Individualized Functional Deviation Mapping: Linking Heterogeneous Structural Atrophy to Convergent Network Disruption in Preclinical Alzheimer's Disease

The preclinical phase of Alzheimers disease (AD) is characterized by profound biological and structural heterogeneity, challenging our ability to map early pathology onto large-scale brain networks. To address this fundamental challenge, we introduce Functional Deviation Maps ({pi}z), an individualized neuroimaging framework for mapping participant-specific functional architecture to their unique structural atrophy landscape. By fitting a normative model to the voxel-based morphometry of amyloid-negative individuals, we extract personalized "atrophy seeds" (W-scores [≤] -1.96) for amyloid-positive patients, subsequently obtaining their resting-state seed-based connectivity (SBC). By standardizing these participant-level SBC maps against a healthy reference distribution, we show that, despite the highly variable spatial origins of structural atrophy, individual functional deviations converge into a common "atrophy network". Spatial enrichment analyses show that the functional disruption is not random, but preferentially is dominated by the Default Mode Network. Furthermore, by projecting these populational functional deviations onto high-order cognitive topographies, we find a considerable alignment with the brains fundamental unimodal-transmodal and external-internal attentional gradients. Overall, the{pi} z framework transcends conventional group-level averages, offering a highly personalized, biologically meaningful signature of system-level network vulnerability in the earliest stages of AD.