Author(s)

Rosimar Jose de Lima Dias

Faculdade Católica de Mato Grosso (FACC-MT), Várzea Grande, Brasil.

Artificial intelligence (AI) and neurotechnologies are redefining neuropsychological rehabilitation, enabling precision-guided, real-time neuromodulation. This review introduces the hybrid mind paradigm—a convergence of biological and artificial cognition—operationalized through AI-enhanced braincomputer interfaces (BCIs), deep brain stimulation (DBS), and adaptive neurofeedback. These technologies integrate closed-loop modulation and neuroadaptive algorithms to optimize neuroplasticity and functional recovery. While AI-driven systems show promise in cognitive and motor domains, translational barriers persist, including algorithmic opacity, neural data governance, and fragmented regulation. We synthesize recent evidence and outline strategic priorities: implementation of explainable AI frameworks, development of non-invasive neuromodulatory alternatives, and global harmonization of ethical standards. As AI and neuroscience converge, the hybrid mind paradigm signals a pivotal shift toward individualized, ethically guided neurorehabilitation.

Hybrid Mind, AI-Driven Neurorehabilitation, Brain-Computer Interfaces (BCIs), Deep Brain Stimulation (DBS), Neuroadaptive Algorithms

de Lima Dias, R. (2025) The Hybrid Mind in Precision Neurorehabilitation: Integrating AI-Driven Neurotechnologies and Ethical Governance. World Journal of Neuroscience, 15, 105-125. doi: 10.4236/wjns.2025.152010.