Non-neuronal signal fluctuations in Alzheimer’s disease and in mild cognitive impairment

Abstract Blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) permits the investigation neural activity thanks to the neurovascular coupling mechanism. However, neural activity accounts for only a portion of the observed BOLD signal fluctuations, as the vasculature integrates multiple physiological inputs that contribute to the response. Research focusing on isolating the vascular components of the BOLD signal revealed that markers of cerebrovascular health, such as cerebrovascular reactivity (CVR), serve as valuable biomarkers for neurodegenerative diseases. This study examines the relationship between vascular metrics and noise in a cohort comprising individuals with Alzheimer’s disease (AD), mild cognitive impairment (MCI), and healthy controls (HC). Vascular responses were assessed using three functional contrasts during a hypercapnic challenge: arterial spin labeling (ASL) to measure cerebral blood flow (CBF) reactivity, vascular space occupancy (VASO) to quantify cerebral blood volume (CBV) reactivity, and BOLD imaging. Noise metrics were derived from multi-echo BOLD resting-state data by isolating the TE-independent components of the signal. Mean correlation coefficients for noise vs ASL-CVR are: (–0.12 ± 0.06) for HC, (–0.14 ± 0.08) for MCI, (–0.11 ± 0.05) for AD. Mean correlation coefficients for noise vs BOLD-CVR are: (0.25 ± 0.11) for HC, (0.24 ± 0.07) for MCI, (0.23 ± 0.11) for AD. Mean correlation coefficients for noise vs VASO-CVR are: (0.13 ± 0.10) for HC, (0.13 ± 0.07) for MCI, (0.12 ± 0.12) for AD. These results suggest that TE-independent noise relates to the three vascular contrasts to varying extents and directions, with no significant differences across groups. Further analysis within specific functional networks revealed group differences in specific networks. The observed cortical correlations between noise and vascular features provide important insights into brain function and the progression of neurodegenerative diseases, offering a potential avenue to disentangle vascular and neural contributions in brain network and connectivity studies.