Frequency-Resolved Functional Connectivity: Role of Delay and the Strength of Connections.

Abolfazl Ziaeemehr,Alireza Valizadeh

doi:10.3389/fncir.2021.608655

Abstract

The brain functional network extracted from the BOLD signals reveals the correlated activity of the different brain regions, which is hypothesized to underlie the integration of the information across functionally specialized areas. Functional networks are not static and change over time and in different brain states, enabling the nervous system to engage and disengage different local areas in specific tasks on demand. Due to the low temporal resolution, however, BOLD signals do not allow the exploration of spectral properties of the brain dynamics over different frequency bands which are known to be important in cognitive processes. Recent studies using imaging tools with a high temporal resolution has made it possible to explore the correlation between the regions at multiple frequency bands. These studies introduce the frequency as a new dimension over which the functional networks change, enabling brain networks to transmit multiplex of information at any time. In this computational study, we explore the functional connectivity at different frequency ranges and highlight the role of the distance between the nodes in their correlation. We run the generalized Kuramoto model with delayed interactions on top of the brain's connectome and show that how the transmission delay and the strength of the connections, affect the correlation between the pair of nodes over different frequency bands.

Highlights

A very prominent feature of the brain is the ability to dynamically changing the routes for communication between the brain regions when undertaking different cognitive and executive functions (Honey et al, 2007; Friston, 2011; Valdes-Sosa et al, 2011; Park et al, 2018)
This is revealed by extensive studies on the pattern of statistical inter-relations between the activities of different brain regions at different brain states based on BOLD signals (Chang and Glover, 2010; Allen et al, 2014; Calhoun et al, 2014; Wang et al, 2016; Park et al, 2018)
We aim to study the properties of the functional network of the brain at different frequency bands through simulation of a simple model of the human brain network

Summary

Introduction

A very prominent feature of the brain is the ability to dynamically changing the routes for communication between the brain regions when undertaking different cognitive and executive functions (Honey et al, 2007; Friston, 2011; Valdes-Sosa et al, 2011; Park et al, 2018). This is revealed by extensive studies on the pattern of statistical inter-relations between the activities of different brain regions at different brain states based on BOLD signals (Chang and Glover, 2010; Allen et al, 2014; Calhoun et al, 2014; Wang et al, 2016; Park et al, 2018). It has been shown that, due to environmental demands and changes in the state of the brain, regions of the brain can engage in functional modules and detach from others, allowing the brain to switch between multiple tasks over time (Gonzalez-Castillo et al, 2015; Hansen et al, 2015).

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