# Hippocampal phase precession may be generated by chimera dynamics

## TL;DR

This paper explores how hippocampal phase precession might arise from chimera dynamics, using computational models to show how synchronized and asynchronous neuron activity could explain this phenomenon.

## Contribution

The paper proposes a novel computational model linking hippocampal phase precession to chimera dynamics in neural oscillators.

## Key findings

- Changing oscillator frequencies in Kuramoto networks can match the theta and phase precession frequency ratios.
- Faster firing oscillators exhibit theta-sequence-like behavior and phase precession.
- Spiking neuron networks trained to produce chimera states show phase precession in subsets of neurons.

## Abstract

The 8 Hz theta rhythm observed in hippocampal local field potentials of animals can be regarded as a “clock” that regulates the timing of spikes. While different interneuron sub-types synchronously phase lock to different phases for every theta cycle, the phase of pyramidal neurons' spikes asynchronously vary in each theta cycle, depending on the animal's position. On the other hand, pyramidal neurons tend to fire slightly faster than the theta oscillation in what is termed hippocampal phase precession. Chimera states are specific solutions to dynamical systems where synchrony and asynchrony coexist, similar to coexistence of phase precessing and phase locked cells during the hippocampal theta oscillation. Here, we test the hypothesis that the hippocampal phase precession emerges from chimera dynamics with computational modeling. We utilized multiple network topologies and sizes of Kuramoto oscillator networks that are known to collectively display chimera dynamics. We found that by changing the oscillators' intrinsic frequency, the frequency ratio between the synchronized and unsynchronized oscillators can match the frequency ratio between the hippocampal theta oscillation (≈ 8 Hz) and phase precessing pyramidal neurons (≈ 9 Hz). The faster firing population of oscillators also displays theta-sequence-like behavior and phase precession. Finally, we trained networks of spiking integrate-and-fire neurons to output a chimera state by using the Kuramoto-chimera system as a dynamical supervisor. We found that the firing times of subsets of individual neurons display phase precession.