Replay, the sequential reactivation of a neuronal ensemble, is thought to play a central role in the hippocampus during the consolidation of a recent experience into a long-term memory. Following a contextual change (e.g. entering a novel environment), hippocampal place cells typically modulate their in-field firing rate and shift the position of their place field, providing a rate and place representation for the behavioral episode, respectively. However, replay has been largely defined by only the latter- based on the fidelity of sequential activity across neighboring place fields. Here we show that dorsal CA1 place cells in rats can modulate their firing rate between the replay of two different contexts, mirroring the same pattern of rate modulation observed during behavior. This context-driven rate modulation within replay events was experience-dependent, observable during both behavioral episodes and throughout the subsequent rest period, but not prior to experience. Furthermore, we demonstrate that both the temporal order and firing rate of place cells can independently be used to decode contextual information within a replay event, revealing the existence of two separable but complementary neural representations available for memory consolidation processes.

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

During sleep, recent memories are consolidated, whereby behavioral episodes first encoded by the hippocampus get transformed into long-term memories. However, the brain cannot consolidate every experience and much like the triage of an emergency room, the hippocampus is hypothesized to give precedence to more important memories first, and deprioritize or even skip over less relevant memories if needed. Here we examine two factors that are postulated to influence this memory triage process- 1) repetition, arising from the number of times a behavioral episode is repeated, increasing the priority to consolidate and 2) familiarity, resulting from previously experiencing a similar behavioral episode, in turn decreasing the need for further consolidation. Recording from large ensembles of hippocampal place cells while rats ran repeated spatial trajectories, and afterwards during periods of sleep, we examined how these two factors influenced replay, a hypothesized mechanism of consolidation involving the offline spontaneous reactivation of memory traces. 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 rat. In contrast to this, the rate of sleep replay events decreased if the rat was more familiar with the track, arising from previously running on the same track before its most recent sleep session. Furthermore, we find that the cumulative number of awake replay events that occur during behavior, influenced by both the novelty and duration of an experience, predicts which memories are prioritized for sleep replay, and provides a more parsimonious mechanism for the selectively strengthening and triaging of memories.

During rest and sleep, memory traces replay in the brain. The dialogue between brain regions during replay is thought to stabilize labile memory traces for long-term storage. However, because replay is an internally-driven, spontaneous phenomenon, it does not have a ground truth - an external reference that can validate whether a memory has truly been replayed. Instead, replay detection is based on the similarity between the sequential neural activity comprising the replay event and the corresponding template of neural activity generated during active locomotion. If the statistical likelihood of observing such a match by chance is sufficiently low, the candidate replay event is inferred to be replaying that specific memory. However, without the ability to evaluate whether replay detection methods are successfully detecting true events and correctly rejecting non-events, the evaluation and comparison of different replay methods is challenging. To circumvent this problem, we present a new framework for evaluating replay, tested using hippocampal neural recordings from rats exploring two novel linear tracks. Using this two-track paradigm, our framework selects replay events based on their temporal fidelity (sequence-based detection), and applies a cross-validation using each event's trajectory discriminability, where cross-track sequenceless decoding is used to quantify whether the track replaying is also the most likely track being reactivated.

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