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A macaque connectome for large-scale network simulations in TheVirtualBrain

Models of large-scale brain networks that are informed by the underlying anatomical connectivity contribute to our understanding of the mapping between the structure of the brain and its dynamical function. Connectome-based modelling is a promising approach to a more comprehensive understanding of b...

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Detalles Bibliográficos
Autores principales: Shen, Kelly, Bezgin, Gleb, Schirner, Michael, Ritter, Petra, Everling, Stefan, McIntosh, Anthony R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6637142/
https://www.ncbi.nlm.nih.gov/pubmed/31316116
http://dx.doi.org/10.1038/s41597-019-0129-z
Descripción
Sumario:Models of large-scale brain networks that are informed by the underlying anatomical connectivity contribute to our understanding of the mapping between the structure of the brain and its dynamical function. Connectome-based modelling is a promising approach to a more comprehensive understanding of brain function across spatial and temporal scales, but it must be constrained by multi-scale empirical data from animal models. Here we describe the construction of a macaque (Macaca mulatta and Macaca fascicularis) connectome for whole-cortex simulations in TheVirtualBrain, an open-source simulation platform. We take advantage of available axonal tract-tracing datasets and enhance the existing connectome data using diffusion-based tractography in macaques. We illustrate the utility of the connectome as an extension of TheVirtualBrain by simulating resting-state BOLD-fMRI data and fitting it to empirical resting-state data.