Title |
Gray Matter Axonal Connectivity Maps
|
---|---|
Published in |
Frontiers in Psychiatry, March 2015
|
DOI | 10.3389/fpsyt.2015.00035 |
Pubmed ID | |
Authors |
Leonardo Bonilha, Ezequiel Gleichgerrcht, Travis Nesland, Chris Rorden, Julius Fridriksson |
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. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | 33% |
United Kingdom | 2 | 17% |
Switzerland | 1 | 8% |
Argentina | 1 | 8% |
Unknown | 4 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 8 | 67% |
Scientists | 3 | 25% |
Science communicators (journalists, bloggers, editors) | 1 | 8% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 2 | 4% |
United States | 1 | 2% |
Austria | 1 | 2% |
Unknown | 50 | 93% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 12 | 22% |
Researcher | 10 | 19% |
Student > Master | 8 | 15% |
Student > Bachelor | 3 | 6% |
Student > Doctoral Student | 2 | 4% |
Other | 8 | 15% |
Unknown | 11 | 20% |
Readers by discipline | Count | As % |
---|---|---|
Neuroscience | 10 | 19% |
Medicine and Dentistry | 9 | 17% |
Psychology | 8 | 15% |
Engineering | 5 | 9% |
Agricultural and Biological Sciences | 3 | 6% |
Other | 6 | 11% |
Unknown | 13 | 24% |