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  The Virtual Brain integrates computational modeling and multimodal neuroimaging

Ritter, P., Schirner, M., McIntosh, A. R., & Jirsa, V. K. (2013). The Virtual Brain integrates computational modeling and multimodal neuroimaging. Brain Connectivity, 3(2), 121-145. doi:10.1089/brain.2012.0120.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-000E-B8E7-E Version Permalink: http://hdl.handle.net/21.11116/0000-0003-ACB2-2
Genre: Journal Article

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 Creators:
Ritter, Petra1, 2, 3, 4, 5, Author              
Schirner, Michael2, 4, Author
McIntosh, Anthony R.6, Author
Jirsa, Viktor K.7, Author
Affiliations:
1Minerva Research Group Brain Modes, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_751546              
2Bernstein Focus: State Dependencies of Learning, Berlin, Germany, ou_persistent22              
3Bernstein Center for Computational Neuroscience, Berlin, Germany, ou_persistent22              
4Department of Neurology, Charité University Medicine Berlin, Germany, ou_persistent22              
5Berlin School of Mind and Brain, Humboldt University Berlin, Germany, ou_persistent22              
6Rotman Research Institute, University of Toronto, ON, Canada, ou_persistent22              
7Institut de Neurosciences des Systèmes, Aix-Marseille Université Faculté de Médecine, France, ou_persistent22              

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Free keywords: brain connectivity; brain model; brain networks; modeling; space–time structure
 Abstract: Brain function is thought to emerge from the interactions among neuronal populations. Apart from traditional efforts to reproduce brain dynamics from the micro- to macroscopic scales, complementary approaches develop phenomenological models of lower complexity. Such macroscopic models typically generate only a few selected—ideally functionally relevant—aspects of the brain dynamics. Importantly, they often allow an understanding of the underlying mechanisms beyond computational reproduction. Adding detail to these models will widen their ability to reproduce a broader range of dynamic features of the brain. For instance, such models allow for the exploration of consequences of focal and distributed pathological changes in the system, enabling us to identify and develop approaches to counteract those unfavorable processes. Toward this end, The Virtual Brain (TVB) (www.thevirtualbrain.org), a neuroinformatics platform with a brain simulator that incorporates a range of neuronal models and dynamics at its core, has been developed. This integrated framework allows the model-based simulation, analysis, and inference of neurophysiological mechanisms over several brain scales that underlie the generation of macroscopic neuroimaging signals. In this article, we describe how TVB works, and we present the first proof of concept.

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Language(s): eng - English
 Dates: 2013-02-262013-04-232013-04-23
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1089/brain.2012.0120
PMID: 23442172
PMC: PMC3696923
 Degree: -

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Title: Brain Connectivity
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Mary Ann Liebert
Pages: - Volume / Issue: 3 (2) Sequence Number: - Start / End Page: 121 - 145 Identifier: Other: 2158-0022
CoNE: https://pure.mpg.de/cone/journals/resource/2158-0022