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18 reviewsUnderstanding 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 highdensity EEG recordings and single-trial self-reported pain ratings in response to nociceptive laser stimuli of varying intensities (from 2.5J to 4.5J) 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.Background & SummaryPain is a fundamental sensory and emotional experience crucial for survival, but this protective mechanism can become pathological in chronic pain conditions, leading to significant impairment in quality of life1. Understanding the neural mechanisms of pain is key to the development of novel pain diagnostic and treatment strategies. Noninvasive brain imaging technologies such as electroencephalography (EEG) have led to remarkable advancements in elucidating the cortical processing of pain signals and the interplay between physiological and psychological processes in pain perception2,3. For example, nociceptive-evoked brain potentials like N1, N2, and P2 waves, and neural oscillations like alpha- and gamma-band oscillations have been shown to encode stimulus intensity4, spatial information5,6, and subjective pain perception7. Tese responses have also been utilized to buil