In NeuroImage. Clinical
Global cognitive performance plays an important role in the diagnosis of HIV-associated neurocognitive disorders (HAND), yet to date, there is no simple way to measure global cognitive performance in people with HIV (PWH). Here, we performed connectome-based predictive modeling (CPM) to pursue a neural biomarker of global cognitive performance in PWH based on whole-brain resting-state functional connectivity. We built a CPM model that successfully predicted individual differences in global cognitive performance in the training set of 67 PWH by using leave-one-out cross-validation. This model generalized to both 33 novel PWH in the testing set and a subset of 39 PWH who completed a follow-up visit two years later. Furthermore, network strengths identified by the CPM model were significantly different between PWH with HAND and without HAND. Together, these results demonstrate that whole-brain functional network strengths could serve as a potential neural biomarker of global cognitive performance in PWH.
Yang Fan Nils, Hassanzadeh-Behbahani Shiva, Bronshteyn Margarita, Dawson Matthew, Kumar Princy, Moore David J, Ellis Ronald J, Jiang Xiong
Cognitive function, Connectome-based predictive modeling, HIV, Machine Learning, Magnetic resonance imaging, Neurodegenerative Diseases