Project Summary/Abstract The application addresses the formidable treatment gap for cognitive rehabilitation of spatial neglect (SN), defined as asymmetric orienting, perception, and responding to left space after right brain stroke, causing functional disability. Although veterans with SN are half as likely to return home, have one-third the community mobility, require 3x as much caregiver supervision, and have longer hospitalizations, increased fall risk and increased rehospitalization compared with similar right brain stroke survivors, a personalized approach to SN rehabilitation is not available in veteran-specific systems of care. We discovered that frontal lobe damage and “Aiming” SN both predict optimal recovery of functional independence after prism adaptation treatment (PAT). These findings argue for the development of an [objective, biomarker-based process to identify patients who should be administered PAT. The algorithm will be developed by identifying specific neurobiological features predictive of PAT treatment response. Thus, we expect this research will deliver a critical missing element to rehabilitation, eliminating clinician uncertainty about SN diagnosis and appropriateness of PAT, and allowing a more personalized health care approach to SN rehabilitation. Our team of researchers at three high-performing VA medical centers, distinguished in cognitive neurology analysis of brain imaging predictors, and stroke rehabilitation, from both advanced and clinical data, will develop the first biological parameter that can be used to assign SN rehabilitation. In 180 veterans (120 with SN, 60 without), we will define and validate brain imaging biomarkers that predict the presence of Aiming SN (Aim 1), a strong predictor of functional recovery after receiving PAT. Our expectation that disconnection of frontal regions with subcortical and parietal regions will predict Aiming SN. We will also examine the correlation between the brain imaging biomarkers predicting Aiming SN and improvements in daily life function after PAT (Aim 2).] Then, we will determine if adding behavioral predictors to biomarker predictors (Aim 3) accounts for additional variance in the trajectory of functional recovery. The overall impact of our work will be to establish the utility of a validated biomarker that routinely identifies veterans with SN after stroke who are the best candidates for PAT. Armed with a biomarker-based algorithm, we can then carry out a large-scale PAT clinical trial, and personalized SN care. This care pathway could reduce reliance on specialized SN assessment, [coordinate VA and community systems providing veteran stroke care,] and improve stroke care efficiency, to enhance outcomes and quality of life after stroke for thousands of veterans.