Authors : Girendra Kumar Gautam, Shikha Rathi, Akansha Nirwal, Mukesh Sharma
DOI : 10.5281/zenodo.21744974
Volume : 2
Issue : 8
Year : 2024
Page No : 50-64
The integration of artificial intelligence (AI) with neuroscience has initiated a new era of brain–machine communication, cognitive augmentation, and neurobehavioral investigation. The AI–brain interface represents an advanced technological framework that enables bidirectional communication between biological neural systems and computational devices through AI-driven analysis of brain signals. Recent progress in deep learning, neural decoding, wearable sensors, intracortical implants, and adaptive neurostimulation has accelerated the development of brain computer interfaces (BCIs) from experimental research tools into emerging clinical and cognitive enhancement platforms. Initially developed to restore communication and motor abilities in individuals with neurological disabilities, AI-assisted BCIs are now being investigated for applications in memory support, attention regulation, emotional monitoring, neurorehabilitation, learning, and human–machine interaction. Machine learning and deep learning techniques facilitate the identification of complex patterns within high-dimensional neural data, enabling more accurate interpretation of brain activity and the development of adaptive and personalized interventions. Increasing interest in AI-enabled neurotechnology has also been driven by the growing burden of neurological and psychiatric disorders, including stroke, neurodegenerative diseases, depression, and cognitive impairment. Emerging research demonstrates potential applications in speech decoding, neuroprosthetic control, rehabilitation, and closed loop therapeutic systems. However, challenges involving neural signal variability, device stability, cognitive privacy, neural data governance, safety, ethical oversight, and equitable access remain significant. This review examines current advances in AI–brain interfaces, focusing on their technological foundations, applications in cognitive enhancement and neurobehavioral research, clinical translation, emerging developments, challenges, and future perspectives.