Skip to content
Open access

Network topology determines neuronal phase-of-firing codes

Jul 2026 · bioRxiv · 0 citations · 30 references
Biology

TL;DR

It is shown that recurrent connectivity does not merely permit phase-of-firing codes but actively determines which patterns the network can hold onto, and that the symmetries of the wiring determines which of those patterns the network can stably hold.

Abstract

Brain rhythms organize neural activity in time. When a shared oscillation is broadcast across a population of neurons, the phase at which the neurons fire with respect to the oscillation can itself carry information, a strategy the brain appears to use for navigation, memory, and sensory perception. In such a phase-of-firing code, information is conveyed not by how rapidly a neuron fires but by when it fires relative to the phase of the ongoing rhythm. Models that implement such phase-of-firing codes consider the neurons as independent. How such codes arise in cortical and hippocampal circuits, where neurons are densely interconnected rather than independent, remains unclear. Here we show that recurrent connectivity does not merely permit phase-of-firing codes but actively determines which patterns the network can hold onto. Using networks of model neurons wired in a manner determined by the constraints of a Sudoku puzzle, we find that the network supports an enormous repertoire of distinct rhythmic firing patterns, each corresponding to a valid Sudoku solution and selectable by brief targeted inputs against a common background oscillation. Some patterns persist after the input is removed while others dissolve. We show that a factor deciding this selectivity is network symmetry. Patterns that respect the symmetries of the wiring are stable, while those that break them are not, and small perturbations can switch the network between stable patterns. Adjusting synaptic weights to remove asymmetry stabilizes patterns that were previously unstable, giving the network a tunable memory. More broadly, our results suggest that a common oscillatory drive, targeted biases to the neurons, and recurrent network structure, act together as complementary control variables. The oscillation sets up a temporal scaffold, the biases select spatiotemporal patterns, and the connectivity determines the stability of the chosen patterns. Tuning these complementary variables can predictably and flexibly reshape the repertoire of activity a circuit expresses. Significance Statement Many brain regions generate rhythmic activity, and the precise moment at which individual neurons fire within each rhythm carries information that the brain can harness to encode memory, perception and location as an animal navigates its environment. In such a phase-of-firing code, information is conveyed not by how rapidly a neuron fires but by when it fires relative to the phase of the ongoing network rhythm. Existing theories of how phase-of-firing codes arise have modeled neurons as independent, leaving open how such codes emerge in the densely interconnected circuits of cortex and hippocampus. Using model networks wired to reflect the constraints of the Sudoku puzzle, we show that recurrent connectivity supports a vast repertoire of distinct rhythmic firing patterns, and that the symmetries of the wiring determines which of those patterns the network can stably hold. This identifies network symmetry as a general principle relating circuit architecture to temporal coding.

Read PDF

Similar papers

Open access Oct 2026

Hippocampal theta states are linked to reconfiguration of population activity with respect to behavioural context

Neural activity reflects both external stimuli and the brain’s internal state, which shapes how information is processed and perceived. For example, in phase-precession in the hippocampus, the phase of theta oscillations affects the firing of single neurons (place cells) and its relation to the external world. Here,...

Laura Masaracchia, Pablo Oyarzo, Felipe Fredes et al. · 0 citations
Preprint Sep 2026

Hierarchical emergence of network bursting in a four-cell central pattern generator model

How can a neural circuit rhythmically burst when none of its constituent neurons can endogenously do so? We address this question through a bottom-up reconstruction of a 4-cell neural circuit modeled after the swim central pattern generator (CPG) of the sea slug \textit{Dendronotus iris}. We first map the intrinsic reg...

K. Pusuluri, Hui-Wen Wu, Andrey L. Shilnikov · 0 citations
Open access Sep 2026

Increased firing rates monotonically expand neuronal coding bandwidth

Sensory information is often processed by populations of neurons that vary with respect to their levels of spiking activity. It appears plausible that neurons that fire more often are capable of following faster changes in the input signal than those with lower firing rates. In this study, we test this intuitive assump...

Alexander Wendt, Kolja Klett, J. Benda et al. · 0 citations
Open access Sep 2026

Hierarchical feature binding in a spiking neural network model of the primate ventral visual pathway

Simulation of a spiking neural network that closely aligns with the structural organisation of the primate ventral visual pathway, incorporating bottom-up, top-down, and lateral synaptic connections provides evidence for binding by polychrony as a feasible solution to the feature binding problem, and characterise the m...

Brian Gardner, Patrick T. McCarthy, J. Chrol-Cannon et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.