Resting state EEG measurements: Trait and state variance influence personality trait relations: Methodological considerations.

• Applicants: Dr. Stefan Arnau; Professorin Dr. Andrea Hildebrandt; Professorin Dr. Andrea Kübler; Dr. Katharina Paul; Dr. Johannes Rodrigues; Professorin Dr. Jutta Stahl; Professor Dr. Alexander Strobel; Dr. Annika Ziereis
• Subject Area: Biological Psychology and Cognitive Neuroscience
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 540631605

Resting state Electroencephalography (EEG) measurements has been considered as a stable trait (e.g., Hagemann et al., 2002, 2005; Thibodeau et al., 2006; Tomarken et al., 1990; Tran et al., 2006) and features of it have been linked to various personality traits. Yet, in recent meta-analyses, summing up studies utilizing only one resting measurement for a rather limited time for about 1-4 minutes, stable trait relations are often questioned (e.g., Kuper et al., 2019; Thibodeau et al., 2006; Vecchio & De Pascalis, 2020). Explaining this finding, twenty years ago, the variance of a single resting state EEG measurement has been identified as very state dependent and only up to four measurements of the same persons allowed to identify up to 60% trait variance in all four measurements of resting state EEG combined, for example for frontal asymmetry (Hagemann et al., 2002). In a second study with three measurement repetitions, only between 40-50% trait variance could be explained (Hagemann et al., 2005). These findings led to the first goal of my project, the identification of the number of repetitions in resting state recordings to determine sufficient trait variance of resting EEG features. Beside this repetition of recording, the aspect of recording time is also of interest. Hagemann et al., (2002) could show that having a resting EEG recording of 12 minutes it was possible to identify the trait variance as explained above. Hence, beside the recording repetition, my goal is to identify the impact of recording time on the trait variance of the resting EEG features. In their work, Hagemann and colleagues were predominantly interested in frontal asymmetry (e.g., Davidson, 1984). Yet, global frequency band responses (e.g., Jach et al., 2020; Jaušovec & Jaušovec, 2007; Tran et al., 2006), cross frequency coupling (c.f., Cohen, 2014), EEG microstates (e.g., Britz et al., 2010, Khanna et al., 2015), as well as entropy (e.g., Cohen et al., 2014) have also been utilized in resting EEG research. In this project the trait variance of these different resting EEG features will be investigated, depending on the recording time as well as recording repetitions. Additionally, the impact of the reference scheme used (CSD, e.g., Cohen, 2014, Kayser, 2009, vs. linked mastoids vs. average reference) will be investigated for the trait variance of these different features. Also, the relations of the resting EEG features to selected personality traits will be determined. Finally, a short experimental task (movie task, cf. Rodrigues et al., 2021) and state measurement (Arousal and valence, e.g., Bradley & Lang, 1994, Kontou et al., 2012; Stern et al., 1997) are planned to be used to determine the impact of states as well as the impact of a repeated experimental task on the respective EEG features and their trait and state variance.

• DFG Programme: Research Grants