Mindfulness Meditators Do Not Show Differences in Electrophysiological Measures of Error Processing
- 7 Downloads
Mindfulness meditation may improve attention and self-regulation. One component of attention and self-regulation that may allow these improvements is performance monitoring. Neural correlates of performance monitoring can be objectively measured with electroencephalogram (EEG) via the error-related negativity (ERN) and error positivity (Pe). Previous research assessing the ERN and Pe in meditators has resulted in inconsistent findings; some have reported alteration in peak amplitudes from both very brief meditation practice and long-term meditation practice, while others have failed to provide evidence for differences in the ERN or Pe. However, recently developed EEG analysis techniques allow for more rigorous analyses than have been used in past investigations.
The current study measured the ERN and Pe, as well as post-error alpha suppression, during a Go/Nogo task, and emotional and colour Stroop tasks. The measures were compared between 22 experienced meditators (mean of 8 years of practice) and 20 healthy controls.
The results suggested no differences in the ERN, Pe, or post-error alpha suppression (all p > 0.05), even when varying multiple analysis parameters. The study showed equivalent statistical power to previous research, and > 85% power to detect medium effect sizes present in previous research. Bayes Factor analysis indicated the null hypotheses were > 3.5 more likely than any of the alternative hypotheses for the ERN or Pe.
These results suggest that meditation may not alter neural activity related to error processing, despite prior research suggesting that it does.
KeywordsMindfulness Meditation EEG Error processing ERN Pe
NWB designed and oversaw the study, assisted with data collection, performed the data analysis, and wrote the paper. KR performed data collection, assisted with data analysis, and collaborated with writing of the study. GF performed data collection, assisted with data analysis, and collaborated with writing of the study. BMF assisted with study design and writing of the paper. NCR assisted with study design and writing of the paper. NTVD collaborated in the interpretation of results, writing and editing of the final manuscript. PBF assisted with study design and writing and editing of the final manuscript.
PBF is supported by a National Health and Medical Research Council of Australia Practitioner Fellowship (6069070). NCR is supported by a National Health and Medical Research Council of Australia Fellowship (1072057).
Compliance with Ethical Standards
All procedures performed in the study involving human participants were in accordance with the ethical standards of both The Alfred Hospital and Monash University ethical research committee and with the 1964 Helsinki declaration and its later amendments. Informed consent was obtained from all individual participants included in the study.
Conflict of Interest
PBF has received equipment for research from MagVenture A/S, Medtronic Ltd., Cervel Neurotech and Brainsway Ltd. and funding for research from Neuronetics and Cervel Neurotech. PBF is on the scientific advisory board for Bionomics Ltd. All other authors have no conflicts to report.
- Bailey, N., Freedman, G., Raj, K., Sullivan, C., Rogasch, N., Chung, S., et al. (2018). Mindfulness meditators show altered distributions of early and late neural activity markers of attention in a response inhibition task. bioRxiv, 396259.Google Scholar
- Beck, A. T., Steer, R. A., & Brown, G. K. (1996). Beck Depression Inventory-II. San Antonio, 78(2), 490–498.Google Scholar
- Bishop, S. R., Lau, M., Shapiro, S., Carlson, L., Anderson, N. D., Carmody, J., et al. (2004). Mindfulness: a proposed operational definition. Clinical Psychology: Science and Practice, 11(3), 230–241.Google Scholar
- Falkenstein, M. (2004). ERP correlates of erroneous performance. Errors, conflicts, and the brain. Current Opinions on Performance Monitoring, 1, 5–14.Google Scholar
- Fissler, M., Winnebeck, E., Schroeter, T. A., Gummbersbach, M., Huntenburg, J. M., Gärtner, M., & Barnhofer, T. (2017). Brief training in mindfulness may normalize a blunted error-related negativity in chronically depressed patients. Cognitive, Affective, & Behavioral Neuroscience, 17(6), 1164–1175.CrossRefGoogle Scholar
- Fox, K. C., Nijeboer, S., Dixon, M. L., Floman, J. L., Ellamil, M., Rumak, S. P., et al. (2014). Is meditation associated with altered brain structure? A systematic review and meta-analysis of morphometric neuroimaging in meditation practitioners. Neuroscience & Biobehavioral Reviews, 43, 48–73.CrossRefGoogle Scholar
- Friedman, D. (2012). The components of aging. In S. J. Luck & E. S. Kappenman (Eds.), Oxford handbook of event-related potential components (pp. 1–66). Oxford: Oxford University Press.Google Scholar
- Geburek, A. J., Rist, F., Gediga, G., Stroux, D., & Pedersen, A. (2013). Electrophysiological indices of error monitoring in juvenile and adult attention deficit hyperactivity disorder (ADHD)—A meta-analytic appraisal. International Journal of Psychophysiology, 87(3), 349–362.Google Scholar
- Gehring, W. J., Liu, Y., Orr, J. M., & Carp, J. (2012). The error-related negativity (ERN/Ne). In S. J. Luck & E. S. Kappenman (Eds.), The Oxford handbook of event-related potential components (pp. 231–291). Oxford: Oxford University Press.Google Scholar
- Hergueta, T., Baker, R., & Dunbar, G. C. (1998). The Mini-International Neuropsychiatric Interview (MINI): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. Journal of Clinical Psychiatry, 59(Suppl 20), 2233.Google Scholar
- Jeffreys, H. (1961). Theory of probability (3rd edition). Oxford: Oxford University Press. MR0187257, 432.Google Scholar
- Kabat-Zinn, J. (1994). Wherever you go, there you are: mindfulness meditation in everyday life. New York: Hyperion.Google Scholar
- O’Connell, R. G., Dockree, P. M., Bellgrove, M. A., Kelly, S. P., Hester, R., Garavan, H., et al. (2007). The role of cingulate cortex in the detection of errors with and without awareness: a high-density electrical mapping study. European Journal of Neuroscience, 25(8), 2571–2579.CrossRefGoogle Scholar
- Palmer, J. A., Makeig, S., Kreutz-Delgado, K., & Rao, B. D. (2008). Newton method for the ICA mixture model. Paper presented at the Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference.Google Scholar
- Raftery, A. E. (1995). Bayesian model selection in social research. Sociological Methodology, 111–163.Google Scholar
- Schoenberg, P. L., Hepark, S., Kan, C. C., Barendregt, H. P., Buitelaar, J. K., & Speckens, A. E. (2014). Effects of mindfulness-based cognitive therapy on neurophysiological correlates of performance monitoring in adult attention-deficit/hyperactivity disorder. Clinical Neurophysiology, 125(7), 1407–1416.CrossRefGoogle Scholar
- Steer, R. A., & Beck, A. T. (1997). Beck anxiety inventory.Google Scholar