| Title |
Multivoxel pattern analysis of structural MRI in children and adolescents with conduct disorder
|
|---|---|
| Published in |
Brain Imaging and Behavior, August 2018
|
| DOI | 10.1007/s11682-018-9953-6 |
| Pubmed ID | |
| Authors |
Jianing Zhang, Wanyi Cao, Mingyu Wang, Nizhuan Wang, Shuqiao Yao, Bingsheng Huang |
| Abstract |
Conduct disorder (CD) is a psychiatric disorder in either childhood or adolescence and is characterized by aggressive and antisocial behavior. Although CD has been shown to be associated with structural abnormalities by structural magnetic resonance imaging (sMRI), the classification ability of these structural abnormalities' spatial patterns remains unclear. The aim of the present study was to characterize these different spatial patterns, which may eventually serve as potential reliable imaging biomarkers in the classification of CD from healthy controls (HCs). High-resolution 3D sMRI was acquired from 60 CD and 60 HCs, and all subjects were male participants. The mean (standard deviation) age was 15.3 (1.0) years old and 15.5 (0.7) years old for the CD and HC group respectively. Multivoxel pattern analysis (MVPA) with searchlight algorithm combined with support vector machine (SVM) was used to characterize the different spatial patterns in grey matter (GM) and to assess the classification ability of such structural difference. Seven cortical and subcortical regions showed significant GM difference between CD and HCs, including the cerebellum posterior lobe, temporal lobe, parahippocampal gyrus, lingual gyrus, insula, parietal lobe and medial frontal gyrus. GM in these brain regions discriminated CD with accuracy of up to 83%. Multiple brain regions exhibited aberrantly different spatial patterns in CD. The spatial patterns might be objective and reliable imaging features that could help to improve the classification of CD. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 48 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 15% |
| Student > Bachelor | 7 | 15% |
| Student > Ph. D. Student | 6 | 13% |
| Student > Postgraduate | 4 | 8% |
| Student > Master | 3 | 6% |
| Other | 8 | 17% |
| Unknown | 13 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 13 | 27% |
| Neuroscience | 6 | 13% |
| Medicine and Dentistry | 3 | 6% |
| Social Sciences | 3 | 6% |
| Engineering | 2 | 4% |
| Other | 4 | 8% |
| Unknown | 17 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 August 2018.
All research outputs
#15,544,609
of 23,102,082 outputs
Outputs from Brain Imaging and Behavior
#670
of 1,158 outputs
Outputs of similar age
#211,563
of 334,301 outputs
Outputs of similar age from Brain Imaging and Behavior
#11
of 31 outputs
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