Temporal and spatial characteristics of meditation EEG.

Decisions about the temporal and spatial characteristics of EEG during recording and analysis of meditation practices are critically important. A recent meta-analysis averaged EEG in the alpha1 and alpha2 bands to characterize mindfulness practices, ignoring known differences in cognitive processing associated with these two bands, thus confounding conclusions about brain patterns during mindfulness. Another paper averaged EEG from central and frontal electrodes to characterize Transcendental Meditation, averaging signals from motor and frontal cortices that respond to different behaviors, also confounding conclusions. Both papers reported power-derived measures, missing connectivity information captured in coherence analysis. Meditation researchers should investigate narrow frequency bands, average EEG over theoretically known spatial areas, and employ both power and coherence analysis.

Study at a glance

Abstract

OBJECTIVE: This article discusses the importance of decisions made about the temporal and spatial characteristics of EEG during recording and analysis of meditation practices. ISSUE: A recent meta-analysis averaged EEG in the alpha1 and alpha2 bands to characterize mindfulness practices. This ignored known differences in cognitive processing associated with these two bands, and so confounded their conclusion about brain patterns during mindfulness. Another paper averaged EEG from central electrodes, which reflect activity of motor cortices, and frontal electrodes, which reflect activity of the frontal association cortices, to characterize Transcendental Meditation practice. This averaged the signals from motor and frontal cortices, which respond to different behaviors, and so confounded any conclusion about the nature of brain patterns during Transcendental Meditation practice. Also, both of these papers reported power-derived measures. This misses the connectivity information that is captured in coherence analysis. CONCLUSION: Meditation researchers should (a) investigate narrow frequency bands, especially theta1, theta2, alpha1 and alpha2, which are known to reflect different cognitive processes, (b) average EEG over theoretically known spatial areas, and (c) employ power as well as coherence analysis to more accurately define different categories of meditation practices and more reliably apply meditation practices to specific subject populations. (PsycINFO Database Record (c) 2020 APA, all rights reserved).