# Dynamical modulation of hippocampal replay through firing rate adaptation

**Authors:** Zilong Ji, Tianhao Chu, Xingsi Dong, Changmin Yu, Daniel Bush, Neil Burgess, Si Wu

PMC · DOI: 10.1038/s41467-025-68042-3 · Nature Communications · 2026-01-20

## TL;DR

The study shows how changes in neural firing rates can explain different patterns of hippocampal replay during rest and sleep.

## Contribution

The paper introduces a computational model linking firing-rate adaptation to diverse hippocampal replay dynamics.

## Key findings

- More diffusive replay sequences correlate with longer theta sequences, indicating stronger adaptation.
- Increased neural activity with adaptation reduces step size in decoded replay trajectories.
- The model aligns with prior findings on how behavioral states influence replay diffusivity.

## Abstract

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.

The neural mechanisms underlying the diversity of hippocampal replay dynamics remain unclear. Here, using computational modelling, the authors show that modulation of firing-rate adaptation accounts for distinct replay modes and their relationships to behavioral state and oscillatory activity.

## Full-text entities

- **Genes:** Ca2 (carbonic anhydrase 2) [NCBI Gene 54231] {aka Car2}, Ca3 (carbonic anhydrase 3) [NCBI Gene 54232] {aka Car3}, hc-6 [NCBI Gene 100302894], Ca1 (carbonic anhydrase 1) [NCBI Gene 310218] {aka CA-I, Car1}
- **Diseases:** FRA (MESH:D018489), depression (MESH:D003866), REM (MESH:D020187), CAN (MESH:D014202)
- **Chemicals:** Au (MESH:D006046), calcium (MESH:D002118), Ach (MESH:D000109), CAN (-), sodium (MESH:D012964), Ar (MESH:D001128)
- **Species:** Rattus norvegicus (brown rat, species) [taxon 10116]
- **Mutations:** U with V

## Full text

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## Figures

6 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12868804/full.md

## References

9 references — full list in the complete paper: https://tomesphere.com/paper/PMC12868804/full.md

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Source: https://tomesphere.com/paper/PMC12868804