Abstract / Summary
The integration of artificial intelligence (AI) into neuropsychological rehabilitation represents an expanding technological frontier, yet no study has systematically mapped this field across the lifespan. This bibliometric-systematic review analyzed 4336 Scopus-indexed publications (2020–2025) across pediatric ( n = 366), adult ( n = 883), and geriatric ( n = 3,087) populations using Bibliometrix. Results reveal an overwhelming disparity: research on older adults exceeds that on children and adults by eightfold. Geriatric research shows sustained annual growth (≈ 18.5 articles/year), while pediatric and adult corpora exhibit volatile, non-linear patterns (R²=0.0515 and 0.0087), indicating lack of research consolidation. Virtual reality emerged as the central cross-cutting technology, yet with marked specialization: in pediatrics, associated with executive functions training; in older adults, combined with machine learning for cognitive assessment (highest impact: 4.250). Thematic foci align with epidemiological priorities—neurodevelopmental disorders in children, acquired conditions in adults, neurodegenerative diseases in older adults—while revealing methodological stratification: geriatric research integrates neuroimaging with AI; pediatric research emphasizes behavioral interventions. High-impact niches identified include AI-integrated neurofeedback in pediatrics (impact 2.052) and VR with machine learning for mild cognitive impairment in gerontology (impact 4.250). Working-age adults with acquired brain injuries emerge as a persistently underserved population. This first comparative cartography of AI-enabled neuropsychological rehabilitation across the lifespan offers actionable insights for strategic resource allocation and identifies critical gaps requiring urgent attention.