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Individualized prediction of dispositional worry using white matter connectivity
Feng, Chunliang1,2,3; Cui, Zaixu2,4; Cheng, Dazhi5; Xu, Rui1; Gu, Ruolei6,7
First AuthorFeng, Chunliang
2019-09-01
Source PublicationPSYCHOLOGICAL MEDICINE
Correspondent Emailxvr@cacms.cn ; gurl@psych.ac.cn
ISSN0033-2917
Subtypearticle
Volume49Issue:12Pages:1999-2008
Contribution Rank6
Abstract

Background Excessive worry is a defining feature of generalized anxiety disorder and is present in a wide range of other psychiatric conditions. Therefore, individualized predictions of worry propensity could be highly relevant in clinical practice, with respect to the assessment of worry symptom severity at the individual level. Methods We applied a multivariate machine learning approach to predict dispositional worry based on microstructural integrity of white matter (WM) tracts. Results We demonstrated that the machine learning model was able to decode individual dispositional worry scores from microstructural properties in widely distributed WM tracts (mean absolute error = 10.46, p < 0.001; root mean squared error = 12.82, p < 0.001; prediction R-2 = 0.17, p < 0.001). WM tracts that contributed to worry prediction included the posterior limb of internal capsule, anterior corona radiate, and cerebral peduncle, as well as the corticolimbic pathways (e.g. uncinate fasciculus, cingulum, and fornix) already known to be critical for emotion processing and regulation. Conclusions The current work thus elucidates potential neuromarkers for clinical assessment of worry symptoms across a wide range of psychiatric disorders. In addition, the identification of widely distributed pathways underlying worry propensity serves to better improve the understanding of the neurobiological mechanisms associated with worry.

KeywordCross-validation diffusion tensor imaging machine learning relevance vector regression worry
DOI10.1017/S0033291718002763
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China ; Major Program of Chinese National Social Science Foundation ; National Postdoctoral Program for Innovative Talents ; China Postdoctoral Science Foundation ; Beijing National Science Foundation ; Project of Institute of Basic Research in Clinical Medicine ; China Academy of Chinese Medical Sciences
Funding ProjectNational Natural Science Foundation of China[81503480] ; National Natural Science Foundation of China[31571124] ; National Natural Science Foundation of China[31500920] ; National Natural Science Foundation of China[31700977] ; Major Program of Chinese National Social Science Foundation[17ZDA324] ; National Postdoctoral Program for Innovative Talents[BX201600019] ; China Postdoctoral Science Foundation[2017M610055] ; Beijing National Science Foundation[7154227] ; Project of Institute of Basic Research in Clinical Medicine ; China Academy of Chinese Medical Sciences[Z0414]
WOS Research AreaPsychology ; Psychiatry
WOS SubjectPsychology, Clinical ; Psychiatry ; Psychology
WOS IDWOS:000482962600007
PublisherCAMBRIDGE UNIV PRESS
WOS KeywordGENERALIZED ANXIETY DISORDER ; POSTTRAUMATIC-STRESS-DISORDER ; REDUCED FRACTIONAL ANISOTROPY ; DIFFUSION-TENSOR ; PREFRONTAL CORTEX ; STRUCTURAL CONNECTIVITY ; UNCINATE FASCICULUS ; BRAIN ACTIVATION ; INTEGRITY ; STATE
Citation statistics
Cited Times:7[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.psych.ac.cn/handle/311026/29825
Collection中国科学院行为科学重点实验室
Corresponding AuthorXu, Rui; Gu, Ruolei
Affiliation1.China Acad Chinese Med Sci, Inst Basic Res Clin Med, Beijing 100700, Peoples R China
2.Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing 100875, Peoples R China
3.Beijing Normal Univ, Coll Informat Sci & Technol, Beijing 100875, Peoples R China
4.Univ Penn, Dept Psychiat, Perelman Sch Med, Philadelphia, PA 19104 USA
5.Capital Inst Pediat, Dept Pediat Neurol, Beijing 100020, Peoples R China
6.Inst Psychol, CAS Key Lab Behav Sci, Beijing 100101, Peoples R China
7.Univ Chinese Acad Sci, Dept Psychol, Beijing 100049, Peoples R China
Recommended Citation
GB/T 7714
Feng, Chunliang,Cui, Zaixu,Cheng, Dazhi,et al. Individualized prediction of dispositional worry using white matter connectivity[J]. PSYCHOLOGICAL MEDICINE,2019,49(12):1999-2008.
APA Feng, Chunliang,Cui, Zaixu,Cheng, Dazhi,Xu, Rui,&Gu, Ruolei.(2019).Individualized prediction of dispositional worry using white matter connectivity.PSYCHOLOGICAL MEDICINE,49(12),1999-2008.
MLA Feng, Chunliang,et al."Individualized prediction of dispositional worry using white matter connectivity".PSYCHOLOGICAL MEDICINE 49.12(2019):1999-2008.
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