Neurophysiological signatures of sensory-processing sensitivity.

Background: Sensory processing sensitivity is mainly captured based on questionnaires and it's neurophysiological basis is largely unknown. As hitherto no electroencephalography (EEG) study has been carried out, the aim of this work was to determine whether the self-reported level of SPS correlates with the EEG activity in different frequency bands. Methods: One hundred fifteen participants were measured with 64-channel EEG during a task-free resting state. After artifact correction, a power spectrum time series was calculated using the Fast Fourier Transform (FFT) for the following frequency bands: Delta: 1-3.5 Hz, theta: 4-7.5 Hz, alpha1: 8-10 Hz, alpha2: 10.5-12 Hz, beta1: 12.5-15 Hz, beta2: 15.5-25 Hz, gamma: 25.5-45 Hz, global: 1-45 Hz. Correlations with the 'Highly Sensitive Person Scale' (HSPS-G) scores were determined. Then, the lowest and the highest 30% of the cohort were contrasted as polar opposites. EEG features were compared between the two groups applying a paired two-tailed t-test. Results: The HSPS-G scores correlated statistically significantly positive with beta 1 and 2, and global EEG power during resting with eyes open, but not during resting with eyes closed. The highly sensitive group revealed higher beta power (4.38 ± 0.32 vs. 4.21 ± 0.17, p = 0.014), higher gamma power (4.21 ± 0.37 vs. 4.00 ± 0.25, p = 0.010), and increased global EEG power (4.38 ± 0.29 vs. 4.25 ± 0.17, p = 0.041). The higher EEG activity in the HSP group was most pronounced in the central, parietal, and temporal region, whereas lower EEG activity was most present in occipital areas. Conclusion: For the first time, neurophysiological signatures associated with SPS during a task free resting state were demonstrated. Evidence is provided that neural processes differ between HSP and non-HSP. During resting with eyes open HSP exhibit higher EEG activity suggesting increased information processing. The findings could be of importance for the development of biomarkers for clinical diagnostics and intervention efficacy evaluation.

Sensory-Processing Sensitivity Is Associated with Increased Neural Entropy.

BACKGROUND: This study aimed at answering the following research questions: (1) Does the self-reported level of sensory-processing sensitivity (SPS) correlate with complexity, or criticality features of the electroencephalogram (EEG)? (2) Are there significant EEG differences comparing individuals with high and low levels of SPS? METHODS: One hundred fifteen participants were measured with 64-channel EEG during a task-free resting state. The data were analyzed using criticality theory tools (detrended fluctuation analysis, neuronal avalanche analysis) and complexity measures (sample entropy, Higuchi's fractal dimension). Correlations with the 'Highly Sensitive Person Scale' (HSPS-G) scores were determined. Then, the cohort's lowest and the highest 30% were contrasted as opposites. EEG features were compared between the two groups by applying a Wilcoxon signed-rank test. RESULTS: During resting with eyes open, HSPS-G scores correlated significantly positively with the sample entropy and Higuchi's fractal dimension (Spearman's ρ = 0.22, p < 0.05). The highly sensitive group revealed higher sample entropy values (1.83 ± 0.10 vs. 1.77 ± 0.13, p = 0.031). The increased sample entropy in the highly sensitive group was most pronounced in the central, temporal, and parietal regions. CONCLUSION: For the first time, neurophysiological complexity features associated with SPS during a task-free resting state were demonstrated. Evidence is provided that neural processes differ between low- and highly-sensitive persons, whereby the latter displayed increased neural entropy. The findings support the central theoretical assumption of enhanced information processing and could be important for developing biomarkers for clinical diagnostics.