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Performing group-level functional image analyses based on homologous functional regions mapped in individuals.
Li, Meiling; Wang, Danhong; Ren, Jianxun; Langs, Georg; Stoecklein, Sophia; Brennan, Brian P; Lu, Jie; Chen, Huafu; Liu, Hesheng.
  • Li M; Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
  • Wang D; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, United States of America.
  • Ren J; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, United States of America.
  • Langs G; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, United States of America.
  • Stoecklein S; National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, China.
  • Brennan BP; Department of Biomedical Imaging and Image-guided Therapy, Computational Imaging Research Lab, Medical University of Vienna, Vienna, Austria.
  • Lu J; Institute of Clinical Radiology, Ludwig-Maximilians University of Munich, Munich Germany.
  • Chen H; McLean Hospital, Harvard Medical School, Belmont, Massachusetts, United States of America.
  • Liu H; Department of Radiology, Xuanwu Hospital, Beijing, China.
PLoS Biol ; 17(3): e2007032, 2019 03.
Article en En | MEDLINE | ID: mdl-30908490
ABSTRACT
Functional MRI (fMRI) studies have traditionally relied on intersubject normalization based on global brain morphology, which cannot establish proper functional correspondence between subjects due to substantial intersubject variability in functional organization. Here, we reliably identified a set of discrete, homologous functional regions in individuals to improve intersubject alignment of fMRI data. These functional regions demonstrated marked intersubject variability in size, position, and connectivity. We found that previously reported intersubject variability in functional connectivity maps could be partially explained by variability in size and position of the functional regions. Importantly, individual differences in network topography are associated with individual differences in task-evoked activations, suggesting that these individually specified regions may serve as the "localizer" to improve the alignment of task-fMRI data. We demonstrated that aligning task-fMRI data using the regions derived from resting state fMRI may lead to increased statistical power of task-fMRI analyses. In addition, resting state functional connectivity among these homologous regions is able to capture the idiosyncrasies of subjects and better predict fluid intelligence (gF) than connectivity measures derived from group-level brain atlases. Critically, we showed that not only the connectivity but also the size and position of functional regions are related to human behavior. Collectively, these findings suggest that identifying homologous functional regions across individuals can benefit a wide range of studies in the investigation of connectivity, task activation, and brain-behavior associations.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Imagen por Resonancia Magnética Tipo de estudio: Prognostic_studies Límite: Adult / Female / Humans / Male Idioma: En Año: 2019 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Imagen por Resonancia Magnética Tipo de estudio: Prognostic_studies Límite: Adult / Female / Humans / Male Idioma: En Año: 2019 Tipo del documento: Article