Detecting Altered connectivity patterns in HIV associated neurocognitive impairment using Mutual Connectivity...

Area of Science:

• Neuroimaging
• Neurology
• Network Science

Background:

• Functional Magnetic Resonance Imaging (fMRI) reveals brain network changes in neurological disorders.
• HIV infection often leads to cognitive deficits, known as HIV-associated neurocognitive disorder (HAND).

Purpose of the Study:

• To apply a novel Mutual Connectivity Analysis (MCA) technique to detect brain network differences between HIV-positive and HIV-negative individuals.
• To investigate the utility of MCA combined with Network-Based Statistics (NBS) in a clinical case-control setting.

Main Methods:

• Resting-state fMRI data from 10 subjects (5 HIV+, 5 HIV-) were pre-processed.
• Mutual Connectivity Analysis (MCA) was used to generate brain network graphs from Automated Anatomic Labeling (AAL) atlas data.
• Network-Based Statistics (NBS) compared graph edges between groups, controlling for family-wise error rate.

Main Results:

• A significantly different network (42 nodes, 65 edges) was identified between HIV+ and HIV- subjects.
• HIV+ individuals exhibited decreased connectivity in basal ganglia regions and affected posterior cingulate cortex nodes.
• Findings align with existing knowledge of HIV-associated neurocognitive disorder (HAND) pathophysiology.

Conclusions:

• The novel MCA approach, coupled with NBS, effectively detects connectivity pattern differences in clinical populations.
• This method holds promise for understanding brain network alterations in HIV infection and HAND.
• The study highlights significant network disruptions in HIV+ individuals, particularly involving the basal ganglia.