Electrophysiological markers of mind wandering: A systematic review
•We systematically reviewed 42 studies on EEG markers of mind wandering.•Reduced P1, N1 and P3 ERP amplitude were reliable markers of mind wandering.•Mind wandering was linked to greater delta, theta, and alpha, and reduced beta.•Spectral markers are likely context-dependent. The ability to mentally...
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Veröffentlicht in: | NeuroImage (Orlando, Fla.) Fla.), 2022-09, Vol.258, p.119372-119372, Article 119372 |
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Zusammenfassung: | •We systematically reviewed 42 studies on EEG markers of mind wandering.•Reduced P1, N1 and P3 ERP amplitude were reliable markers of mind wandering.•Mind wandering was linked to greater delta, theta, and alpha, and reduced beta.•Spectral markers are likely context-dependent.
The ability to mentally wander away from the external environment is a remarkable feature of the human mind. Although recent years have witnessed a surge of interest in examining mind wandering using EEG, there is no comprehensive review that summarizes and accounts for the variable findings. Accordingly, we conducted a systematic review that synthesizes evidence from EEG studies that examined the electrophysiological measures of mind wandering. Our search yielded 42 studies that met eligibility criteria. The reviewed literature converges on a reduction in the amplitude of canonical ERP components (i.e., P1, N1 and P3) as the most reliable markers of mind wandering. Spectral findings were less robust, but point towards greater activity in lower frequency bands, (i.e., delta, theta, and alpha), as well as a decrease in beta band activity, during mind wandering compared to on-task states. The variability in these findings appears to be modulated by the task context. To integrate these findings, we propose an electrophysiological account of mind wandering that explains how the brain supports this inner experience. Conclusions drawn from this work will inform future endeavours in basic science to map out electrophysiological patterns underlying mind wandering and in translational science using EEG to predict the occurrence of this phenomenon. |
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ISSN: | 1053-8119 1095-9572 |
DOI: | 10.1016/j.neuroimage.2022.119372 |