LANTERN: Task-Anchored Network Reserve for Post-Stroke Aphasia Recovery

Regional vascular responses and measurement noise complicate task-fMRI prediction of language recovery after stroke. We introduce \method, which measures task-conditioned language-network reserve and carries its measurement uncertainty into prediction. The reserve measure captures the diversity of regional response patterns across task conditions and is invariant to region-specific hemodynamic scaling. We relate its underlying response rank to independent task-to-region pathways in networks with hidden populations and feedback. To make measurement reliability part of learning, we jointly bound reserve over overlapping brain-region sets and train a monotone predictor against the worst-case error within those bounds. Independent calibration yields outcome prediction intervals. We evaluate current language impairment in the public Aphasia Recovery Cohort and six-month outcome in a two-center longitudinal cohort of 237 participants. On 84 participants from the held-out center, six-month prediction attains WAB-AQ mean absolute error, compared with for a brain network transformer. Nominal 90% intervals achieve coverage with a mean width of AQ points. Uncertainty-based retention reduces MAE to in the more certain half of the held-out cohort. Controlled acquisition tests distinguish task diversity, measurement precision, and integration of delayed responses. Clinical adjustment, group-level repeatability, and \FingerprintPercent% cross-run identification support the reserve's clinical relevance and individual specificity.