Using brain connectomics to detect functional connectivity differences in Alzheimer's disease

Abstract

Prodromal Alzheimer’s disease (AD) has recently been identified as a disease state where pathophysiological changes may progress despite the absence of significant clinical symptoms. Yet, the specific processes of neural dysfunction occurring during this preclinical phase remain unclear. Resting state fMRI (RS-fMRI) in combination with brain connectomic measurements may be able to provide ways to measure subtle connectivity changes in different neurological disease states. For instance, RS-fMRI scans allow us to determine functionally connected yet spatially distinct brain regions that can then be separated into resting-state networks (RSNs). More recently, the exploration of RSNs in disease states have proved promising since they have been reliably altered when compared to a control population. By using brain connectomic approaches to assess functional connectivity we can evaluate the human connectome from a different and more global perspective to help us better understand and detect prodromal neurodegenerative disease states.