Novel Causal Relations between Neuronal Networks due to Synchronization

Sentao Wang; Hongbiao Chen; Yang Zhan

doi:10.1093/cercor/bhab219

Novel Causal Relations between Neuronal Networks due to Synchronization

Cereb Cortex. 2022 Jan 10;32(2):429-438. doi: 10.1093/cercor/bhab219.

Authors

Sentao Wang¹, Hongbiao Chen¹, Yang Zhan¹

Affiliation

¹ Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Key Laboratory of Brain Connectome and Manipulation, the Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Key Laboratory of Translational Research for Brain Diseases, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences; Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China.

PMID: 34274974
DOI: 10.1093/cercor/bhab219

Abstract

In the process of information transmission, information is thought to be transmitted from the networks that are activated by the input to the networks that are silent or nonactivated. Here, via numerical simulation of a 3-network motif, we show that the silent neuronal network when interconnected with other 2 networks can exert much stronger causal influences on the other networks. Such an unexpected causal relationship results from high degree of synchronization in this network. The predominant party is consistently the network whose noise is smaller when the noise level in each network is considered. Our results can shed lights on how the internal network dynamics can affect the information flow of interconnected neuronal networks.

Keywords: causality analysis; functional connectivity; information flow; neural networks; synchronous activities.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Computer Simulation
Models, Neurological
Nerve Net* / physiology
Neurons* / physiology