Hypertension is a risk factor for dementia and age-related neurological disorders. Analysis of resting state fMRI for brain network organization may capture early changes induced by hypertension. This investigation examined characteristic network metrics in young, otherwise asymptomatic adults (n=27; mean age 34) classified for hypertension. Path length was the most discriminating global metric. Differences in node clustering were identified using machine learning, including for subcortical regions that have been identified as brain network hubs (thalamus, hippocampus and putamen). These are critical structures for memory, supporting a potential role in cognitive deterioration and dementia and the premise of hub vulnerability.
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