Year: 2026
Type: preprint
Abstract: Age-related cognitive decline in humans is well established, yet how neurobiological variations influence brain dynamics, and subsequently behavioral performance, remains insufficiently explored. Microscale accounts of cognitive aging revolve around attenuations in dopamine (DA) receptors and transporters (DAT). In contrast, macroscale accounts associate individual declines in cognitive performance with functional brain networks’ reorganization and white-matter tracts’ deterioration. We endeavor to bridge this gap with an amortized dopaminergic aging model (ADAM) which assembles aging brain twins by coupling dopaminergic modulation with structural connectomes to constrain emergent whole-brain dynamics. ADAM thereby augments established DAT decline with personalized estimates, through a reusable and generalizable estimator capable of disentangling neuromodulatory from structural contributions to age-related decline within each individual. To that end, we embed structural connectomes into a low-dimensional space exhibiting high reconstruction fidelity and —pseudonymized— individual identifiability. The spectrum of structural embeddings is subsequently updated with fMRI observations to estimate DA clearance timescales in 3,650 adults aged 36 to 95 years across five independent aging cohorts. Our analysis reveals an age-related elevation of DA clearance timescales. Critically, low performers exhibit elevated clearance in adults with marked structural degradation, and only within sliding age windows centred between 56 and 76 years. This supports a contribution of dopamine to aging, and reveals a structure- and age-conditional association between its clearance and cognitive performance. Our findings suggest that structural connectivity gates the macroscale reach of dopaminergic modulation, thus rendering the gain-control framework of neuromodulation mechanistically explicit across individuals and cohorts. ADAM therefore provides a biologically plausible framework that anchors interindividual variability in cognitive aging to perturbations in the dopaminergic system by learning cohort-scale mappings which can be shared across sites, establishing a transferable testbed for precision neuromodulation and future in-silico pharmacological trials.
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
Funders: New York State Office of Mental Health, Washington University in St. Louis, European Commission, Deutsche Forschungsgemeinschaft, Heinz Nixdorf Stiftung, National Institutes of Health, Directorate for Biological Sciences, HORIZON EUROPE Framework Programme, Medical Research Council, National Institute on Aging, National Institute of Mental Health, National Institute of Biomedical Imaging and Bioengineering
Awards: Virtual Brain Twin for personalised treatment of Psychiatric Disorders, G1643978601, G2847176290, G3275562924, EBRAINS 2.0: A Research Infrastructure to Advance Neuroscience and Brain Health, Discovery Science of Human Brain Function Across the Lifespan, G482091879, G49395674, DRIVING PERFORMANCE IN PRECLINICAL ALZHEIMER'S DISEASE, Healthy Aging and Senile Dementia, Washington University Institute of Clinical and Translational Sciences, G7660237446, G7831108753, G7919699100, G8301431789, G8441428806, Mapping the Human Connectome During Typical Aging, G9000112288, G9000115080, VULNERABILITY AND RESILIENCY IN THE AGING ADULT BRAIN CONNECTOME (AABC), Alzheimer's Disease Research Center, THE XNAT IMAGING INFORMATICS PLATFORM, Antecedent Biomarkers for Alzheimer Disease: The Adult Children Study
OpenAlex ID: W7220395433