Disentangling periodic and aperiodic resting EEG correlates of personality.

Autor: Pacheco LB; Melbourne School of Psychological Sciences, The University of Melbourne, Victoria, Australia. Electronic address: luiza.bonfimp@gmail.com., Feuerriegel D; Melbourne School of Psychological Sciences, The University of Melbourne, Victoria, Australia., Jach HK; Hector Research Institute of Education Sciences and Psychology, University of Tübingen, Tübingen, Germany., Robinson E; Melbourne School of Psychological Sciences, The University of Melbourne, Victoria, Australia; Bolton Clarke Research Institute, Melbourne, Victoria, Australia., Duong VN; Melbourne School of Psychological Sciences, The University of Melbourne, Victoria, Australia., Bode S; Melbourne School of Psychological Sciences, The University of Melbourne, Victoria, Australia., Smillie LD; Melbourne School of Psychological Sciences, The University of Melbourne, Victoria, Australia.
Jazyk: angličtina
Zdroj: NeuroImage [Neuroimage] 2024 Jun; Vol. 293, pp. 120628. Date of Electronic Publication: 2024 Apr 28.
DOI: 10.1016/j.neuroimage.2024.120628
Abstrakt: Previous studies of resting electroencephalography (EEG) correlates of personality traits have conflated periodic and aperiodic sources of EEG signals. Because these are associated with different underlying neural dynamics, disentangling them can avoid measurement confounds and clarify findings. In a large sample (n = 300), we investigated how disentangling these activities impacts findings related to two research programs within personality neuroscience. In Study 1 we examined associations between Extraversion and two putative markers of reward sensitivity-Left Frontal Alpha asymmetry (LFA) and Frontal-Posterior Theta (FPT). In Study 2 we used machine learning to predict personality trait scores from resting EEG. In both studies, power within each EEG frequency bin was quantified as both total power and separate contributions of periodic and aperiodic activity. In Study 1, total power LFA and FPT correlated negatively with Extraversion (r ∼ -0.14), but there was no relation when LFA and FPT were derived only from periodic activity. In Study 2, all Big Five traits could be decoded from periodic power (r ∼ 0.20), and Agreeableness could also be decoded from total power and from aperiodic indices. Taken together, these results show how separation of periodic and aperiodic activity in resting EEG may clarify findings in personality neuroscience. Disentangling these signals allows for more reliable findings relating to periodic EEG markers of personality, and highlights novel aperiodic markers to be explored in future research.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024. Published by Elsevier Inc.)
Databáze: MEDLINE
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