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.
Meditation shows promise for treating posttraumatic stress disorder (PTSD), but its mechanisms remain poorly understood, hindering its use as an evidence-based clinical intervention. Electroencephalography (EEG) can measure brain network changes during meditation, yet recent meta-analyses report mixed findings, with some consistent enhancements in theta and alpha neural oscillations but many inconsistencies. This commentary identifies critical, often overlooked measurement issues in meditation EEG studies that contribute to replication problems. It reviews physiological artifact-related issues in time, frequency, and time-frequency measures, as well as spatial-domain measurement problems inherent to EEG, and recommends standard EEG processing and analysis methods to resolve these obstacles.