title: Gray matter axonal connectivity maps.
abstract: 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.
authors: Department of Neurology, Medical University of South Carolina , Charleston, SC , USA.
authors: Leonardo
authors: L
authors: Bonilha
authors: Department of Neurology, Medical University of South Carolina , Charleston, SC , USA.
authors: Ezequiel
authors: E
authors: Gleichgerrcht
authors: Department of Neurology, Medical University of South Carolina , Charleston, SC , USA.
authors: Travis
authors: T
authors: Nesland
authors: Department of Psychology, University of South Carolina , Columbia, SC , USA.
authors: Chris
authors: C
authors: Rorden
authors: Department of Communication Sciences and Disorders, University of South Carolina , Columbia, SC , USA.
authors: Julius
authors: J
authors: Fridriksson
keywords: connectome; diffusion tensor imaging; magnetic resonance imaging; structural networks