Advanced neuroimaging methodologies based on magnetic resonance
imaging (MRI) allow us to non-invasively study the human brain and have been
extensively used in recent years to investigate its structural and functional
characteristics. However, precise locations of functionally-related connectivity
pathways have proven extremely difficult and computationally intensive to
identify, as has modeling the functionality of the neural architecture. We propose
to develop and apply tools to investigate the neuronal connectivity pathways in
the human brain as visualized by fractional anisotropic and tractographic display
of diffusion tensor MRI (DTI) data with integrated spatio-temporal cortical activities
using multi-modal MRI data fusion. The multimodal MRI data will involve fusion of
functional magnetic resonance imaging (fMRI), diffusion tensor MRI, and
electroencephalographic (EEG) data containing both functional and structural
characteristics of the human brain. The proposed research will facilitate the
addressing of research issues in efficient computational modeling of advanced
neuroimaging and provide for a better understanding of the functionality of white matter
neuronal architecture in the human brain. Such an understanding will have significant
impact on the knowledge and interpretation of relationships among normal aging,
neurodegenerative diseases, and altered white matter architecture
and have potential applications to significantly improve diagnosis of neurodegenerative
diseases and neurosurgery.