Modeling the interplay between regional heterogeneity and critical dynamics underlying brain functional networks

Neural Netw. 2024 Dec 25:184:107100. doi: 10.1016/j.neunet.2024.107100. Online ahead of print.

Abstract

The human brain exhibits heterogeneity across regions and network connectivity patterns; However, how these heterogeneities contribute to whole-brain network functions and cognitive capacities remains unclear. In this study, we focus on the regional heterogeneity reflected in local dynamics and study how it contributes to the emergence of functional connectivity patterns, network ignition dynamics of the empirical brains. We find that the level of synchrony among voxelwise neural activities measured from the fMRI data is significantly correlated with the transcriptional variations in excitatory and inhibitory receptor gene expression. Consequently, we construct heterogeneous whole-brain network models with nodal excitability calibrated by the synchronization measure of regional dynamics. We demonstrate that as the extent of heterogeneity increases, the models operating around the critical point between order and disorder generate simulated functional connectivity networks increasingly similar to empirical resting-state or working memory task-evoked function connectivity networks. Furthermore, the heterogeneous models can predict individual differences in resting-state and task-evoked reconfiguration of the functional connectivity, as well as the comparative causal effect of empirical brain networks-that is, how the dynamics of one brain region affect whole-brain synchronization. Overall, this work demonstrates the viability of using regional heterogeneous functional signals to improve the performance of the whole-brain models, and illustrates how regional heterogeneity in human brains interplays with structural connections and critical dynamics to contribute to the emergence of functional connectivity networks.

Keywords: Criticality; Personalized brain modelling; Regional heterogeneity; Whole-brain models; synchronization.