Electroencephalogram-derived Involvement Indexes in Sensory Processing Sensitivity

Sensory processing sensitivity (SPS) is a temperament trait observed in highly sensitive persons (HSPs) characterized by heightened responsiveness to environmental and social stimuli. Up to now, this condition has been assessed through the HSP scale, but the neurophysiological correlates of SPS have started to be investigated by the electroencephalogram (EEG). In this context, this study aims to investigate the role of EEG-derived involvement indexes as physiological markers for characterizing and possibly identifying HSPs, contributing to existing evidence of SPS by resting-state EEG. To do so, restingstate EEG data published by Dimulescu et al. were analyzed in EEGLAB. After preprocessing involving 0.5-80 Hz band-pass filtering, average re-referencing, and artifact removal via independent component analysis, EEG rhythms were extracted, and 37 involvement indexes were computed as the ratio of powers and/or power summations of two or more EEG rhythms. Comparisons between HSPs and non-HSPs were performed per brain rhythm using the Wilcoxon rank-sum test, setting statistical significance p to 0.05, while group differences in involvement indexes were evaluated by analysis of variance (ANOVA). A more pronounced EEG brain rhythm activity in HSPs was observed, except for the alpha rhythm that resulted to be more pronounced in the non-HSP group. As for involvement indexes, 13 indexes resulted to be statistical significant in distinguishing HSPs from non-HSPs. Our results suggest that: (1) HSPs and non-HSPs exhibit different spectral patterns in resting-state EEG; (2) EEG-derived involvement indexes, especially those defined considering both low-frequency and high-frequency oscillations, may be useful to characterize SPS.Clinical RelevanceThe present study provides electroencephalographic evidence to identify highly sensitive persons, contributing to create an objective way to recognize this temperament trait.