ArticleApplied psychophysiology and biofeedback2026
Load-Dependent Modulation of Cognitive Control Following OM Meditation: Time-Resolved EEG Evidence from the N2 Component.
Article in Applied psychophysiology and biofeedback, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Working memory (WM) depends on dynamic cognitive control processes that adapt to task demands. Although meditation has been associated with enhanced attentional regulation, its effects on load-dependent neural dynamics remain unclear. The present study investigated the effects of one month of OM meditation on behavioral performance and electrophysiological markers of cognitive control during a visual working memory task. Thirty-four healthy adult males were randomly assigned to either an OM meditation group (n = 18) or a non-meditative control group (n = 16). Electroencephalographic activity was recorded while participants performed visual n-back task with three load conditions (0-back, 1-back, and 2-back). Behavioral performance was analyzed using linear mixed-effects models. Event-related potentials (ERPs), including the P1, N1, N2, P3, and late slow wave components, were examined using both component-based and time-resolved analyses. Behaviorally, the meditation group demonstrated greater pre-post improvements in reaction time during the 0-back and 1-back conditions, but not during the 2-back condition. Accuracy remained high across all task conditions. Electrophysiologically, a significant Group × Time × Load interaction was observed for the N2 component, primarily driven by the 1-back condition. Time-resolved permutation testing further revealed a temporally localized N2 modulation under moderate working memory demand, with no reliable effects observed in other ERP components. These findings suggest that OM meditation selectively modulates monitoring-related cognitive control processes in a demand-dependent manner. More broadly, the results support adaptive models of cognitive control and highlight the value of time-resolved electrophysiological approaches for detecting transient neural changes associated with meditation training.
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