Model Validation Pipeline Against Longitudinal Alzheimer's Biomarker Data

This study develops a fractional-order model of Alzheimer's disease using a [Formula: see text]-generalized Atangana-Baleanu-Caputo (ABC) operator to capture the spatiotemporal dynamics of amyloid-beta and tau protein spread, coupled with a neuron regeneration mechanism. The fractional parameters α, [Formula: see text], and τ control memory depth, deformation of the kernel, and temporal scaling, respectively. Numerical simulations demonstrate that: (i) intermediate fractional orders [Formula: see text] produce biologically realistic propagation delays, (ii) lower [Formula: see text] values enhance nonlocal interactions and accelerate tau diffusion across the connectome, and (iii) increasing the scaling parameter τ slows accumulation, mimicking effective clearance or treatment response. Incorporating a treatment term with drug diffusion and decay reveals that sustained low decay rates ([Formula: see text]) markedly reduce tau concentrations and protect neuron populations. These findings show that the [Formula: see text]-ABC framework not only captures the hereditary and memory effects of Alzheimer's progression but also provides a flexible platform for simulating therapeutic interventions and predicting disease trajectories using real brain connectome data.