Gray matter axonal connectivity maps

被引:7
作者
Bonilha, Leonardo [1 ]
Gleichgerrcht, Ezequiel [1 ]
Nesland, Travis [1 ]
Rorden, Chris [2 ]
Fridriksson, Julius [3 ]
机构
[1] Med Univ S Carolina, Dept Neurol, Charleston, SC 29425 USA
[2] Univ S Carolina, Dept Psychol, Columbia, SC 29208 USA
[3] Univ S Carolina, Dept Commun Sci & Disorders, Columbia, SC 29208 USA
基金
美国国家卫生研究院;
关键词
connectome; magnetic resonance imaging; diffusion tensor imaging; structural networks; PROBABILISTIC DIFFUSION TRACTOGRAPHY; CEREBRAL-CORTEX; BRAIN; MR; RECONSTRUCTION; CONNECTOME; THALAMUS; IMAGES;
D O I
10.3389/fpsyt.2015.00035
中图分类号
R749 [精神病学];
学科分类号
100204 [神经病学];
摘要
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.
引用
收藏
页数:8
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