The effects of physiologically plausible connectivity structure on local and global dynamics in large scale brain models

Functionally relevant large scale brain dynamics operates within the framework imposed by anatomical connectivity and time delays due to finite transmission speeds. To gain insight on the reliability and comparability of large scale brain network simulations, we investigate the effects of variations...

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Bibliographic Details
Published in:Journal of neuroscience methods 2009-09, Vol.183 (1), p.86-94
Main Authors: Knock, S.A., McIntosh, A.R., Sporns, O., Kötter, R., Hagmann, P., Jirsa, V.K.
Format: Article
Language:English
Subjects:
Animals
Brain - anatomy & histology
Brain - physiology
Brain Mapping
CoCoMac
Computer Graphics
Computer Simulation
Connectivity
Dynamics
Humans
Models, Neurological
Nerve Net - physiology
Network
Neural Pathways - physiology
Nonlinear Dynamics
Principal Component Analysis
Time Factors
Tractography
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Summary:Functionally relevant large scale brain dynamics operates within the framework imposed by anatomical connectivity and time delays due to finite transmission speeds. To gain insight on the reliability and comparability of large scale brain network simulations, we investigate the effects of variations in the anatomical connectivity. Two different sets of detailed global connectivity structures are explored, the first extracted from the CoCoMac database and rescaled to the spatial extent of the human brain, the second derived from white-matter tractography applied to diffusion spectrum imaging (DSI) for a human subject. We use the combination of graph theoretical measures of the connection matrices and numerical simulations to explicate the importance of both connectivity strength and delays in shaping dynamic behaviour. Our results demonstrate that the brain dynamics derived from the CoCoMac database are more complex and biologically more realistic than the one based on the DSI database. We propose that the reason for this difference is the absence of directed weights in the DSI connectivity matrix.
ISSN:0165-0270
1872-678X
DOI:10.1016/j.jneumeth.2009.07.007