SUMMARY Intelligent behavior requires acquiring and following rules. Rules define how our behavior should fit different situations. To understand its neural mechanisms, we simultaneously recorded from multiple electrodes in dorsolateral prefrontal cortex (PFC) while monkeys switched between two rules (respond to color versus orientation). We found evidence that oscillatory synchronization of local field potentials (LFPs) formed neural ensembles representing the rules: there were rule-specific increases in synchrony at “beta” (19–40 Hz) frequencies between electrodes. In addition, individual PFC neurons synchronized to the LFP ensemble corresponding to the current rule (color versus orientation). Furthermore, the ensemble encoding the behaviorally dominant orientation rule showed increased “alpha” (6–16 Hz) synchrony when preparing to apply the alternative (weaker) color rule. This suggests that beta-frequency synchrony selects the relevant rule ensemble, while alpha-frequency synchrony deselects a stronger, but currently irrelevant, ensemble. Synchrony may act to dynamically shape task-relevant neural ensembles out of larger, overlapping circuits.

Executing memory-guided behavior requires storage of information about experience and later recall of that information to inform choices. Awake hippocampal replay, when hippocampal neural ensembles briefly reactivate a representation related to prior experience, has been proposed to critically contribute to these memory-related processes. However, it remains unclear whether awake replay contributes to memory function by promoting the storage of past experiences, facilitating planning based on evaluation of those experiences, or both. We designed a dynamic spatial task that promotes replay before a memory-based choice and assessed how the content of replay related to past and future behavior. We found that replay content was decoupled from subsequent choice and instead was enriched for representations of previously rewarded locations and places that had not been visited recently, indicating a role in memory storage rather than in directly guiding subsequent behavior.

Representations related to past experiences play a critical role in memory and decision-making processes. The rat hippocampus expresses these types of representations during sharp-wave ripple (SWR) events, and previous work identified a minority of SWRs that contain ‘replay’ of spatial trajectories at ∼20x the movement speed of the animal. Efforts to understand replay typically make multiple assumptions about which events to examine and what sorts of representations constitute replay. We therefore lack a clear understanding of both the prevalence and the range of representational dynamics associated with replay. Here, we develop a state space model that uses a combination of movement dynamics of different speeds to capture the spatial content and time evolution of replay during SWRs. Using this model, we find that the large majority of replay events contain spatially coherent, interpretable content. Furthermore, many events progress at real-world, rather than accelerated, movement speeds, consistent with actual experiences.

Representations of past and possible future experiences play a critical role in memory and decision-making processes. The hippocampus expresses these types of representations during sharp-wave ripple (SWR) events, and previous work identified a minority of SWRs that contain "replay" of spatial trajectories at ~20x real-world speeds. Efforts to understand replay typically make multiple assumptions about which events to examine and what sorts of representations constitute replay. We therefore lack a clear understanding of both the prevalence and the range of representational dynamics associated with replay. Here we develop a state space model that uses a combination of movement dynamics of different speeds to capture the spatial content and time evolution of replay during SWRs. Using this model, we find that the large majority of replay events contain spatially coherent, interpretable content. Furthermore, most events progress at real-world, rather than accelerated, movement speeds, consistent with actual experiences.