Fiber-Centered Analysis of Brain Connectivities Using DTI and Resting State FMRI Data
Recently, inference of functional connectivity between brain regions using resting state fMRI (rsfMRI) data has attracted significant interests in the neuroscience community. This paper proposes a novel fiber-centered approach to study the functional connectivity between brain regions using high spatial resolution diffusion tensor imaging (DTI) and rsfMRI data. We measure the functional coherence of a fiber as the time series correlation of two gray matter voxels that this fiber connects. The functional connectivity strength between two brain regions is defined as the average functional coherence of fibers connecting them. Our results demonstrate that: 1) The functional coherence of fibers is correlated with the brain regions they connect; 2) The functional connectivity between brain regions is correlated with structural connectivity. And these two patterns are consistent across subjects. These results may provide new insights into the brains structural and functional architecture.
functional network structural network rsfMRI DTI functional coherence
Jinglei Lv Lei Guo Xintao Hu Tuo Zhang Kaiming Li Degang Zhang Jianfei Yang Tianming Liu
School of Automation, Northwestern Polytechnical University, Xi’an, China School of Automation, Northwestern Polytechnical University, Xi’an, ChinaDepartment of Computer Scie School of Automation, Northwestern Polytechnical University, Xi’an, China Department of Computer Sci Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA
国际会议
北京
英文
143-150
2010-09-01（万方平台首次上网日期，不代表论文的发表时间）