequences maintained representations of current choices during navigation. In contrast, hippocampal theta sequences encoded alternatives for deliberation and were coordinated with prefrontal theta sequences that predicted upcoming choices. During error trials, these representations were preserved to guide ongoing behavior, whereas replay sequences during inter-trial periods were impaired prior to navigation. These results establish cooperative interaction between hippocampal and prefrontal sequences at multiple timescales for memory-guided decision-making.

Refinement and Reactivation of a Taste-Responsive Hippocampal Network.

Animals need to remember the locations of nourishing and toxic food sources for survival, a fact that necessitates a mechanism for associating taste experiences with particular places. We have previously identified such responses within hippocampal place cells [1], the activity of which is thought to aid memory-guided behavior by forming a mental map of an animal's environment that can be reshaped through experience [2-7]. It remains unknown, however, whether taste responsiveness is intrinsic to a subset of place cells or emerges as a result of experience that reorganizes spatial maps. Here, we recorded from neurons in the dorsal CA1 region of rats running for palatable tastes delivered via intra-oral cannulae at specific locations on a linear track. We identified a subset of taste-responsive cells that, even prior to taste exposure, had larger place fields than non-taste-responsive cells overlapping with stimulus delivery zones. Taste-responsive cells' place fields then contracted as a result of taste experience, leading to a stronger representation of stimulus delivery zones on the track. Taste-responsive units exhibited increased sharp-wave ripple co-activation during the taste delivery session and subsequent rest periods, which correlated with the degree of place field contraction. Our results reveal that novel taste experience evokes responses within a preconfigured network of taste-responsive hippocampal place cells with large fields, whose spatial representations are refined by sensory experience to signal areas of behavioral salience. This represents a possible mechanism by which animals identify and remember locations where ecologically relevant stimuli are found within their environment.

The role of replay and theta sequences in mediating hippocampal-prefrontal interactions for memory and cognition.

Sequential activity is seen in the hippocampus during multiple network patterns, prominently as replay activity during both awake and sleep sharp-wave ripples (SWRs), and as theta sequences during active exploration. Although various mnemonic and cognitive functions have been ascribed to these hippocampal sequences, evidence for these proposed functions remains primarily phenomenological. Here, we briefly review current knowledge about replay events and theta sequences in spatial memory tasks. We reason that in order to gain a mechanistic and causal understanding of how these patterns influence memory and cognitive processing, it is important to consider how these sequences influence activity in other regions, and in particular, the prefrontal cortex, which is crucial for memory-guided behavior. For spatial memory tasks, we posit that hippocampal-prefrontal interactions mediated by replay and theta sequences play complementary and overlapping roles at different stages in learning, supporting memory encoding and retrieval, deliberative decision making, planning, and guiding future actions. This framework offers testable predictions for future physiology and closed-loop feedback inactivation experiments for specifically targeting hippocampal sequences as well as coordinated prefrontal activity in different network states, with the potential to reveal their causal roles in memory-guided behavior.

Dynamics of Awake Hippocampal-Prefrontal Replay for Spatial Learning and Memory-Guided Decision Making.

Spatial learning requires remembering and choosing paths to goals. Hippocampal place cells replay spatial paths during immobility in reverse and forward order, offering a potential mechanism. However, how replay supports both goal-directed learning and memory-guided decision making is unclear. We therefore continuously tracked awake replay in the same hippocampal-prefrontal ensembles throughout learning of a spatial alternation task. We found that, during pauses between behavioral trajectories, reverse and forward hippocampal replay supports an internal cognitive search of available past and future possibilities and exhibits opposing learning gradients for prediction of past and future behavioral paths, respectively. Coordinated hippocampal-prefrontal replay distinguished correct past and future paths from alternative choices, suggesting a role in recall of past paths to guide planning of future decisions for spatial working memory. Our findings reveal a learning shift from hippocampal reverse-replay-based retrospective evaluation to forward-replay-based prospective planning, with prefrontal readout of memory-guided paths for learning and decision making.

Coherent Coding of Spatial Position Mediated by Theta Oscillations in the Hippocampus and Prefrontal Cortex.

Interactions between the hippocampus (area CA1) and prefrontal cortex (PFC) are crucial for memory-guided behavior. Theta oscillations (∼8 Hz) underlie a key physiological mechanism for mediating these coordinated interactions, and theta oscillatory coherence and phase-locked spiking in the two regions have been shown to be important for spatial memory. Hippocampal place-cell activity associated with theta oscillations encodes spatial position during behavior, and theta phase-associated spiking is known to further mediate a temporal code for space within CA1 place fields. Although prefrontal neurons are prominently phase-locked to hippocampal theta oscillations in spatial memory tasks, whether and how theta oscillations mediate processing of spatial information across these networks remains unclear. Here, we addressed these questions using simultaneous recordings of dorsal CA1-PFC ensembles and population decoding analyses in male rats performing a continuous spatial working memory task known to require hippocampal-prefrontal interactions. We found that in addition to CA1, population activity in PFC can also encode the animal's current spatial position on a theta-cycle timescale during memory-guided behavior. Coding of spatial position was coherent for CA1 and PFC ensembles, exhibiting correlated position representations within theta cycles. In addition, incorporating theta-phase information during decoding to account for theta-phase associated spiking resulted in a significant improvement in the accuracy of prefrontal spatial representations, similar to concurrent CA1 representations. These findings indicate a theta-oscillation-mediated mechanism of temporal coordination for shared processing and communication of spatial information across the two networks during spatial memory-guided behavior.SIGNIFICANCE STATEMENT Theta oscillation- (∼8 Hz) mediated interactions between the hippocampus and prefrontal cortex are known to be important for spatial memory. Hippocampal place-cell activity associated with theta oscillations underlies a rate and temporal code for spatial position, but it is not known whether these oscillations mediate simultaneous coding of spatial information in hippocampal-prefrontal networks. Here, we found that population activity in prefrontal cortex encodes animals' current position coherently with hippocampal populations on a theta-cycle timescale. Further we found that theta phase-associated spiking significantly improves prefrontal coding of spatial position, in parallel with hippocampal coding. Our findings establish that theta oscillations mediate a temporal coordination mechanism for coherent coding of spatial position in hippocampal-prefrontal networks during memory-guided behavior.

Interaction of Taste and Place Coding in the Hippocampus.

An animal's survival depends on finding food and the memory of food and contexts are often linked. Given that the hippocampus is required for spatial and contextual memory, it is reasonable to expect related coding of space and food stimuli in hippocampal neurons. However, relatively little is known about how the hippocampus responds to tastes, the most central sensory property of food. In this study, we examined the taste-evoked responses and spatial firing properties of single units in the dorsal CA1 hippocampal region as male rats received a battery of taste stimuli differing in both chemical composition and palatability within a specific spatial context. We identified a subset of hippocampal neurons that responded to tastes, some of which were place cells. These taste and place responses had a distinct interaction: taste-responsive cells tended to have less spatially specific firing fields and place cells only responded to tastes delivered inside their place field. Like neurons in the amygdala and lateral hypothalamus, hippocampal neurons discriminated between tastes predominantly on the basis of palatability, with taste selectivity emerging concurrently with palatability-relatedness; these responses did not reflect movement or arousal. However, hippocampal taste responses emerged several hundred milliseconds later than responses in other parts of the taste system, suggesting that the hippocampus does not influence real-time taste decisions, instead associating the hedonic value of tastes with a particular context. This incorporation of taste responses into existing hippocampal maps could be one way that animals use past experience to locate food sources.SIGNIFICANCE STATEMENT Finding food is essential for animals' survival and taste and context memory are often linked. Although hippocampal responses to space and contexts have been well characterized, little is known about how the hippocampus responds to tastes. Here, we identified a subset of hippocampal neurons that discriminated between tastes based on palatability. Cells with stronger taste responses typically had weaker spatial responses and taste responses were confined to place cells' firing fields. Hippocampal taste responses emerged later than in other parts of the taste system, suggesting that the hippocampus does not influence taste decisions, but rather associates the hedonic value of tastes consumed within a particular context. This could be one way that animals use past experience to locate food sources.

Sharp-wave ripples as a signature of hippocampal-prefrontal reactivation for memory during sleep and waking states.

It is widely believed that memories that are encoded and retrieved during waking behavior are consolidated during sleep. Recent studies on the interactions between the hippocampus and the prefrontal cortex have greatly advanced our understanding of the physiological bases of these memory processes. Although hippocampal-prefrontal network activity differs in many aspects during waking and sleep states, here we review evidence that hippocampal sharp-wave ripples (SWRs) emerge as a common neurophysiological pattern in both states, facilitating communication between these two regions via coordinated reactivation of stored memory information. We further consider whether sleep and awake reactivation mediate similar memory processes or have different mnemonic functions, and the mechanistic role of this cross-regional dialogue in learning and memory. Finally, we provide an integrated view of how these two forms of reactivation might work together to support spatial learning and memory.

Conducting the Neural Symphony of Memory Replay.

Hippocampal sharp-wave ripple oscillations and sequence replay events are important for memory. Ramirez-Villegas et al. present a model that dissects cellular mechanisms of SWR generation in the CA3-CA1 circuit, and explains the network features of slow-gamma coordination and sequence replay.

Disruption of dorsal hippocampal - prefrontal interactions using chemogenetic inactivation impairs spatial learning.

The hippocampus (HPC) and prefrontal cortex (PFC) are both necessary for learning and memory-guided behavior. Multiple direct and indirect anatomical projections connect the two regions, and HPC - PFC functional interactions are mediated by diverse physiological network patterns, thought to sub serve various memory processes. Disconnection experiments using contralateral inactivation approaches have established the role of direct, ipsilateral projections from ventral and intermediate HPC (vHPC and iHPC) to PFC in spatial memory. However, numerous studies have also prominently implicated physiological interactions between dorsal HPC (dHPC) and PFC regions in spatial memory tasks, and recent reports have identified direct dHPC - PFC connections. Whether dHPC - PFC interactions are necessary for spatial learning and memory has yet to be tested. Here, we used a chemogenetic inactivation approach using virally-expressed DREADDs (designer receptors exclusively activated by designer drugs) in rats to investigate the role of dHPC - PFC interactions in learning a hippocampal - dependent spatial alternation task. We implemented a rapid learning paradigm for a continuous W-track spatial alternation task comprising two components: an outbound, working memory component, and an inbound, spatial reference memory component. We investigated the effect of contralateral inactivation of dHPC and PFC on learning this task as compared with naïve and vehicle injection controls, as well as ipsilateral inactivation of the same regions. Contralateral dHPC - PFC inactivation selectively led to a significant impairment in learning the spatial working memory task compared to control groups, but did not impair learning of the spatial reference memory task. Ipsilateral inactivation animals showed similar learning rates as animals in the control groups. In a separate experiment, we confirmed that bilateral inactivation of PFC also leads to an impairment in learning the spatial working memory task. Our results thus demonstrate that dHPC - PFC interactions are necessary for spatial alternation learning in novel tasks. In addition, they provide crucial evidence to support the view that physiological interactions between dHPC and PFC play a key role in spatial learning and memory.

Hippocampal-Prefrontal Reactivation during Learning Is Stronger in Awake Compared with Sleep States.

Hippocampal sharp-wave ripple (SWR) events occur during both behavior (awake SWRs) and slow-wave sleep (sleep SWRs). Awake and sleep SWRs both contribute to spatial learning and memory, thought to be mediated by the coordinated reactivation of behavioral experiences in hippocampal-cortical circuits seen during SWRs. Current hypotheses suggest that reactivation contributes to memory consolidation processes, but whether awake and sleep reactivation are suited to play similar or different roles remains unclear. Here we addressed that issue by examining the structure of hippocampal (area CA1) and prefrontal (PFC) activity recorded across behavior and sleep stages in male rats learning a spatial alternation task. We found a striking state difference: prefrontal modulation during awake and sleep SWRs was surprisingly distinct, with differing patterns of excitation and inhibition. CA1-PFC synchronization was stronger during awake SWRs, and spatial reactivation, measured using both pairwise and ensemble measures, was more structured for awake SWRs compared with post-task sleep SWRs. Stronger awake reactivation was observed despite the absence of coordination between network oscillations, namely hippocampal SWRs and cortical delta and spindle oscillations, which is prevalent during sleep. Finally, awake CA1-PFC reactivation was enhanced most prominently during initial learning in a novel environment, suggesting a key role in early learning. Our results demonstrate significant differences in awake and sleep reactivation in the hippocampal-prefrontal network. These findings suggest that awake SWRs support accurate memory storage and memory-guided behavior, whereas sleep SWR reactivation is better suited to support integration of memories across experiences during consolidation.SIGNIFICANCE STATEMENT Hippocampal sharp-wave ripples (SWRs) occur both in the awake state during behavior and in the sleep state after behavior. Awake and sleep SWRs are associated with memory reactivation and are important for learning, but their specific memory functions remain unclear. Here, we found profound differences in hippocampal-cortical reactivation during awake and sleep SWRs, with key implications for their roles in memory. Awake reactivation is a higher-fidelity representation of behavioral experiences, and is enhanced during early learning, without requiring coordination of network oscillations that is seen during sleep. Our findings suggest that awake reactivation is ideally suited to support initial memory formation, retrieval and planning, whereas sleep reactivation may play a broader role in integrating memories across experiences during consolidation.

Interplay between Hippocampal Sharp-Wave-Ripple Events and Vicarious Trial and Error Behaviors in Decision Making.

Current theories posit that memories encoded during experiences are subsequently consolidated into longer-term storage. Hippocampal sharp-wave-ripple (SWR) events have been linked to this consolidation process during sleep, but SWRs also occur during awake immobility, where their role remains unclear. We report that awake SWR rates at the reward site are inversely related to the prevalence of vicarious trial and error (VTE) behaviors, thought to be involved in deliberation processes. SWR rates were diminished immediately after VTE behaviors and an increase in the rate of SWR events at the reward site predicted a decrease in subsequent VTE behaviors at the choice point. Furthermore, SWR disruptions increased VTE behaviors. These results suggest an inverse relationship between SWRs and VTE behaviors and suggest that awake SWRs and associated planning and memory consolidation mechanisms are engaged specifically in the context of higher levels of behavioral certainty.