Structural and Functional Connectivity: A Combined Analysis of Patients with Multiple Sclerosis Using Joint-ICA

The human brain can be compared to a “bundle of wires” composed by neurons that interconnect distinct gray matter regions. These “bundle of wires” are the principal composition of the white matter and has the fundamental function of conducting the synaptic signals to the gray matter. Functional magnetic resonance imaging (fMRI) corresponds to a neuroimage modality optimized to quantify neural activity that occurs in the gray matter, whereas the Diffusion Tensor Imaging (DTI) is another neuroimage modality optimized to quantify distinct white matter properties. Despite the resulting signal of these image modalities come from different tissues, they are signals that contain complementary information. In neurodegenerative diseases such as Multiple Sclerosis (MS), the myelin sheath of neurons are damaged, and can provoke a series of dysfunctions such as motor disability, problems with speech, visual problems, fatigue, among other complications. Knowing the existence of this intimate functional and structural correlation among white and gray matter, this study seeks to unify both, functional connectivity measures of fMRI and structural connectivity measures of DTI, using the statistical tool joint independent component analysis (J-ICA). Results show that the coupling of these different imaging modalities is modulated by scores derived from neuropsychological tests used to evaluate patient’s cognitive impairment by MS.