Dynamical modulation of hippocampal replay through firing rate adaptation

During periods of immobility and sleep, the hippocampus generates diverse self-sustaining sequences of "replay" activity, which exhibit stationary, diffusive, and super-diffusive dynamical patterns. However, the neural mechanisms underlying this diversity in hippocampal sequential dynamics remain largely unknown. Here, we propose a unifying mechanism by showing that modulation of firing-rate adaptation strength within a continuous attractor model of place cells gives rise to these distinct forms of replay. Our model accounts for empirical data and yields several testable predictions. First, more diffusive replay sequences should positively correlate with longer theta sequences, both reflecting stronger adaptation. Second, increased neural activity combined with firing-rate adaptation should reduce the step size of decoded trajectories during replay. Third, the framework is consistent with previous work showing that replay diffusivity can vary within an animal across behavioural states that may influence adaptation (such as wake and sleep). Together, these results suggest that the diverse replay dynamics observed in the hippocampus can be understood through a simple yet powerful neural mechanism, providing insight into the computational role of replay in hippocampal-dependent cognition and its relationship to other electrophysiological phenomena.