Dataset for: The Neural Correlates of Implicit Emotion Regulation through Affect Labeling as Reflected in EEG

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Authors: Jinyu Chen
Cited by: 0

Abstract

Materials •The folder titled “subjective_rating” contains the Excel file named “image_selected.” This file provides detailed information about the images used in the study (n = 240), including each image’s filename, transformed normative ratings (1–9) for arousal and valence, and the Picture Valence category (negative, neutral). Subjective Rating Data · The folder ‘subjective_rating’ contains an Excel file named ‘arousal_3phases_ratings’, and ‘valence_3phases_ratings’, which includes raw data on arousal and valence ratings collected for each trial per participant, along with their response times during the rating task, respectively. · The same columns in both files are: Subject, Image, Intervention_Condition, Pic_Valence, Emotion, Phase. · Within-subject factors o Intervention_Condition (labeled, matched) o Picture_Valence (negative, neutral) o Phase (immediate, short-interval, long-interval) Arousal Rating/Valence Rating · Dependent variables o Arousal_post/Valence_post: participants’ arousal/valence ratings collected during the three reexposure phases following the intervention o ArousalRT_post/ValenceRT_post: Response time (in ms) required to provide the arousal/valence rating during the reexposure phases EEG Data EEG Data Recording The EEG files exceed the upload size limitation; therefore, they can be transferred upon request if access is required. The folder titled “EEG_raw_data” contains the usable raw EEG data from 39 participants (pp09–pp57). For two participants (pp11 and pp55), the recordings are stored as two separate files due to technical issues during data collection.

Fields of Study & Subjects

Neural and Behavioral Psychology Studies Anxiety Depression Psychometrics Treatment Cognitive Processes Emotion and Mood Recognition

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
5 March 2026
Language
EN
Document type
Dataset