Integrating Raga Therapy and Non-Linear Computational Models: A Novel Approach to Neuronal Healing and Mental Well-being

New advancements in neuroscience occur when traditional healing practices unite with contemporary computational approaches in mental health research. Modern investigation of neurons' healing process and emotional health makes significant progress with the combination of Raga Therapy based on traditional music and Non-Linear Computational Modeling. Biological signals like EEG need highly advanced nonlinear modeling which consists of artificial neural networks (ANNs) and autoregressive (AR) models because these methods process dynamic and non-linear data resources. A research investigation analyzes Carnatic ragas Shankarabharanam, Hamsadhwani, Bhairavi and their effects on neuronal functions together with their modifications of brainwave patterns linked to emotional control and mental sharpness. The EEG recording data obtained from thirty healthy participants under each 15- minute raga exposure period. The researchers used BioWell equipment as it captures electrophotonic imaging (EPI) parameters to examine energy field alterations and chakra alignment during the raga sessions. Shankarabharanam exposure in EEG recordings yielded elevated alpha-band activity which indicates emotion stability while cognitive alertness increased in Hamsadhwani exposure due to beta-band intensity elevation but Bhairavi showed moderate shifts between alpha and theta bands resulting in stress reduction. The BioWell device showed a boost in mental and emotional energy patterns together with equalized chakra vibration centers which mainly affected the brain's heart (Anahata) and third-eye (Ajna) energy centers. Tests of statistical significance through paired-sample t-tests revealed that therapy produced substantial increases in alpha frequency bands, demonstrating an average rise of M = 9.24 and standard deviation of SD = 1.15 (t (49) = 7.83, p less than 0.001). The forecasting results generated through the AR model showed Shankarabharanam to be the most accurate predictor which enabled researchers to validate its therapeutic ability to relax patients. The research showed that Hamsadhwani along with Bhairavi showed remarkable effectiveness for focus enhancement and stress relief purposes respectively. The AR model succeeded in following the dynamic changes of brain activity patterns because it tracked EEG signal evolution during Raga Therapy in its non-linear nature. The combined approach of neurotherapy with computational modeling and classical music interventions forms a complete system to study how raga exposure affects nervous system recovery and emotional regulation. Additional future research needs to investigate mental health benefits from music by increasing their frequency band selection and employing advanced non-linear analysis methods for neural mechanism understanding.