Journal Article

FZJ-2021-05979

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Individual-Specific Areal-Level Parcellations Improve Functional Connectivity Prediction of Behavior

Kong, R. ; Yang, Q. ; Gordon, E. ; Xue, A. ; Yan, X. ; Orban, C. ; Zuo, X.-N. ; Spreng, N. ; Ge, T. ; Holmes, A. ; Eickhoff, S.FZJ* ; Yeo, B. T. T. (Corresponding author)

2021
Oxford Univ. Press Oxford

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Please use a persistent id in citations: doi:10.1093/cercor/bhab101

Abstract: Resting-state functional magnetic resonance imaging (rs-fMRI) allows estimation of individual-specific cortical parcellations. We have previously developed a multi-session hierarchical Bayesian model (MS-HBM) for estimating high-quality individual-specific network-level parcellations. Here, we extend the model to estimate individual-specific areal-level parcellations. While network-level parcellations comprise spatially distributed networks spanning the cortex, the consensus is that areal-level parcels should be spatially localized, that is, should not span multiple lobes. There is disagreement about whether areal-level parcels should be strictly contiguous or comprise multiple noncontiguous components; therefore, we considered three areal-level MS-HBM variants spanning these range of possibilities. Individual-specific MS-HBM parcellations estimated using 10 min of data generalized better than other approaches using 150 min of data to out-of-sample rs-fMRI and task-fMRI from the same individuals. Resting-state functional connectivity derived from MS-HBM parcellations also achieved the best behavioral prediction performance. Among the three MS-HBM variants, the strictly contiguous MS-HBM exhibited the best resting-state homogeneity and most uniform within-parcel task activation. In terms of behavioral prediction, the gradient-infused MS-HBM was numerically the best, but differences among MS-HBM variants were not statistically significant. Overall, these results suggest that areal-level MS-HBMs can capture behaviorally meaningful individual-specific parcellation features beyond group-level parcellations.

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Contributing Institute(s):

1. Gehirn & Verhalten (INM-7)

Research Program(s):

1. 5252 - Brain Dysfunction and Plasticity (POF4-525) (POF4-525)

Appears in the scientific report 2021

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Database coverage:
; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; Current Contents - Life Sciences ; Essential Science Indicators ; IF >= 5 ; JCR ; Nationallizenz ; PubMed Central ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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