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Emo-FilM:一个使用自然主义刺激的情感神经科学多模态数据集。

Emo-FilM: A multimodal dataset for affective neuroscience using naturalistic stimuli.

作者信息

Morgenroth Elenor, Moia Stefano, Vilaclara Laura, Fournier Raphael, Muszynski Michal, Ploumitsakou Maria, Almató-Bellavista Marina, Vuilleumier Patrik, Van De Ville Dimitri

机构信息

Neuro-X Institute, École Polytechnique Fédérale de Lausanne, Geneva, 1202, Switzerland.

Department of Radiology and Medical Informatics, University of Geneva, Geneva, 1202, Switzerland.

出版信息

Sci Data. 2025 Apr 23;12(1):684. doi: 10.1038/s41597-025-04803-5.

Abstract

The Emo-FilM dataset stands for Emotion research using Films and fMRI in healthy participants. This dataset includes emotion annotations by 44 raters for 14 short films with a combined duration of over 2½ hours and recordings of respiration, heart rate, and functional magnetic resonance imaging (fMRI) from a sample of 30 individuals watching the same films. 50 items were annotated including discrete emotions and emotion components from the domains of appraisal, motivation, motor expression, physiological response, and feeling. The ratings had a mean inter-rater agreement of 0.38. The fMRI data acquired at 3 Tesla is includes high-resolution structural and resting state fMRI for each participant. Physiological recordings included heart rate, respiration, and electrodermal activity. This dataset is designed, but not limited, to studying the dynamic neural processes involved in emotion experience. It has a high temporal resolution of annotations, and includes validations of annotations by the fMRI sample. The Emo-FilM dataset is a treasure trove for researching emotion in response to naturalistic stimulation in a multimodal framework.

摘要

Emo-FilM数据集代表在健康参与者中使用电影和功能磁共振成像(fMRI)进行的情绪研究。该数据集包括44名评分者对14部短片的情绪注释,这些短片总时长超过2个半小时,还包括30名观看相同影片的个体的呼吸、心率和功能磁共振成像(fMRI)记录。共注释了50个项目,包括来自评估、动机、运动表达、生理反应和感觉等领域的离散情绪和情绪成分。评分者之间的平均一致性为0.38。在3特斯拉采集的fMRI数据包括每个参与者的高分辨率结构和静息态fMRI。生理记录包括心率、呼吸和皮肤电活动。该数据集旨在(但不限于)研究情绪体验中涉及的动态神经过程。它具有较高的注释时间分辨率,并包括fMRI样本对注释的验证。Emo-FilM数据集是在多模态框架下研究对自然主义刺激的情绪反应的宝库。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d6d/12019557/275918c4c503/41597_2025_4803_Fig1_HTML.jpg

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