The oscillatory fingerprints of self-prioritization: Novel markers in spectral EEG for self-relevant processing

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Abstract

Self-prioritization is a very influential modulator of human information processing. Still, little is known about the time-frequency dynamics of the self-prioritization network. In this EEG study, we used the familiarity-confound free matching task to investigate the spectral dynamics of self-prioritization and their underlying cognitive functions in a drift-diffusion model. Participants (N = 40) repeatedly associated arbitrary geometric shapes with either “the self” or “a stranger.” Behavioral results demonstrated prominent self-prioritization effects (SPEs) in reaction time and accuracy. Remarkably, EEG cluster analysis also revealed two significant SPEs, one in delta/theta power (2–7 Hz) and one in beta power (19–29 Hz). Drift-diffusion modeling indicated that beta activity was associated with evidence accumulation, whereas delta/theta activity was associated with response selection. The decreased beta suppression of the SPE might indicate more efficient sensorimotor processing of self-associated stimulus–response features, whereas the increased delta/theta SPE might refer to the facilitated retrieval of self-relevant features across a widely distributed associative self-network. These novel oscillatory biomarkers of self-prioritization indicate their function as an associative glue for the self-concept.

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Haciahmet, C. C., Golubickis, M., Schäfer, S., Frings, C., & Pastötter, B. (2023). The oscillatory fingerprints of self-prioritization: Novel markers in spectral EEG for self-relevant processing. Psychophysiology, 60(12). https://doi.org/10.1111/psyp.14396

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