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Proceedings Paper

Investigation of effective connectivity in the motor cortex of fMRI data using Granger causality model
Author(s): Xingchun Wu; Ni Tang; Kai Yin; Xia Wu; Xiaotong Wen; Li Yao; Xiaojie Zhao
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Paper Abstract

Effective connectivity of brain regions based on brain data (e.g. EEG, fMRI, etc.) is a focused research at present. Many researchers tried to investigate it using different methods. Granger causality model (GCM) is presently used to investigate effective connectivity of brain regions more and more. It can explore causal relationship between time series, meaning that if a time-series y causes x, then knowledge of y should help predict future values of x. In present work, time invariant GCM was applied to fMRI data considering slow changing of blood oxygenation level dependent (BOLD). The time invariant GCM often requires determining model order, estimating model parameters and significance test. In particular, we extended significance test method to make results more reasonable. The fMRI data were acquired from finger movement experiment of two right-handed subjects. We obtained the activation maps of two subjects using SPM'2 software firstly. Then we chose left SMA and left SMC as regions of interest (ROIs) with different radiuses, and calculated causality from left SMA to left SMC using the mean time courses of the two ROIs. The results from both subjects showed that left SMA influenced on left SMC. Hence GCM was suggested to be an effective approach in investigation of effective connectivity based on fMRI data.

Paper Details

Date Published: 29 March 2007
PDF: 7 pages
Proc. SPIE 6511, Medical Imaging 2007: Physiology, Function, and Structure from Medical Images, 651127 (29 March 2007); doi: 10.1117/12.708369
Show Author Affiliations
Xingchun Wu, Beijing Normal Univ. (China)
Ni Tang, Beijing Normal Univ. (China)
Kai Yin, Beijing Normal Univ. (China)
Xia Wu, Beijing Normal Univ. (China)
Xiaotong Wen, Beijing Normal Univ. (China)
Li Yao, Beijing Normal Univ. (China)
Xiaojie Zhao, Beijing Normal Univ. (China)


Published in SPIE Proceedings Vol. 6511:
Medical Imaging 2007: Physiology, Function, and Structure from Medical Images
Armando Manduca; Xiaoping P. Hu, Editor(s)

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