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A reversal coarse-grained analysis with application to an altered functional circuit in depression
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Guo, Shuixia, Yu, Yun, Zhang, Jie and Feng, Jianfeng (2013) A reversal coarse-grained analysis with application to an altered functional circuit in depression. Brain and Behavior, Volume 3 (Number 6). pp. 637-648. doi:10.1002/brb3.173 ISSN 2162-3279.
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WRAP_Feng_brb3173.pdf - Published Version Available under License Creative Commons Attribution. Download (1595Kb) | Preview |
Official URL: http://dx.doi.org/10.1002/brb3.173
Abstract
Introduction:
When studying brain function using functional magnetic resonance imaging (fMRI) data containing tens of thousands of voxels, a coarse-grained approach – dividing the whole brain into regions of interest – is applied frequently to investigate the organization of the functional network on a relatively coarse scale. However, a coarse-grained scheme may average out the fine details over small spatial scales, thus rendering it difficult to identify the exact locations of functional abnormalities.
Methods:
A novel and general approach to reverse the coarse-grained approach by locating the exact sources of the functional abnormalities is proposed.
Results:
Thirty-nine patients with major depressive disorder (MDD) and 37 matched healthy controls are studied. A circuit comprising the left superior frontal gyrus (SFGdor), right insula (INS), and right putamen (PUT) exhibit the greatest changes between the patients with MDD and controls. A reversal coarse-grained analysis is applied to this circuit to determine the exact location of functional abnormalities.
Conclusions:
The voxel-wise time series extracted from the reversal coarse-grained analysis (source) had several advantages over the original coarse-grained approach: (1) presence of a larger and detectable amplitude of fluctuations, which indicates that neuronal activities in the source are more synchronized; (2) identification of more significant differences between patients and controls in terms of the functional connectivity associated with the sources; and (3) marked improvement in performing discrimination tasks. A software package for pattern classification between controls and patients is available in Supporting Information.
| Item Type: | Journal Article | ||||
|---|---|---|---|---|---|
| Subjects: | R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry | ||||
| Divisions: | Faculty of Science, Engineering and Medicine > Science > Centre for Scientific Computing | ||||
| Library of Congress Subject Headings (LCSH): | Magnetic resonance imaging, Depression, Mental , Depression, Mental -- Diagnosis , Depression, Mental -- Etiology, Brain -- Research | ||||
| Journal or Publication Title: | Brain and Behavior | ||||
| Publisher: | John Wiley & Sons Ltd. | ||||
| ISSN: | 2162-3279 | ||||
| Official Date: | November 2013 | ||||
| Dates: |
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| Volume: | Volume 3 | ||||
| Number: | Number 6 | ||||
| Page Range: | pp. 637-648 | ||||
| DOI: | 10.1002/brb3.173 | ||||
| Status: | Peer Reviewed | ||||
| Publication Status: | Published | ||||
| Access rights to Published version: | Open Access (Creative Commons) | ||||
| Date of first compliant deposit: | 25 December 2015 | ||||
| Date of first compliant Open Access: | 25 December 2015 | ||||
| Funder: | Royal Society (Great Britain). Wolfson Research Merit Award (RSWRMA), Zhongguo ke xue yuan [Chinese Academy of Sciences] (CAS), Guo jia zi ran ke xue ji jin wei yuan hui (China) [National Natural Science Foundation of China] (NSFC), Hunan Shi fan da xue [Hunan Normal University] (HNU) | ||||
| Grant number: | 91230201, 11271121, 61104143 and 61004104 (NSFC) ; 11K038 (HNU) |
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