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

Détails

ID Serval
serval:BIB_8BB422B88B31
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
The effects of physiologically plausible connectivity structure on local and global dynamics in large scale brain models.
Périodique
Journal of Neuroscience Methods
Auteur(s)
Knock S.A., McIntosh A.R., Sporns O., Kötter R., Hagmann P., Jirsa V.K.
ISSN
1872-678X (Electronic)
ISSN-L
0165-0270
Statut éditorial
Publié
Date de publication
2009
Volume
183
Numéro
1
Pages
86-94
Langue
anglais
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov'tPublication Status: ppublish
Résumé
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.
Mots-clé
Animals, Brain/anatomy & histology, Brain/physiology, Brain Mapping, Computer Graphics, Computer Simulation, Humans, Models, Neurological, Nerve Net/physiology, Neural Pathways/physiology, Nonlinear Dynamics, Principal Component Analysis, Time Factors
Pubmed
Web of science
Création de la notice
29/06/2012 9:03
Dernière modification de la notice
03/03/2018 19:12
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