medRxiv
July 8, 2023
Javier R. Soriano, Julio Rodriguez-Larios, Carolina Varon et al.
1 citation
preprint
Neural and cardiac rhythms interact differently during stress and meditation. In 21 young adults with no meditation experience, heart rate and alpha brainwave frequency both slowed more during breath focus meditation than during a stressful arithmetic task. The ratio between alpha and heart rate frequencies was smaller under stress, and a specific 8:1 cross-frequency relationship occurred more often, suggesting a mechanism for coupling neural and cardiac rhythms during mild cognitive stress. Changes in these cross-frequency relationships were mostly driven by shifts in heart rate. Integrating physiological markers and their interactions may better characterize stress responses and meditation, guiding biofeedback and neurofeedback interventions.
medRxiv
September 6, 2024
Hendrik-Jan De Vuyst, Angeliki-Ιlektra Karaiskou, Javier R. Soriano et al.
preprint
A single session of EEG-neurofeedback training can increase the occurrence of non-harmonic alpha-theta brainwave patterns during focused attention meditation, an effect that persists after training ends. Thirty participants received 25 minutes each of experimental training (auditory feedback when non-harmonic alpha-theta patterns were detected) and sham training (unrelated feedback). The increase in these brainwave patterns occurred across the whole scalp, not just at the training site, and was linked to improvements in depressive mood. People with higher depressive mood at the start showed stronger training effects. The findings suggest neurofeedback could help train brainwave patterns relevant to meditation, especially for those with depressive symptoms.
Journal of Neural Engineering
December 22, 2025
Angeliki-Ilektra Karaiskou, Carolina Varon, Cem Ates Musluoglu et al.
Combining spatial and spectral alignment of EEG signals improves the classification of meditation versus rest states in new subjects without retraining. The Riemannian Space Data Alignment (RSDA) method adjusts brain activity patterns across electrodes, while Convolutional Monge Mapping Normalization (CMMN) aligns brain rhythms across frequencies. Together, they raised leave-one-subject-out classification accuracy to 66.6%, compared to 55.7% for non-aligned data and 59.6% for z-score normalization alone. Theta, Alpha, and Beta frequency bands contributed consistently, and Frontopolar and Temporal brain regions were key for distinguishing mental states. This approach offers a practical step toward calibration-free neurofeedback systems.
Javier R. Soriano, Eduardo A. Bracho Montes de Oca, Angeliki-Ilektra Karaiskou et al.
Alpha power can be trained up or down using neurofeedback combined with focused-attention meditation, but up-regulation is harder to achieve than down-regulation in a single session. In a within-subject experiment with 31 novice practitioners (25 women, mean age 23.16), participants attempted to increase or decrease global alpha power while focusing attention above the crown of the head and receiving auditory feedback. Alpha power was overall higher during up-regulation than down-regulation trials, but this difference came mainly from successful reduction of alpha during down-regulation; up-regulation did not significantly increase alpha. Training effects did not persist during a post-training resting-state recording, suggesting that more sessions are needed for lasting change.
Javier R. Soriano, Angeliki-Ilektra Karaiskou, Julio Rodriguez-Larios et al.
preprint
Expert meditators show a shift from reactive to proactive control over the connection between brain and body compared to novices. During breath-focused meditation, both groups slowed their breathing, but experts had the lowest rates and higher parasympathetic (rest-and-digest) tone. Information-flow analysis showed that novices' heart and breathing signals more strongly influenced brain alpha activity, whereas experts showed stronger top-down control from the brain to breathing, especially in frontal brain regions. Experts also showed a reduced ratio between alpha brain waves and heart rate during meditation. These results suggest that meditation training changes how the brain and body interact, consistent with predictive processing theories of interoception.