A longitudinal study of functional brain complexity in progressive Alzheimer's disease

Cross-sectional resting-state functional magnetic resonance imaging (rsfMRI) studies have revealed altered complexity with advanced Alzheimer's disease (AD) stages. The current study conducted longitudinal rsfMRI complexity analyses in AD.

Linear mixed-effects (LME) models were implemented to evaluate altered rates of disease progression in complexity across disease groups.

The LME models revealed complexity of the higher frequency in the CNtoMCI group (those converted from cognitively normal [CN] to mild cognitive impairment [MCI]) decayed faster over time versus CN in the prefrontal and lateral occipital cortex; complexity of the lower frequency decayed faster in AD versus CN in various frontal and temporal regions (p < 0.05 & Benjamini-Hochberg corrected with q < 0.05).

Local functional brain activities decayed in the early stage of the disease, and long-range communications were impacted in the later stage. Our study demonstrated longitudinal changes in AD-related rsfMRI complexity, indicating its potential as an imaging biomarker of AD.

We conducted longitudinal resting state functional magnetic resonance imaging (rsfMRI) complexity analyses using the Alzheimer's Disease Neuroimaging Initiative dataset.Higher-frequency complexity in the CNtoMCI group (those transitioning from cognitively normal [CN] to mild cognitive impairment [MCI]) was found to decay faster over time compared to CN, specifically in the prefrontal and lateral occipital cortex.Lower-frequency complexity was found to decay faster in AD versus CN in various frontal and temporal regions.This study demonstrated that longitudinal changes in rsfMRI complexity could serve as a potential imaging biomarker for Alzheimer's disease.