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Evaluating Brain Activity in Response to Short Meditation Stimuli Using R-Score, Electroencephalography, and Neural Networks.

Daisy Das, Nabamita Deb, Rita Rani Talukdar, Saswati Sanyal Choudhury

Annals of Neurosciences October 17, 2025 DOI: 10.1177/09727531251379925 (opens in new tab) via PubMed

Summary

AI-generated from the abstract

Short audio interventions can induce relaxation in pregnant women, as measured by EEG brain activity. A new classification model combining EEG data with an artificial neural network achieved 100% accuracy in identifying meditative states during mantra meditation, particularly using signals from the frontal midline, right frontal lobe, and parietal lobe. The study emphasizes that EEG readings during meditation are more significant than those after meditation, and it offers insights into trimester-specific responses to brief audio stimuli, suggesting such interventions may be useful for stress reduction in prenatal care.

Study at a glance

Characteristics Observational study Peer reviewed
Population Pregnant participants
Intervention brief auditory stimuli
Keywords Brief Audio Electroencephalography EEG Machine learning Mantra
Key finding Short audio interventions can induce relaxation in pregnant women, and EEG channels CFz, F8, and CP2 resulted in 100% accuracy in recognizing meditative states during meditation.

Abstract

Stress is a major problem in today's culture, especially for expectant mothers. Newer therapies that show promising avenues for the reduction of stress include sound therapy, yoga, mantra chanting, and meditation (M). Electroencephalography (EEG) electroencephalography plays an important role in understanding the relaxation effects caused by these practices. This study looks at the immediate neuro-physiological effects of brief auditory stimuli on pregnant participants, focusing on EEG responses during and after meditation (AM). Unlike the literature that has focused on AM, the significance of EEG readings during M is emphasised. The new classification model, namely REA (R-score, EEG and Artificial Neural Network [ANN]) was employed for the analysis against the conventional approach of ANN. The statistical feature analysis showed in M EEG more significant than AM EEG. The results indicated that short audio interventions can be used to induce relaxation, and the identified EEG channels of CFz (frontal midline), F8 (right frontal lobe), and CP2 (parietal lobe) resulted in 100% accuracy in recognising meditative states during M. This accuracy underlines the importance of these regions for the differentiation of the relaxation states. The present study offers novel insights into trimester-specific responses to brief M audio stimuli and highly underscores the crucial role of EEG monitoring in M. These results point out that short auditory interventions might serve as a useful tool in the realm of stress reduction in prenatal care and offer a future direction of research into the neuro-physiological effects of M.

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