Analysis of the Correlation between Frontal Alpha Asymmetry of Electroencephalography and Short-Term Subjective Well-Being Changes

Abstract

Subjective well-being (SWB) describes how well people experience and evaluate their current condition. Previous studies with electroencephalography (EEG) have shown that SWB can be related to frontal alpha asymmetry (FAA). While those studies only considered a single SWB score for each experimental session, our goal is to investigate such a correlation for individuals with a possibly different SWB every 60 or 30 s. Therefore, we conducted two experiments with 30 participants each. We used different temperature and humidity settings and asked the participants to periodically rate their SWB. We computed the FAA from EEG over different time intervals and associated the given SWB, leading to pairs of (FAA, SWB) values. After correcting the imbalance in the data with the Synthetic Minority Over-sampling Technique (SMOTE), we performed a linear regression and found a positive linear correlation between FAA and SWB. We also studied the best time interval sizes for determining FAA around each SWB score. We found that using an interval of 10 s before recording the SWB score yields the best results.

An Analysis of the Correlation between the Asymmetry of Different EEG-Sensor Locations in Diverse Frequency Bands and Short-Term Subjective Well-Being Changes

“…The experiment was conducted in 2022 and first analyses of this data with the focus on FAA are already published in [ 46 ]. Before starting the experiment, we obtained approval of the local ethics committee at Osaka University.…”

“…We recorded EEG data for up to 9 min for each of the six different temperature–humidity settings in the room, namely, low, middle, and high temperatures in combination with low and high humidities. The specific values, as measured with temperature–humidity sensors of [ 47 ], can be found in the Supplementary Material of [ 46 ]. After finishing a run, the participant could relax and the experimenter changed the temperature and humidity of the room with off-the-shelf equipment to the next temperature–humidity setting.…”

“…For the EEG preprocessing, we wrote a MATLAB (R2022a) [ 48 ] pipeline using EEGLAB (v2022.0) [ 49 ] following HAPPE (The Harvard Automated Processing Pipeline for Electroencephalography) [ 50 ], making use of MARA (Multiple Artifact Rejection Algorithm) [ 51 , 52 ]. We refer the interested reader to our last paper [ 46 ] for all details about the EEG preprocessing steps. After loading the EEG data as EDF (European Data Format) files and disabling non-EEG channel recordings, we identified the sensors locations by their names in the 10–20 system.…”

“…Another issue when it comes to calculating EEG asymmetries, especially FAA, is that there is no consensus in the literature on which specific EEG sensors to use. In our previous work [ 46 ], we chose AF3 and AF4 for the calculation of FAA. However, F7 and F8 are also popular choices.…”

“…In our previous work, we could show that a correlation between FAA and SWB also holds for short-time scales [ 46 ]. This expands previous knowledge, which described this correlation on larger time scales and when psychological or psychiatric interventions were performed.…”