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000848149 1001_ $$0P:(DE-HGF)0$$aKong, Ru$$b0
000848149 245__ $$aSpatial Topography of Individual-Specific Cortical Networks Predicts Human Cognition, Personality, and Emotion
000848149 260__ $$aOxford$$bOxford Univ. Press$$c2019
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000848149 520__ $$aResting-state functional magnetic resonance imaging (rs-fMRI) offers the opportunity to delineate individual-specific brain networks. A major question is whether individual-specific network topography (i.e., location and spatial arrangement) is behaviorally relevant. Here, we propose a multi-session hierarchical Bayesian model (MS-HBM) for estimating individual-specific cortical networks and investigate whether individual-specific network topography can predict human behavior. The multiple layers of the MS-HBM explicitly differentiate intra-subject (within-subject) from inter-subject (between-subject) network variability. By ignoring intra-subject variability, previous network mappings might confuse intra-subject variability for inter-subject differences. Compared with other approaches, MS-HBM parcellations generalized better to new rs-fMRI and task-fMRI data from the same subjects. More specifically, MS-HBM parcellations estimated from a single rs-fMRI session (10 min) showed comparable generalizability as parcellations estimated by 2 state-of-the-art methods using 5 sessions (50 min). We also showed that behavioral phenotypes across cognition, personality, and emotion could be predicted by individual-specific network topography with modest accuracy, comparable to previous reports predicting phenotypes based on connectivity strength. Network topography estimated by MS-HBM was more effective for behavioral prediction than network size, as well as network topography estimated by other parcellation approaches. Thus, similar to connectivity strength, individual-specific network topography might also serve as a fingerprint of human behavior.
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000848149 7001_ $$0P:(DE-HGF)0$$aLi, Jingwei$$b1
000848149 7001_ $$0P:(DE-HGF)0$$aOrban, Csaba$$b2
000848149 7001_ $$0P:(DE-HGF)0$$aSabuncu, Mert R$$b3
000848149 7001_ $$0P:(DE-HGF)0$$aLiu, Hesheng$$b4
000848149 7001_ $$0P:(DE-HGF)0$$aSchaefer, Alexander$$b5
000848149 7001_ $$0P:(DE-HGF)0$$aSun, Nanbo$$b6
000848149 7001_ $$0P:(DE-HGF)0$$aZuo, Xi-Nian$$b7
000848149 7001_ $$0P:(DE-HGF)0$$aHolmes, Avram J$$b8
000848149 7001_ $$0P:(DE-Juel1)131678$$aEickhoff, Simon$$b9$$ufzj
000848149 7001_ $$00000-0002-0119-3276$$aYeo, B T Thomas$$b10$$eCorresponding author
000848149 773__ $$0PERI:(DE-600)1483485-6$$a10.1093/cercor/bhy123$$n6$$p2533–2551$$tCerebral cortex$$v29$$x1460-2199$$y2019
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