ArticleScientific data2025
A comprehensive EEG dataset of laser-evoked potentials for pain research.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Understanding the neural mechanisms of pain is key to the development of novel pain diagnostic and treatment strategies. Here, we present a large-scale, comprehensive electroencephalogram (EEG) dataset of laser-evoked potentials (LEPs) from 678 healthy participants. This dataset comprises high-density EEG recordings and single-trial self-reported pain ratings in response to nociceptive laser stimuli of varying intensities (from 2.5 J to 4.5 J) delivered to either the left or right dorsum of the hand, without any physical or psychological interventions. As the largest nociceptive-evoked EEG dataset to date, it can serve as a valuable resource for mechanistic pain studies such as investigating electrophysiological underpinnings of within-individual and between-individual pain variations, for clinical studies such as providing normal values of LEPs to assess the possible lesions of pain pathways, and for methodological innovations in EEG signal processing such as optimizing preprocessing pipelines and developing new analytical tools.
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