Pattern-based Granger causality mapping in FMRI.
Since its development, the multivoxel pattern analysis (MVPA) method has been widely used to study high-level cognitive function in the brain. The results of the MVPA indicate that the spatial pattern of functional MRI data contains useful information. In addition to the spatial pattern analysis of the brain functions, effective connectivity can also be analyzed between the spatial pattern-based information. In this article, we propose a multivoxel pattern-based causality mapping method to explore influences between the spatial pattern-based information in the brain. The method applies the Granger causality to interested regions of the brain in terms of spatiotemporal pattern-based data, which are known to play an important role in dealing with high-level functions of the brain. The method can compose a causality map throughout the entire brain for any specified region of interest. Both simulations and experiments were performed to show the performance of the proposed method, and the existence and analyzability of the connectivity between pattern-based information in the brain were verified.
Department of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST) , Daejeon, Korea.
Eunwoo
E
Kim
Dae-Shik
DS
Kim
Fayyaz
F
Ahmad
Hyunwook
H
Park
D000465:Algorithms; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008959:Models, Neurological; D009044:Motor Cortex / Q000502:physiology; D009415:Nerve Net / Q000502:physiology*; D014793:Visual Cortex / Q000502:physiology