Title |
Fast construction of voxel-level functional connectivity graphs
|
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Published in |
BMC Neuroscience, June 2014
|
DOI | 10.1186/1471-2202-15-78 |
Pubmed ID | |
Authors |
Kristian Loewe, Marcus Grueschow, Christian M Stoppel, Rudolf Kruse, Christian Borgelt |
Abstract |
Graph-based analysis of fMRI data has recently emerged as a promising approach to study brain networks. Based on the assessment of synchronous fMRI activity at separate brain sites, functional connectivity graphs are constructed and analyzed using graph-theoretical concepts. Most previous studies investigated region-level graphs, which are computationally inexpensive, but bring along the problem of choosing sensible regions and involve blurring of more detailed information. In contrast, voxel-level graphs provide the finest granularity attainable from the data, enabling analyses at superior spatial resolution. They are, however, associated with considerable computational demands, which can render high-resolution analyses infeasible. In response, many existing studies investigating functional connectivity at the voxel-level reduced the computational burden by sacrificing spatial resolution. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Italy | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
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Scientists | 1 | 50% |
Members of the public | 1 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Spain | 1 | 2% |
United States | 1 | 2% |
Switzerland | 1 | 2% |
Austria | 1 | 2% |
Unknown | 41 | 91% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 17 | 38% |
Student > Ph. D. Student | 5 | 11% |
Professor > Associate Professor | 5 | 11% |
Student > Bachelor | 4 | 9% |
Lecturer | 4 | 9% |
Other | 8 | 18% |
Unknown | 2 | 4% |
Readers by discipline | Count | As % |
---|---|---|
Neuroscience | 7 | 16% |
Engineering | 6 | 13% |
Medicine and Dentistry | 6 | 13% |
Computer Science | 5 | 11% |
Psychology | 3 | 7% |
Other | 9 | 20% |
Unknown | 9 | 20% |