Resting-State EEG Dynamics During Mindfulness Meditation: Gamma-Band Enhancement and Subgroup Differences
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Resting-State EEG Dynamics During Mindfulness Meditation: Gamma-Band Enhancement and Subgroup Differences

Yichan Song 1*
1 University of Glasgow
*Corresponding author: coffey_27@hotmail.com
Published on 24 September 2025
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TNS Vol.138
ISSN (Print): 2753-8826
ISSN (Online): 2753-8818
ISBN (Print): 978-1-80590-381-9
ISBN (Online): 978-1-80590-382-6
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Abstract

Meditative states provide a unique window into intrinsic neural activity, yet the spectral and spatial dynamics of resting-state EEG during meditation remain incompletely understood. This study examined how gender, age, and meditation experience influence EEG band power and spatial coherence during eyes-closed meditation. Twenty-four participants (12 experienced meditators, 12 novices) completed a resting meditation task while 64-channel EEG data were recorded. Epochs preceding self-report prompts were extracted, and power spectral density (PSD) was computed for five canonical frequency bands (delta, theta, alpha, beta, gamma). Analyses revealed that gender consistently predicted band power—males showed elevated beta, whereas females exhibited higher gamma and delta—while age and meditation experience had minimal effects. Inter-channel correlation matrices indicated strong inter-hemispheric synchrony and local coherence. Segment-wise one-sample t-tests across five temporal blocks demonstrated robust and temporally stable gamma-band enhancement, particularly in frontal and parietal regions; beta activity was selectively enhanced in males, and delta increases appeared in females and older adults. Meditation experience influenced only minor topographic patterns without significantly altering power. These results suggest that high-frequency gamma activity is a stable marker of resting-state cortical dynamics during meditation, modulated by gender and age but not substantially by prior training. The consistent spatial and temporal patterns highlight the stability and individuality of intrinsic brain states, contributing to mapping resting-state neural signatures and informing future research on attention, self-referential processing, and mindfulness-based interventions.

Keywords:

EEG, resting-state, meditation, gamma oscillations, neural dynamics

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Song,Y. (2025). Resting-State EEG Dynamics During Mindfulness Meditation: Gamma-Band Enhancement and Subgroup Differences. Theoretical and Natural Science,138,1-12.

References

[1]. Cahn, B. R., & Polich, J. (2006). Meditation states and traits: EEG, ERP, and neuroimaging studies. Psychological Bulletin, 132(2), 180–211. https: //doi.org/10.1037/0033-2909.132.2.180

[2]. Lutz, A., Greischar, L. L., Rawlings, N. B., Ricard, M., & Davidson, R. J. (2004). Long-term meditators self-induce high-amplitude gamma synchrony during mental practice. Proceedings of the National Academy of Sciences, 101(46), 16369–16373. https: //doi.org/10.1073/pnas.0407401101

[3]. Travis, F., & Shear, J. (2010). Focused attention, open monitoring and automatic self-transcending: Categories to organize meditations from Vedic, Buddhist and Chinese traditions. Consciousness and Cognition, 19(4), 1110–1118. https: //doi.org/10.1016/j.concog.2010.01.007

[4]. Lomas, T., Ivtzan, I., & Fu, C. H. Y. (2015). A systematic review of the neurophysiology of mindfulness on EEG oscillations. Neuroscience and Biobehavioral Reviews, 57, 401–410. https: //doi.org/10.1016/j.neubiorev.2015.09.018

[5]. Braboszcz, C., Cahn, B. R., Levy, J., Fernandez, M., & Delorme, A. (2017). Increased Gamma Brainwave Amplitude Compared to Control in Three Different Meditation Traditions. PloS One, 12(1), e0170647. https: //doi.org/10.1371/journal.pone.0170647

[6]. Berger, A. M., & Davelaar, E. J. (2018). Frontal Alpha Oscillations and Attentional Control: A Virtual Reality Neurofeedback Study. Neuroscience, 378, 189–197. https: //doi.org/10.1016/j.neuroscience.2017.06.007

[7]. Cahn, B. R., Delorme, A., & Polich, J. (2010). Occipital gamma activation during Vipassana meditation. Cognitive Processing, 11(1), 39–56. https: //doi.org/10.1007/s10339-009-0352-1

[8]. State-trait influences of Vipassana meditation practice on P3 EEG dynamics. (2019). In Progress in Brain Research (Vol. 244, pp. 115–136). Elsevier. https: //doi.org/10.1016/bs.pbr.2018.10.027

[9]. From alpha to gamma: Electrophysiological correlates of meditation-related states of consciousness. (2010). Medical Hypotheses, 75(2), 218–224. https: //doi.org/10.1016/j.mehy.2010.02.025

[10]. Assem, M., Hart, M. G., Coelho, P., Romero-Garcia, R., McDonald, A., Woodberry, E., Morris, R. C., Price, S. J., Suckling, J., Santarius, T., Duncan, J., & Erez, Y. (2023). High gamma activity distinguishes frontal cognitive control regions from adjacent cortical networks. Cortex; a Journal Devoted to the Study of the Nervous System and Behavior, 159, 286–298. https: //doi.org/10.1016/j.cortex.2022.12.007

[11]. McQueen, B., Murphy, O. W., Fitzgerald, P. B., & Bailey, N. W. (2024). The Mindful Brain at Rest: Neural Oscillations and Aperiodic Activity in Experienced Meditators. Mindfulness, 15(10), 2484–2502. https: //doi.org/10.1007/s12671-024-02461-z

[12]. Berkovich-Ohana, A., Glicksohn, J., & Goldstein, A. (2012). Mindfulness-induced changes in gamma band activity – Implications for the default mode network, self-reference and attention. Clinical Neurophysiology, 123(4), 700–710. https: //doi.org/10.1016/j.clinph.2011.07.048

[13]. Jaušovec, N., & Jaušovec, K. (2010). Resting brain activity: Differences between genders. Neuropsychologia, 48(13), 3918–3925. https: //doi.org/10.1016/j.neuropsychologia.2010.09.020

[14]. Gender Differences in Spontaneous and Evoked Activities of the Human Brain | Human Physiology. (n.d.). Retrieved August 11, 2025, from https: //link.springer.com/article/10.1134/S0362119717040041

[15]. Thériault, R.-K., & Perreault, M. L. (2019). Hormonal regulation of circuit function: Sex, systems and depression. Biology of Sex Differences, 10(1), 12. https: //doi.org/10.1186/s13293-019-0226-x

[16]. Lutz, A., Greischar, L. L., Rawlings, N. B., Ricard, M., & Davidson, R. J. (2004). Long-term meditators self-induce high-amplitude gamma synchrony during mental practice. Proceedings of the National Academy of Sciences, 101(46), 16369–16373. https: //doi.org/10.1073/pnas.0407401101

[17]. Banks, J. C., Hariri, S., Kveraga, K., Ouyang, A., Gallagher, K., Quadri, S. A., Tesh, R. A., Reed, P. U., Thomas, R. J., Westover, M. B., Sun, H., & Subramaniam, B. (2025). Sleep-Based Brain Age Is Reduced in Advanced Inner Engineering Meditators. Mindfulness, 16(6), 1675–1692. https: //doi.org/10.1007/s12671-025-02583-y

[18]. Bakhtiari, A., Petersen, J., Urdanibia-Centelles, O., Ghazi, M. M., Fagerlund, B., Mortensen, E. L., Osler, M., Lauritzen, M., & Benedek, K. (2023). Power and distribution of evoked gamma oscillations in brain aging and cognitive performance. GeroScience, 45(3), 1523–1538. https: //doi.org/10.1007/s11357-023-00749-x

[19]. Duda, A. T., Clarke, A. R., & Barry, R. J. (2024). Mindfulness meditation alters neural oscillations independently of arousal. International Journal of Psychophysiology, 205, 112439. https: //doi.org/10.1016/j.ijpsycho.2024.112439

[20]. Lieberman, J. M., McConnell, P. A., Estarellas, M., & Sacchet, M. D. (2025). Neurophysiological mechanisms of focused attention meditation: A scoping systematic review. Imaging Neuroscience, 3, IMAG.a.14. https: //doi.org/10.1162/IMAG.a.14

[21]. Temporal segmentation of EEG based on functional connectivity network structure | Scientific Reports. (n.d.). Retrieved August 11, 2025, from https: //www.nature.com/articles/s41598-023-49891-8

[22]. Wiesman, A. I., da Silva Castanheira, J., & Baillet, S. (2022). Stability of spectral estimates in resting-state magnetoencephalography: Recommendations for minimal data duration with neuroanatomical specificity. NeuroImage, 247, 118823. https: //doi.org/10.1016/j.neuroimage.2021.118823

[23]. Michel, C. M., & Koenig, T. (2018). EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: A review. NeuroImage, 180, 577–593. https: //doi.org/10.1016/j.neuroimage.2017.11.062

[24]. Morales, S., & Bowers, M. E. (2022). Time-frequency analysis methods and their application in developmental EEG data. Developmental Cognitive Neuroscience, 54, 101067. https: //doi.org/10.1016/j.dcn.2022.101067

[25]. Deolindo, C. S., Ribeiro, M. W., Aratanha, M. A., Afonso, R. F., Irrmischer, M., & Kozasa, E. H. (2020). A Critical Analysis on Characterizing the Meditation Experience Through the Electroencephalogram. Frontiers in Systems Neuroscience, 14, 53. https: //doi.org/10.3389/fnsys.2020.00053

[26]. Vozzi, A., Ronca, V., Aricò, P., Borghini, G., Sciaraffa, N., Cherubino, P., Trettel, A., Babiloni, F., & Di Flumeri, G. (2021). The Sample Size Matters: To What Extent the Participant Reduction Affects the Outcomes of a Neuroscientific Research. A Case-Study in Neuromarketing Field. Sensors, 21(18), 6088. https: //doi.org/10.3390/s21186088

[27]. Osborn, M., Shankar, S., Szymanski, O., Gunningham, K., Caldwell, B., Perera, M. P. N., Michael, J., Wang, M., Fitzgerald, P. B., & Bailey, N. W. (2022). Meta-analysis Provides Weak Evidence for an Effect of Mindfulness on Neural Activity Related to Error-Processing in Healthy Individuals Only. Mindfulness, 13(12), 2907–2931. https: //doi.org/10.1007/s12671-022-02009-z

[28]. Rodriguez-Larios, J., Oca, E. A. B. M. de, & Alaerts, K. (2021). The EEG spectral fingerprints of meditation and mind wandering differ between experienced meditators and novices (p. 2021.07.06.451305). bioRxiv. https: //doi.org/10.1101/2021.07.06.451305

[29]. Frontiers | Prediction of Mind-Wandering with Electroencephalogram and Non-linear Regression Modeling. (n.d.). Retrieved August 11, 2025, from https: //www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2017.00365/full

[30]. Removal of Artifacts from EEG Signals: A Review—PMC. (n.d.). Retrieved August 11, 2025, from https: //pmc.ncbi.nlm.nih.gov/articles/PMC6427454/

[31]. Muthukumaraswamy, S. D. (2013). High-frequency brain activity and muscle artifacts in MEG/EEG: A review and recommendations. Frontiers in Human Neuroscience, 7, 138. https: //doi.org/10.3389/fnhum.2013.00138

[32]. Optimizing EEG ICA decomposition with data cleaning in stationary and mobile experiments | Scientific Reports. (n.d.). Retrieved August 11, 2025, from https: //www.nature.com/articles/s41598-024-64919-3

References

[1]. Cahn, B. R., & Polich, J. (2006). Meditation states and traits: EEG, ERP, and neuroimaging studies. Psychological Bulletin, 132(2), 180–211. https: //doi.org/10.1037/0033-2909.132.2.180

[2]. Lutz, A., Greischar, L. L., Rawlings, N. B., Ricard, M., & Davidson, R. J. (2004). Long-term meditators self-induce high-amplitude gamma synchrony during mental practice. Proceedings of the National Academy of Sciences, 101(46), 16369–16373. https: //doi.org/10.1073/pnas.0407401101

[3]. Travis, F., & Shear, J. (2010). Focused attention, open monitoring and automatic self-transcending: Categories to organize meditations from Vedic, Buddhist and Chinese traditions. Consciousness and Cognition, 19(4), 1110–1118. https: //doi.org/10.1016/j.concog.2010.01.007

[4]. Lomas, T., Ivtzan, I., & Fu, C. H. Y. (2015). A systematic review of the neurophysiology of mindfulness on EEG oscillations. Neuroscience and Biobehavioral Reviews, 57, 401–410. https: //doi.org/10.1016/j.neubiorev.2015.09.018

[5]. Braboszcz, C., Cahn, B. R., Levy, J., Fernandez, M., & Delorme, A. (2017). Increased Gamma Brainwave Amplitude Compared to Control in Three Different Meditation Traditions. PloS One, 12(1), e0170647. https: //doi.org/10.1371/journal.pone.0170647

[6]. Berger, A. M., & Davelaar, E. J. (2018). Frontal Alpha Oscillations and Attentional Control: A Virtual Reality Neurofeedback Study. Neuroscience, 378, 189–197. https: //doi.org/10.1016/j.neuroscience.2017.06.007

[7]. Cahn, B. R., Delorme, A., & Polich, J. (2010). Occipital gamma activation during Vipassana meditation. Cognitive Processing, 11(1), 39–56. https: //doi.org/10.1007/s10339-009-0352-1

[8]. State-trait influences of Vipassana meditation practice on P3 EEG dynamics. (2019). In Progress in Brain Research (Vol. 244, pp. 115–136). Elsevier. https: //doi.org/10.1016/bs.pbr.2018.10.027

[9]. From alpha to gamma: Electrophysiological correlates of meditation-related states of consciousness. (2010). Medical Hypotheses, 75(2), 218–224. https: //doi.org/10.1016/j.mehy.2010.02.025

[10]. Assem, M., Hart, M. G., Coelho, P., Romero-Garcia, R., McDonald, A., Woodberry, E., Morris, R. C., Price, S. J., Suckling, J., Santarius, T., Duncan, J., & Erez, Y. (2023). High gamma activity distinguishes frontal cognitive control regions from adjacent cortical networks. Cortex; a Journal Devoted to the Study of the Nervous System and Behavior, 159, 286–298. https: //doi.org/10.1016/j.cortex.2022.12.007

[11]. McQueen, B., Murphy, O. W., Fitzgerald, P. B., & Bailey, N. W. (2024). The Mindful Brain at Rest: Neural Oscillations and Aperiodic Activity in Experienced Meditators. Mindfulness, 15(10), 2484–2502. https: //doi.org/10.1007/s12671-024-02461-z

[12]. Berkovich-Ohana, A., Glicksohn, J., & Goldstein, A. (2012). Mindfulness-induced changes in gamma band activity – Implications for the default mode network, self-reference and attention. Clinical Neurophysiology, 123(4), 700–710. https: //doi.org/10.1016/j.clinph.2011.07.048

[13]. Jaušovec, N., & Jaušovec, K. (2010). Resting brain activity: Differences between genders. Neuropsychologia, 48(13), 3918–3925. https: //doi.org/10.1016/j.neuropsychologia.2010.09.020

[14]. Gender Differences in Spontaneous and Evoked Activities of the Human Brain | Human Physiology. (n.d.). Retrieved August 11, 2025, from https: //link.springer.com/article/10.1134/S0362119717040041

[15]. Thériault, R.-K., & Perreault, M. L. (2019). Hormonal regulation of circuit function: Sex, systems and depression. Biology of Sex Differences, 10(1), 12. https: //doi.org/10.1186/s13293-019-0226-x

[16]. Lutz, A., Greischar, L. L., Rawlings, N. B., Ricard, M., & Davidson, R. J. (2004). Long-term meditators self-induce high-amplitude gamma synchrony during mental practice. Proceedings of the National Academy of Sciences, 101(46), 16369–16373. https: //doi.org/10.1073/pnas.0407401101

[17]. Banks, J. C., Hariri, S., Kveraga, K., Ouyang, A., Gallagher, K., Quadri, S. A., Tesh, R. A., Reed, P. U., Thomas, R. J., Westover, M. B., Sun, H., & Subramaniam, B. (2025). Sleep-Based Brain Age Is Reduced in Advanced Inner Engineering Meditators. Mindfulness, 16(6), 1675–1692. https: //doi.org/10.1007/s12671-025-02583-y

[18]. Bakhtiari, A., Petersen, J., Urdanibia-Centelles, O., Ghazi, M. M., Fagerlund, B., Mortensen, E. L., Osler, M., Lauritzen, M., & Benedek, K. (2023). Power and distribution of evoked gamma oscillations in brain aging and cognitive performance. GeroScience, 45(3), 1523–1538. https: //doi.org/10.1007/s11357-023-00749-x

[19]. Duda, A. T., Clarke, A. R., & Barry, R. J. (2024). Mindfulness meditation alters neural oscillations independently of arousal. International Journal of Psychophysiology, 205, 112439. https: //doi.org/10.1016/j.ijpsycho.2024.112439

[20]. Lieberman, J. M., McConnell, P. A., Estarellas, M., & Sacchet, M. D. (2025). Neurophysiological mechanisms of focused attention meditation: A scoping systematic review. Imaging Neuroscience, 3, IMAG.a.14. https: //doi.org/10.1162/IMAG.a.14

[21]. Temporal segmentation of EEG based on functional connectivity network structure | Scientific Reports. (n.d.). Retrieved August 11, 2025, from https: //www.nature.com/articles/s41598-023-49891-8

[22]. Wiesman, A. I., da Silva Castanheira, J., & Baillet, S. (2022). Stability of spectral estimates in resting-state magnetoencephalography: Recommendations for minimal data duration with neuroanatomical specificity. NeuroImage, 247, 118823. https: //doi.org/10.1016/j.neuroimage.2021.118823

[23]. Michel, C. M., & Koenig, T. (2018). EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: A review. NeuroImage, 180, 577–593. https: //doi.org/10.1016/j.neuroimage.2017.11.062

[24]. Morales, S., & Bowers, M. E. (2022). Time-frequency analysis methods and their application in developmental EEG data. Developmental Cognitive Neuroscience, 54, 101067. https: //doi.org/10.1016/j.dcn.2022.101067

[25]. Deolindo, C. S., Ribeiro, M. W., Aratanha, M. A., Afonso, R. F., Irrmischer, M., & Kozasa, E. H. (2020). A Critical Analysis on Characterizing the Meditation Experience Through the Electroencephalogram. Frontiers in Systems Neuroscience, 14, 53. https: //doi.org/10.3389/fnsys.2020.00053

[26]. Vozzi, A., Ronca, V., Aricò, P., Borghini, G., Sciaraffa, N., Cherubino, P., Trettel, A., Babiloni, F., & Di Flumeri, G. (2021). The Sample Size Matters: To What Extent the Participant Reduction Affects the Outcomes of a Neuroscientific Research. A Case-Study in Neuromarketing Field. Sensors, 21(18), 6088. https: //doi.org/10.3390/s21186088

[27]. Osborn, M., Shankar, S., Szymanski, O., Gunningham, K., Caldwell, B., Perera, M. P. N., Michael, J., Wang, M., Fitzgerald, P. B., & Bailey, N. W. (2022). Meta-analysis Provides Weak Evidence for an Effect of Mindfulness on Neural Activity Related to Error-Processing in Healthy Individuals Only. Mindfulness, 13(12), 2907–2931. https: //doi.org/10.1007/s12671-022-02009-z

[28]. Rodriguez-Larios, J., Oca, E. A. B. M. de, & Alaerts, K. (2021). The EEG spectral fingerprints of meditation and mind wandering differ between experienced meditators and novices (p. 2021.07.06.451305). bioRxiv. https: //doi.org/10.1101/2021.07.06.451305

[29]. Frontiers | Prediction of Mind-Wandering with Electroencephalogram and Non-linear Regression Modeling. (n.d.). Retrieved August 11, 2025, from https: //www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2017.00365/full

[30]. Removal of Artifacts from EEG Signals: A Review—PMC. (n.d.). Retrieved August 11, 2025, from https: //pmc.ncbi.nlm.nih.gov/articles/PMC6427454/

[31]. Muthukumaraswamy, S. D. (2013). High-frequency brain activity and muscle artifacts in MEG/EEG: A review and recommendations. Frontiers in Human Neuroscience, 7, 138. https: //doi.org/10.3389/fnhum.2013.00138

[32]. Optimizing EEG ICA decomposition with data cleaning in stationary and mobile experiments | Scientific Reports. (n.d.). Retrieved August 11, 2025, from https: //www.nature.com/articles/s41598-024-64919-3

Cite this article

Song,Y. (2025). Resting-State EEG Dynamics During Mindfulness Meditation: Gamma-Band Enhancement and Subgroup Differences. Theoretical and Natural Science,138,1-12.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Volume title: Proceedings of ICBioMed 2025 Symposium: Computational Modelling and Simulation for Biology and Medicine

ISBN: 978-1-80590-381-9(Print) / 978-1-80590-382-6(Online)
Editor: Alan Wang, Roman Bauer
Conference website: https://2025.icbiomed.org/london.html
Conference date: 19 October 2025
Series: Theoretical and Natural Science
Volume number: Vol.138
ISSN: 2753-8818(Print) / 2753-8826(Online)

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