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Gray Matter Axonal Connectivity Maps

Structural brain connectivity is generally assessed through methods that rely on pre-defined regions of interest (e.g., Brodmann’s areas), thus preventing analyses that are largely free from a priori anatomical assumptions. Here, we introduce a novel and practical technique to evaluate a voxel-based...

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Detalles Bibliográficos
Autores principales: Bonilha, Leonardo, Gleichgerrcht, Ezequiel, Nesland, Travis, Rorden, Chris, Fridriksson, Julius
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4351616/
https://www.ncbi.nlm.nih.gov/pubmed/25798111
http://dx.doi.org/10.3389/fpsyt.2015.00035
Descripción
Sumario:Structural brain connectivity is generally assessed through methods that rely on pre-defined regions of interest (e.g., Brodmann’s areas), thus preventing analyses that are largely free from a priori anatomical assumptions. Here, we introduce a novel and practical technique to evaluate a voxel-based measure of axonal projections connecting gray matter tissue [gray matter axonal connectivity map (GMAC)]. GMACs are compatible with voxel-based statistical approaches, and can be used to assess whole brain, scale-free, gray matter connectivity. In this study, we demonstrate how whole-brain GMACs can be generated from conventional structural connectome methodology, describing each step in detail, as well as providing tools to allow for the calculation of GMAC. To illustrate the utility of GMAC, we demonstrate the relationship between age and gray matter connectivity, using voxel-based analyses of GMAC. We discuss the potential role of GMAC in further analyses of cortical connectivity in healthy and clinical populations.