Background: In vivo neuroimaging modalities such as magnetic resonance imaging (MRI), functional MRI (fMRI), magnetoencephalography (MEG), magnetic resonance spectroscopy (MRS), and quantitative susceptibility mapping (QSM) are useful techniques to understand brain anatomical structure, functional activity, source localization, neurochemical profiling, and tissue susceptibility respectively. Integrating unique and distinct information from these neuroimaging modalities will further help to enhance the understanding of complex neurological disease. Objective: To develop a processing scheme for multimodal data integration in seamless manner on healthy young population, thus establishing a generalized framework for various clinical conditions (e.g., Alzheimer’s disease). Methods: A multimodal data integration scheme has been developed to integrate the outcomes from multiple neuroimaging data (fMRI, MEG, MRS, and QSM) spatially. Furthermore, the entire scheme has been incorporated into a user-friendly toolbox- “PRATEEK”. Results: The proposed methodology and toolbox has been tested for viability among fourteen healthy young participants for bilateral occipital cortices as the region of interest. This scheme can also be extended to other anatomical regions of interest. Overlap percentage from each combination of two modalities (fMRI-MRS, MEG-MRS, fMRI-QSM, and fMRI-MEG) has been computed and also been qualitatively assessed for combinations of the three (MEG-MRS-QSM) and four (fMRI-MEG-MRS-QSM) modalities. Conclusion: This user-friendly toolbox minimizes the need of an expertise in handling different neuroimaging tools for processing and analyzing multimodal data. The proposed scheme will be beneficial for clinical studies where geometric information plays a crucial role in advance brain research.
Generalized Liquid Association Analysis for Multimodal Data Integration
