A Resonance Model for Spontaneous Cortical Activity

TL;DR

This paper introduces a resonance model based on STDP principles that accurately predicts resting brain functional connectivity and explains dynamic coupling fluctuations and negative correlations observed in spontaneous cortical activity.

Contribution

The model uniquely combines wave equations with STDP to describe spontaneous cortical activity and demonstrates superior predictive performance over existing models using large HCP data.

Findings

Accurately predicts resting-state networks.

Shows spontaneous coupling fluctuates at low frequency.

Accounts for emergence of negative functional correlations.

Abstract

How human brain function emerges from structure has intrigued researchers for decades and numerous models have been put forward, yet none of them yields a close structure-function relation. Here we present a resonance model based on neuronal spike timing dependent plasticity (STDP) principle to describe the spontaneous cortical activity by incorporating the dynamic interactions between neuronal populations into a wave equation, which is able to accurately predict the resting brain functional connectivity (FC), including the resting-state networks. Besides, the proposed model provides strong theoretical and experimental evidences that the spontaneous dynamic coupling between brain regions fluctuates with a low frequency. Crucially, it is able to account for how the negative functional correlations emerge during resonance. We test the model with a large cohort of subjects (1038) from the Human Connectome Project (HCP) S1200 release in both time and frequency domain, which exhibits superior performance to existing eigen-decomposition models.