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Data to Brodhun et al: Neural correlates of word processing influenced by painful primes

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DataCite Commons2023-11-22 更新2024-07-13 收录
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https://doi.gin.g-node.org/10.12751/g-node.ikzki6
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Here you can find the data to the study: Brodhun C, Borelli E, Weiss T (2023). Neural correlates of word processing influenced by painful primes. PLOS ONE. DOI 10.1371/journal.pone.0295148 Abstract: The administration of painful primes has been shown to influence the perception of successively presented semantic stimuli. Painful primes lead to more negative valence ratings of pain-related, negative, and positive words than no prime. This effect was greater for pain-related than negative words. The identities of this effect’s neural correlates remain unknown. In this EEG experiment, 48 healthy subjects received noxious electrical stimuli of moderate intensity. During this priming, they were presented with adjectives of variable valence (pain-related, negative, positive, an neutral). The triggered event-related potentials were analyzed during N1 (120–180 ms), P2 (170–260 ms), P3 (300–350 ms), N400 (370–550 ms), and two late positive complex components (LPC1 [650–750 ms] and LPC2 [750–1000 ms]). Larger eventrelated potentials were found for negative and pain-related words compared to positive words in later components (N400, LPC1, and LPC2), mainly in the frontal regions. Early components (N1, P2, and P3) were less affected by the word category but were by the prime condition (painful vs. no stimulation). Later components (LPC1, LPC2) were not affected by the prime condition. An interaction effect involving prime and word category was found on the behavioral level but not the electrophysiological level. This finding indicates that the interaction effect does not directly translate from the behavioral to the electrophysiological level. Possible reasons for this discrepancy are discussed. The data repository contains raw EEG data and EEG log files as well as trigger information for Brain Vision Analyzer (compatible with EEGLAB), and subjective parameters about pain and control conditions for 48 individuals. Meta information about data structure are included. Detailed information about methods and data analysis are presented in the above-mentioned paper.
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G-Node
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2023-11-22
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