The dynamic connectome in Alzheimer's disease: From static snapshots to a symphony in time—A hypothesis

The static functional connectivity (sFC) model has established Alzheimer's disease (AD) as a large-scale brain network disorder, yet it rests on a questionable assumption of temporal stationarity. This assumption obscures the brain's intrinsic dynamics, which are essential for flexible cognition. Here, we advance the hypothesis that the core deficit in AD is not merely a weakening of average connections, but a fundamental loss of the brain's capacity for temporal coordination, adaptive reconfiguration, and metastable dynamics-a state we term dynamic network dysrhythmia. Synthesizing evidence from dynamic functional connectivity (dFC) studies across the AD continuum, from subjective cognitive decline to mild cognitive impairment and AD dementia, we argue that the AD brain exhibits a progressive collapse in temporal flexibility: reduced state transition frequency, diminished connectivity variability, and entrapment in inefficient network configurations. These dynamic abnormalities correlate with molecular pathology, structural disconnection, and domain-specific cognitive deficits, positioning dFC metrics as sensitive, systems-level digital biomarkers. We further outline methodological challenges and translational opportunities for dFC in early detection, prognostic stratification, and treatment monitoring. This hypothesis reframes AD from a static disconnection syndrome to a dynamic dysrhythmia, with profound implications for both mechanistic understanding and clinical practice.