Transcranial direct current stimulation (tDCS) is a noninvasive technique for affecting brain dynamics with promising application in the clinical therapy of neurological and psychiatric disorders such as Parkinson's disease, Alzheimer's disease, depression, and schizophrenia. Resting state dynamics increasingly play a role in the assessment of connectivity-based pathologies such as Alzheimer's and schizophrenia. We systematically applied tDCS in a large-scale network model of 74 cerebral areas, investigating the spatiotemporal changes in dynamic states as a function of structural connectivity changes. Structural connectivity was defined by the human connectome. The main findings of this study are fourfold: Firstly, we found a tDCS-induced increase in functional connectivity among cerebral areas and among EEG sensors, where the latter reproduced empirical findings of other researchers. Secondly, the analysis of the network dynamics suggested synchronization to be the main mechanism of the observed effects. Thirdly, we found that tDCS sharpens and shifts the frequency distribution of scalp EEG sensors slightly towards higher frequencies. Fourthly, new dynamic states emerged through interacting areas in the network compared to the dynamics of an isolated area. The findings propose synchronization as a key mechanism underlying the changes in the spatiotemporal pattern formation due to tDCS. Our work supports the notion that noninvasive brain stimulation is able to bias brain dynamics by affecting the competitive interplay of functional subnetworks.
Keywords: Brain network dynamics; Large-scale brain network modeling; Neural mass modeling; Noninvasive brain stimulation; Resting state dynamics; Transcranial direct current stimulation.
Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.