Multiband EEG Signatures of Openness to Experience: Exploratory Evidence from Resting‑State Eyes‑Open and Eyes‑Closed Conditions
Keywords:
Openness to Experience, Resting-state EEG, Alpha, beta, gamma rhythms, Personality neuroscienceAbstract
Purpose: The present study aimed to investigate the correlated EEG indices of Openness to Experience by analyzing multiband resting-state EEG activity in 352 healthy adults.
Methods and Materials: The present research method is descriptive-correlational. The study population consisted of 352 healthy adult men and women from Tehran, selected through convenience sampling. The process of data collection and registration took place over two years, from 2022 to 2024. The research tools included the NEO Personality Inventory (NEO-PI-R) and EEG data recording using a 19-channel device (10-20 system) at the Parand Center. Four main indices (absolute power, relative power, peak frequency, and band ratios) were extracted across all frequency bands. Data analysis used scipy (1.14.x) for performing linear regression and statistical tests and matplotlib (3.10.x) for drawing EEG topological maps.
Findings: Results indicated that the transition from EC to EO showed the most robust effects, characterized by reduced alpha1 and increased beta and gamma power as a consistent tri-band profile. Similar, though weaker, associations appeared within EC and EO separately. Power-ratio analyses revealed state-dependent markers: alpha/beta ratios in EC and delta/alpha and theta/alpha ratios in EO. These findings suggest that Openness is associated not with a single oscillatory marker but with subtle interactions between alpha, slower rhythms (delta, theta), and faster activity (beta, gamma). Comparisons with pharmacological studies demonstrated overlap with psilocybin-induced reductions in alpha and increases in gamma, while the additional beta effect may help differentiate imaginative and creative aspects of Openness from hallucinatory experiences.
Conclusion: The present results suggest that Openness leaves a modest but detectable multiband trace in resting EEG, providing a foundation for replication and future machine-learning approaches in personality neuroscience.
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Copyright (c) 2025 Farshid Rahmanian (Author); Bita Nasrollahi (Corresponding author); Hooman Namvar (Author)
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