ArticleNeuroImage. Clinical2021
Connectome-based prediction of global cognitive performance in people with HIV.
Article in NeuroImage. Clinical, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Limbic and whole-brain functional connectivity in non-substance abusers with human immunodeficiency virus (HIV).Journal of neurovirology · 2026Article
- Graph theory analysis reveals functional brain network alterations in HIV-associated asymptomatic neurocognitive impairment in virally suppressed homosexual males.BMC infectious diseases · 2025Article
- Decoding HIV-associated neurocognitive disorders: a new perspective from multimodal connectomics.Frontiers in neurology · 2025Review
- The Individualized Prediction of Neurocognitive Function in People Living With HIV Based on Clinical and Multimodal Connectome Data.IEEE journal of biomedical and health informatics · 2023Article
- Connectome-based predictive modeling of trait forgiveness.Social cognitive and affective neuroscience · 2023Article
- Multivariate prediction of long COVID headache in adolescents using gray matter structural MRI features.Frontiers in human neuroscience · 2023Article
- The impacts of HIV infection, age, and education on functional brain networks in adults with HIV.Journal of neurovirology · 2022Article
- What makes our brain unique: Insights from a two-night fMRI-EEG sleep study.Imaging neuroscience (Cambridge, Mass.)Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
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.
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