Structure-Function Relationships in the Brain: Applications in Neurosurgery
Abstract
Multimodal brain imaging allows the study of structure-function relationships of the brain at the individual level, a key subject in basic neuroscience with important applications in neurosurgery. The current thesis aims to better understand these relationships by (1) examining how cortical morphology metrics influence measures of brain function, (2) their visualization in augmented reality (AR), and (3) their application in neurosurgical planning. To achieve these objectives, we made use of multimodal magnetic resonance imaging (MRI) data: diffusion weighted imaging, resting-state functional MRI (rs-fMRI), task-based fMRI, and T1-weighted images. Various metrics were calculated: cortical thickness (CT), blood oxygen level dependent signal variability (BOLDSD), structural connectivity (SC), functional connectivity (FC), etc.. We found that BOLDSD measures are confounded by CT, developed an application to visualize SC and FC in AR, and used rs-fMRI to map language for epilepsy surgery. Overall, these studies provided a better understanding of structure-function relationships in the brain.