Discrete Cognitive Resolution in Alzheimer's Disease: Cross-Cohort Reanalysis of ADNI and NACC Longitudinal Data

Abstract

INTRODUCTIONDo continuous cognitive totals capture patient-relevant transitions, or does decline have discrete structure? METHODSWe formalize a discrete cognitive resolution (DCR) model in which decline is loss of binary discriminative coordinates, with deterministic emissions tying items to a shared low-dimensional mask. Using natively discrete item-level data (ADAS-Cog, 688 ADNI participants; MoCA sub-items, 13,323 NACC participants), we tested pre-specified signatures by out-of-sample log-loss against continuous-drift, per-item, and mixed-effects IRT competitors, with a coordinate-label permutation null (S2). RESULTSDCR beat both pre-specified baselines (ADNI 0.436 vs 0.965; NACC 0.566 vs 0.602). S2 was decisive in ADNI (AUC 0.782; null 0.529, P < .001); in NACC the signal concentrated in orientation (AUC 0.718). Mixed-effects IRT achieved lower log-loss than DCR. DISCUSSIONCognitive decline shows discrete coordinate structure when items are single-coordinate probes. The claim is structural, not predictive; encoding is decisive.