Mapping Neuro signal Alterations through Meditative Practices: A Systematic Review with EEG and BCI Insights

Abstract

Meditation has gained significant attention as a non-invasive approach for improving cognitive and emotional well-being through measurable changes in brain activity. This study presents a structured review of meditationbased neurophysiological research, focusing on electroencephalography (EEG), neuroimaging, and brain– computer interface (BCI) approaches. Unlike conventional descriptive surveys, this review provides a comparative synthesis of existing studies by analyzing patterns, datasets, and computational methods across different meditation practices. The findings consistently indicate increased alpha and theta activity, enhanced neural coherence, and modulation of brain networks associated with attention and emotional regulation. Despite these advancements, key challenges persist, including limited dataset diversity, lack of standardized protocols, and minimal integration of real-time adaptive systems. To address these gaps, an integrated conceptual framework is proposed, combining standardized signal acquisition, machine learning analysis, and real-time feedback mechanisms for personalized meditation assessment. This work bridges neuroscience and engineering applications, supporting the development of scalable and interpretable neurotechnology solutions for mental health and cognitive enhancement.