A simplified walkthrough of the steps and major results from my thesis project. This repository contains a MATLAB live script Project_Demo.mlx. The demo can be viewed in PDF format, or within MATLAB by running the script locally.
Slides from my PhD thesis proposal are available here.
HIV is capable of invading the brain soon after seroconversion. This ultimately can lead to deficits in multiple cognitive domains commonly referred to as HIV-associated neurocognitive disorders (HAND). Clinical diagnosis of such deficits requires detailed neuropsychological assessment but clinical signs may be difficult to detect during asymptomatic injury of the central nervous system (CNS). Therefore neuroimaging biomarkers are of particular interest in HAND.
In this study, we constructed brain connectivity profiles of HIV positive subjects as well as age-matched seronegative controls using two different methods: a non-linear mutual connectivity analysis approach and a conventional method based on Pearson's correlation. These profiles were then summarized using graph-theoretic methods characterizing their topological network properties.
We have demonstrated associations between imaging-derived graph-theoretic properties of brain networks with neuropsychological performance, provides opportunities to further investigate the evolution of HAND in larger, longitudinal studies.
The results from this study have been published at Neuroimage Clinical. Another manuscript detailing the regional differences in these subjects is currently under review.