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  Transcranial direct current stimulation changes resting state functional connectivity: A large-scale brain network modeling study

Kunze, T., Hunold, A., Haueisen, J., Jirsa, V., & Spiegler, A. (2016). Transcranial direct current stimulation changes resting state functional connectivity: A large-scale brain network modeling study. NeuroImage, 140(10), 174-187. doi:10.1016/j.neuroimage.2016.02.015.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-002C-EBE2-7 Version Permalink: http://hdl.handle.net/21.11116/0000-0004-E258-A
Genre: Journal Article

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 Creators:
Kunze, Tim1, 2, Author              
Hunold, Alexander1, Author
Haueisen, Jens1, 3, Author
Jirsa, Viktor4, 5, 6, Author
Spiegler, Andreas4, 5, Author
Affiliations:
1Institute for Biomedical Engineering and Informatics, TU Ilmenau, Germany, ou_persistent22              
2Methods and Development Group MEG and EEG - Cortical Networks and Cognitive Functions, MPI for Human Cognitive and Brain Sciences, Max Planck Society, Leipzig, DE, ou_2205650              
3Department of Neurology, Biomagnetic Center, Jena University Hospital, Germany, ou_persistent22              
4Institut de Neurosciences des Systèmes, Aix-Marseille Université Faculté de Médecine, France, ou_persistent22              
5Institut national de la santé et de la recherche médicale, Marseille, France, ou_persistent22              
6Centre National de la Recherche Scientifique, Paris, France, ou_persistent22              

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Free keywords: Large-scale brain network modeling; Transcranial direct current stimulation; Noninvasive brain stimulation; Brain network dynamics; Neural mass modeling; Resting state dynamics
 Abstract: 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.

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Language(s): eng - English
 Dates: 2016-01-262015-06-102016-02-082016-02-132016-10-15
 Publication Status: Published in print
 Pages: -
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 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.1016/j.neuroimage.2016.02.015
PMID: 26883068
Other: Epub 2016
 Degree: -

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Title: NeuroImage
Source Genre: Journal
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Publ. Info: Orlando, FL : Academic Press
Pages: - Volume / Issue: 140 (10) Sequence Number: - Start / End Page: 174 - 187 Identifier: ISSN: 1053-8119
CoNE: https://pure.mpg.de/cone/journals/resource/954922650166