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On Shapley Ratings in Brain Networks

We consider the problem of computing the influence of a neuronal structure in a brain network. Abraham et al. (2006) computed this influence by using the Shapley value of a coalitional game corresponding to a directed network as a rating. Kötter et al. (2007) applied this rating to large-scale brain...

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Autores principales: Musegaas, Marieke, Dietzenbacher, Bas J., Borm, Peter E. M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5126048/
https://www.ncbi.nlm.nih.gov/pubmed/27965566
http://dx.doi.org/10.3389/fninf.2016.00051
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author Musegaas, Marieke
Dietzenbacher, Bas J.
Borm, Peter E. M.
author_facet Musegaas, Marieke
Dietzenbacher, Bas J.
Borm, Peter E. M.
author_sort Musegaas, Marieke
collection PubMed
description We consider the problem of computing the influence of a neuronal structure in a brain network. Abraham et al. (2006) computed this influence by using the Shapley value of a coalitional game corresponding to a directed network as a rating. Kötter et al. (2007) applied this rating to large-scale brain networks, in particular to the macaque visual cortex and the macaque prefrontal cortex. Our aim is to improve upon the above technique by measuring the importance of subgroups of neuronal structures in a different way. This new modeling technique not only leads to a more intuitive coalitional game, but also allows for specifying the relative influence of neuronal structures and a direct extension to a setting with missing information on the existence of certain connections.
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spelling pubmed-51260482016-12-13 On Shapley Ratings in Brain Networks Musegaas, Marieke Dietzenbacher, Bas J. Borm, Peter E. M. Front Neuroinform Neuroscience We consider the problem of computing the influence of a neuronal structure in a brain network. Abraham et al. (2006) computed this influence by using the Shapley value of a coalitional game corresponding to a directed network as a rating. Kötter et al. (2007) applied this rating to large-scale brain networks, in particular to the macaque visual cortex and the macaque prefrontal cortex. Our aim is to improve upon the above technique by measuring the importance of subgroups of neuronal structures in a different way. This new modeling technique not only leads to a more intuitive coalitional game, but also allows for specifying the relative influence of neuronal structures and a direct extension to a setting with missing information on the existence of certain connections. Frontiers Media S.A. 2016-11-29 /pmc/articles/PMC5126048/ /pubmed/27965566 http://dx.doi.org/10.3389/fninf.2016.00051 Text en Copyright © 2016 Musegaas, Dietzenbacher and Borm. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Musegaas, Marieke
Dietzenbacher, Bas J.
Borm, Peter E. M.
On Shapley Ratings in Brain Networks
title On Shapley Ratings in Brain Networks
title_full On Shapley Ratings in Brain Networks
title_fullStr On Shapley Ratings in Brain Networks
title_full_unstemmed On Shapley Ratings in Brain Networks
title_short On Shapley Ratings in Brain Networks
title_sort on shapley ratings in brain networks
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5126048/
https://www.ncbi.nlm.nih.gov/pubmed/27965566
http://dx.doi.org/10.3389/fninf.2016.00051
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