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Extracting information from functional connectivity maps via function-on-scalar regression
Reiss, Philip T.1,2; Mennes, Maarten1; Petkova, Eva1,2; Huang, Lei1; Hoptman, Matthew J.2,3; Biswal, Bharat B.2,4; Colcombe, Stanley J.2; Zuo, Xi-Nian1,5; Milham, Michael P.1,2; Reiss, PT (reprint author), NYU, Sch Med, Dept Child & Adolescent Psychiat, 215 Lexington Ave,16th Floor, New York, NY 10016 USA.
2011-05-01
Source PublicationNEUROIMAGE
ISSN1053-8119
SubtypeArticle
Volume56Issue:1Pages:140-148
Contribution Rank5
AbstractFunctional connectivity of an individual human brain is often studied by acquiring a resting state functional magnetic resonance imaging scan, and mapping the correlation of each voxel's BOLD time series with that of a seed region. As large collections of such maps become available, including multisite data sets, there is an increasing need for ways to distill the information in these maps in a readily visualized form. Here we propose a two-step analytic strategy. First, we construct connectivity-distance profiles, which summarize the connectivity of each voxel in the brain as a function of distance from the seed, a functional relationship that has attracted much recent interest. Next, these profile functions are regressed on predictors of interest, whether categorical (e.g., acquisition site or diagnostic group) or continuous (e.g., age). This procedure can provide insight into the roles of multiple sources of variation, and detect large-scale patterns not easily available from conventional analyses. We illustrate the proposed methods with a resting state data set pooled across four imaging sites. (C) 2011 Elsevier Inc. All rights reserved.
KeywordFunctional connectivity Functional data analysis Model selection Quantile regression Resting state Seed region
Subject AreaCognitive Psychology
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Indexed BySCI
Language英语
Funding OrganizationNational Institute of Mental Health [R01MH083246, K23MH087770] ; Autism Speaks ; Stavros Niarchos Foundation ; Leon Levy Foundation ; National Science Foundation [DMS-0907017] ; National Institutes of Health (NIH) [R01 EB009744-01A, R21 MH084031, R01 MH064783]
Project Intro.The authors wish to express their gratitude to the referees, whose incisive comments led to a much improved paper, and to Clare Kelly, for very helpful discussions. This research was partially supported by grants from the National Institute of Mental Health (R01MH083246 and K23MH087770), Autism Speaks, the Stavros Niarchos Foundation, and the Leon Levy Foundation, and gifts from Joseph P. Healy, Linda and Richard Schaps, Jill and Bob Smith, and the endowment provided by Phyllis Green and Randolph Cowen. Reiss's research was supported in part by National Science Foundation grant DMS-0907017 and National Institutes of Health (NIH) grant R01 EB009744-01A. Hoptman's research was supported in part by NIH grants R21 MH084031 and R01 MH064783.
WOS IDWOS:000289454900015
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Document Type期刊论文
Identifierhttp://ir.psych.ac.cn/handle/311026/11515
Collection社会与工程心理学研究室
Corresponding AuthorReiss, PT (reprint author), NYU, Sch Med, Dept Child & Adolescent Psychiat, 215 Lexington Ave,16th Floor, New York, NY 10016 USA.
Affiliation1.NYU, Sch Med, Dept Child & Adolescent Psychiat, New York, NY 10016 USA
2.Nathan S Kline Inst Psychiat Res, Orangeburg, NY 10962 USA
3.NYU, Sch Med, Dept Psychiat, New York, NY 10016 USA
4.Univ Med & Dent New Jersey, Dept Radiol, Newark, NJ 07103 USA
5.Chinese Acad Sci, Inst Psychol, Beijing 100101, Peoples R China
Recommended Citation
GB/T 7714
Reiss, Philip T.,Mennes, Maarten,Petkova, Eva,et al. Extracting information from functional connectivity maps via function-on-scalar regression[J]. NEUROIMAGE,2011,56(1):140-148.
APA Reiss, Philip T..,Mennes, Maarten.,Petkova, Eva.,Huang, Lei.,Hoptman, Matthew J..,...&Reiss, PT .(2011).Extracting information from functional connectivity maps via function-on-scalar regression.NEUROIMAGE,56(1),140-148.
MLA Reiss, Philip T.,et al."Extracting information from functional connectivity maps via function-on-scalar regression".NEUROIMAGE 56.1(2011):140-148.
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