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White matter (WM) has traditionally been considered structurally important but functionally inert in fMRI research. However, growing evidence indicates that WM exhibits meaningful BOLD fluctuations and participates in functional connectivity. Here, we investigate alterations in WM functional network connectivity (FNC) across the Alzheimer's disease (AD) spectrum using resting-state fMRI data from the Alzheimer's Disease Neuroimaging Initiative (ADNI; 415 cognitively normal (CN), 283 mild cognitive impairment (MCI), 91 AD). We applied a guided independent component analysis (ICA) approach based on a combined multiscale template including 202 intrinsic connectivity networks ICNs; 97 WM, 105 gray matter (GM) to estimate subject-specific timecourses and compute FNC. Group differences in WM-WM, GM-GM, and WM-GM functional network connectivity (AD-CN, AD-MCI, MCI-CN) were evaluated using two-sample t-tests on residual FNC values for age, sex, and mean framewise displacement. Multiple comparisons across edges were controlled using false discovery rate correction (q < 0.05), and effect sizes were quantified using Hedges' g. Results showed robust alterations in WM-WM and WM-GM connectivity in AD, particularly involving WM subcortical, frontal, sensorimotor, and occipitotemporal networks. Several WM-GM interactions with cerebellar and hippocampal GM networks were also disrupted, including reduced GM-cerebellar: WM-frontal coupling and increased GM-hippocampal: WM-frontal connectivity. Notably, MCI already showed WM-GM dysconnectivity relative to CN, suggesting that functional disruption of WM circuits emerges prior to overt dementia. These findings provide converging evidence that WM functional connectivity is both measurable and selectively altered across the AD continuum. Our findings support WM FNC as a candidate biomarker to GM-based measures for staging and monitoring AD. Together, these results position WM-GM dysconnectivity as an important systems-level signature of the AD continuum and support WM functional network connectivity as a promising complement to established GM-based measures for understanding disease progression.
Itkyal et al. (Thu,) studied this question.