Performing group-level functional image analyses based on homologous functional regions mapped in individuals

• Published in: PLoS biology Vol. 17; no. 3; p. e2007032
• Main Authors: Li, Meiling, Wang, Danhong, Ren, Jianxun, Langs, Georg, Stoecklein, Sophia, Brennan, Brian P., Lu, Jie, Chen, Huafu, Liu, Hesheng
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 25.03.2019; Public Library of Science (PLoS)
• Subjects: Adult; Algorithms; Alignment; Associations; Authorship; Biology and Life Sciences; Brain; Brain - metabolism; Brain - physiology; Brain mapping; Computer and Information Sciences; Female; Functional magnetic resonance imaging; Functional morphology; Funding; Homology; Human behavior; Humans; Image Processing, Computer-Assisted - methods; Intelligence; Laboratories; Life sciences; Magnetic resonance imaging; Magnetic Resonance Imaging - methods; Male; Medical imaging; Medical schools; Medicine and Health Sciences; Methods; Methods and Resources; Morphology; Neural circuitry; Neural networks; Neural Pathways - physiology; Neurological research; Physical Sciences; Psychiatry; Research and Analysis Methods; Schizophrenia; Social Sciences; Variability; Young Adult; Beijing China; United States > US; Massachusetts; China
• ISSN: 1545-7885; 1544-9173; 1545-7885
• DOI: 10.1371/journal.pbio.2007032

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.