An MR-DTI-based fiber tracking method for the multimodal integrative study of cognitive brain functions

We have developed a method for white matter fiber tracking inferred from magnetic resonance diffusion tensor imaging (MR-DTI) to match functional and anatomical information in the human brain. Functional information was obtained using functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG). One of the major problems in fiber tracking based on MR-DTI is the error of fiber orientation estimation at areas of fiber crossing. Here, we propose a novel fiber tracking method involving searching for similarity of direction vectors in the vicinity of fiber crossing areas. The proposed method was tested on simulation images and its utility was validated. Subsequently, the method was applied to in vivo data, and we tried to fuse the data obtained with the method with functional information obtained from a newly developed fMRI-MEG integrative method. The fMRI-MEG integrative method successfully detected dynamic cortical activities in multiple visual areas, such as V1, V2, and V5, during an apparent visual motion perception task. Our fiber tracking results demonstrate that the present method can be used to confirm connectivity among multiple cortical areas associated with higher cognitive brain functions.