A comprehensive physiological dataset of pain and aversive modalities for pain biomarkers research
Year: 2026
Type: preprint
Abstract: While progress has been made in identifying pain biomarkers using neuroimaging, the development of reliable EEG-based biomarkers remains challenging, limited by small sample sizes and the lack of adequate control conditions. We present a comprehensive dataset from 125 pain-free adults, comprising electroencephalogram (EEG) recordings, and behavioural, sociodemographic, and psychological data. Galvanic skin response and electrocardiogram data were also recorded in a subset of participants ( n = 76). Participants received two sustained painful stimulations (thermal, chemical) and two sustained aversive non-painful stimulations (auditory, taste), each delivered twice (with and without continuous intensity ratings). Data are provided in Brain Imaging Data Structure format, where all physiological, stimulus-related, and behavioural data are synchronized within the EEG data files for easy access and analysis. Technical validation confirmed data integrity, with spectral and physiological analyses showing responses associated with stimulus intensity and subjective pain/unpleasantness levels. By providing multimodal physiological data across painful and non-painful aversive conditions, this initiative represents a valuable resource for developing or validating biomarkers and exploring the multidimensional nature of pain perception.
Language: English
Subfield: Physiology (medical)
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7220731084