Fractal Dimension of Resting-State EEG as a Biomarker for Autonomous Sensory Meridian Response (ASMR)

Autonomous Sensory Meridian Response (ASMR) is an audio-visual phenomenon characterized by multisensory experiences in response to specific auditory stimuli, typically triggering a tingling sensation beginning in the scalp and neck and accompanied by decreased heart rate and deep relaxation. While prior electroencephalogram (EEG) studies have identified ASMR-related neural signatures in stimulus-based paradigms, resting-state differe nces between ASMR-sensitive (ASMR+) and non-sensitive (ASMR-) individuals remain unexplored. In this study, we apply Higuchi's fractal dimension (HFD) to eyes-open and eyes-closed resting-state EEG and demonstrate that ASMR+ participants exhibit significantly lower complexity in the delta (1-4Hz) and theta (4-8Hz) bands and higher complexity in the alpha (8-12Hz) band. Moreover, we train Transformer, Mamba, Random Forest and SVM classifiers on these HFD features to distinguish ASMR+ individuals from ASMR-, achieving F1 scores of 82.56%, 77.33%, 73.93%, and 70.85%, respectively. Finally, using an explainable-AI approach, we showed that ASMR+ participants had significantly lower hubness proportions (network connectivity) than ASMR-. These findings reveal novel resting-state biomarkers of ASMR sensitivity and lay the groundwork for rapid, noninvasive EEG-based screening in ASMR-augmented therapeutic applications. The code has been released on https://github.com/Shyamal-Dharia/Fractal-Dimension-of-Resting-State-EEG-as-a-Biomarker-for-Autonomous-Sensory-Meridian-Response-ASMR-GitHub.