Suppr超能文献

情感编码:复杂视频刺激中社会情感内容的标准化编码系统。

EmoCodes: a Standardized Coding System for Socio-emotional Content in Complex Video Stimuli.

作者信息

Camacho M Catalina, Williams Elizabeth M, Balser Dori, Kamojjala Ruchika, Sekar Nikhil, Steinberger David, Yarlagadda Sishir, Perlman Susan B, Barch Deanna M

机构信息

Department of Psychological and Brain Sciences, Washington University in St. Louis, One Brookings Drive, St. Louis, MO 63130 USA.

Department of Psychiatry, Washington University in St. Louis, 4444 Forest Park Drive, MO 63110 St. Louis, USA.

出版信息

Affect Sci. 2022 Jan 20;3(1):168-181. doi: 10.1007/s42761-021-00100-7. eCollection 2022 Mar.

Abstract

UNLABELLED

Social information processing is vital for inferring emotional states in others, yet affective neuroscience has only begun to scratch the surface of how we represent emotional information in the brain. Most previous affective neuroscience work has used isolated stimuli such as static images of affective faces or scenes to probe affective processing. While this work has provided rich insight to the initial stages of emotion processing (encoding cues), activation to isolated stimuli provides limited insight into later phases of emotion processing such as interpretation of cues or interactions between cues and established cognitive schemas. Recent work has highlighted the potential value of using complex video stimuli to probe socio-emotional processing, highlighting the need to develop standardized video coding schemas as this exciting field expands. Toward that end, we present a standardized and open-source coding system for complex videos, two fully coded videos, and a video and code processing Python library. The EmoCodes manual coding system provides an externally validated and replicable system for coding complex cartoon stimuli, with future plans to validate the system for other video types. The  Python library provides automated tools for extracting low-level features from video files as well as tools for summarizing and analyzing the manual codes for suitability of use in neuroimaging analysis. Materials can be freely accessed at https://emocodes.org/. These tools represent an important step toward replicable and standardized study of socio-emotional processing using complex video stimuli.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s42761-021-00100-7.

摘要

未标注

社会信息处理对于推断他人的情绪状态至关重要,但情感神经科学才刚刚开始触及我们如何在大脑中表征情绪信息的表面。以前大多数情感神经科学研究都使用孤立的刺激,如情感面孔或场景的静态图像来探究情感加工。虽然这项工作为情绪加工的初始阶段(编码线索)提供了丰富的见解,但对孤立刺激的激活对情绪加工的后期阶段,如线索的解释或线索与既定认知模式之间的相互作用,提供的见解有限。最近的研究强调了使用复杂视频刺激来探究社会情感加工的潜在价值,随着这个令人兴奋的领域不断扩展,凸显了开发标准化视频编码模式的必要性。为此,我们提出了一个用于复杂视频的标准化开源编码系统、两个完全编码的视频以及一个视频和代码处理的Python库。EmoCodes手动编码系统为编码复杂的卡通刺激提供了一个经过外部验证且可复制的系统,未来计划针对其他视频类型验证该系统。Python库提供了从视频文件中提取低级特征的自动化工具,以及用于总结和分析手动编码以适合神经成像分析使用的工具。材料可在https://emocodes.org/免费获取。这些工具代表了使用复杂视频刺激对社会情感加工进行可复制和标准化研究的重要一步。

补充信息

在线版本包含可在10.1007/s42761-021-00100-7获取的补充材料。

相似文献

3
Emotional Faces Facilitate Statistical Learning.情绪化的面孔有助于统计学习。
Affect Sci. 2022 Aug 22;3(3):662-672. doi: 10.1007/s42761-022-00130-9. eCollection 2022 Sep.
4
DynAMoS: The Dynamic Affective Movie Clip Database for Subjectivity Analysis.DynAMoS:用于主观性分析的动态情感电影片段数据库。
Int Conf Affect Comput Intell Interact Workshops. 2023 Sep;2023. doi: 10.1109/acii59096.2023.10388135. Epub 2024 Jan 15.
8
Naturalistic Stimuli in Affective Neuroimaging: A Review.情感神经影像学中的自然主义刺激:综述
Front Hum Neurosci. 2021 Jun 17;15:675068. doi: 10.3389/fnhum.2021.675068. eCollection 2021.

引用本文的文献

本文引用的文献

4
Towards clinical applications of movie fMRI.走向电影 fMRI 的临床应用。
Neuroimage. 2020 Aug 15;217:116860. doi: 10.1016/j.neuroimage.2020.116860. Epub 2020 May 4.
5
The balance of rigor and reality in developmental neuroscience.发展神经科学中的严谨性与现实性的平衡。
Neuroimage. 2020 Aug 1;216:116464. doi: 10.1016/j.neuroimage.2019.116464. Epub 2019 Dec 24.
8
Emotion schemas are embedded in the human visual system.情绪图式嵌入在人类视觉系统中。
Sci Adv. 2019 Jul 24;5(7):eaaw4358. doi: 10.1126/sciadv.aaw4358. eCollection 2019 Jul.
10
Naturalistic Stimuli in Neuroscience: Critically Acclaimed.神经科学中的自然刺激:备受赞誉。
Trends Cogn Sci. 2019 Aug;23(8):699-714. doi: 10.1016/j.tics.2019.05.004. Epub 2019 Jun 27.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验