Suppr超能文献

通过功能磁共振成像对动态自然主义视听刺激的反应来识别个体的核心情感。

Identifying Core Affect in Individuals from fMRI Responses to Dynamic Naturalistic Audiovisual Stimuli.

作者信息

Kim Jongwan, Wang Jing, Wedell Douglas H, Shinkareva Svetlana V

机构信息

Department of Psychology, University of South Carolina, Columbia, South Carolina, United States of America.

Department of Psychology, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.

出版信息

PLoS One. 2016 Sep 6;11(9):e0161589. doi: 10.1371/journal.pone.0161589. eCollection 2016.

Abstract

Recent research has demonstrated that affective states elicited by viewing pictures varying in valence and arousal are identifiable from whole brain activation patterns observed with functional magnetic resonance imaging (fMRI). Identification of affective states from more naturalistic stimuli has clinical relevance, but the feasibility of identifying these states on an individual trial basis from fMRI data elicited by dynamic multimodal stimuli is unclear. The goal of this study was to determine whether affective states can be similarly identified when participants view dynamic naturalistic audiovisual stimuli. Eleven participants viewed 5s audiovisual clips in a passive viewing task in the scanner. Valence and arousal for individual trials were identified both within and across participants based on distributed patterns of activity in areas selectively responsive to audiovisual naturalistic stimuli while controlling for lower level features of the stimuli. In addition, the brain regions identified by searchlight analyses to represent valence and arousal were consistent with previously identified regions associated with emotion processing. These findings extend previous results on the distributed representation of affect to multimodal dynamic stimuli.

摘要

最近的研究表明,通过功能磁共振成像(fMRI)观察到的全脑激活模式能够识别出由观看效价和唤醒水平不同的图片所引发的情感状态。从更自然主义的刺激中识别情感状态具有临床意义,但基于动态多模态刺激引发的fMRI数据在个体试验基础上识别这些状态的可行性尚不清楚。本研究的目的是确定当参与者观看动态自然主义视听刺激时,是否能以类似方式识别情感状态。11名参与者在扫描仪中进行被动观看任务时观看了5秒的视听片段。在控制刺激的低层次特征的同时,基于对视听自然主义刺激有选择性反应的区域内的分布式活动模式,在参与者内部和参与者之间识别个体试验的效价和唤醒水平。此外,通过探照灯分析确定的代表效价和唤醒水平的脑区与先前确定的与情绪处理相关的区域一致。这些发现将先前关于情感分布式表征的结果扩展到了多模态动态刺激。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2a8/5012606/65c2b29a3d96/pone.0161589.g001.jpg

相似文献

1
Identifying Core Affect in Individuals from fMRI Responses to Dynamic Naturalistic Audiovisual Stimuli.
PLoS One. 2016 Sep 6;11(9):e0161589. doi: 10.1371/journal.pone.0161589. eCollection 2016.
2
Decoding the neural representation of affective states.
Neuroimage. 2012 Jan 2;59(1):718-27. doi: 10.1016/j.neuroimage.2011.07.037. Epub 2011 Jul 23.
3
Decoding dynamic affective responses to naturalistic videos with shared neural patterns.
Neuroimage. 2020 Aug 1;216:116618. doi: 10.1016/j.neuroimage.2020.116618. Epub 2020 Feb 7.
4
A study in affect: Predicting valence from fMRI data.
Neuropsychologia. 2020 Jun;143:107473. doi: 10.1016/j.neuropsychologia.2020.107473. Epub 2020 Apr 22.
6
Distinct brain systems underlie the processing of valence and arousal of affective pictures.
Brain Cogn. 2009 Dec;71(3):387-96. doi: 10.1016/j.bandc.2009.05.007. Epub 2009 Aug 8.
7
Arousal modulates valence effects on both early and late stages of affective picture processing in a passive viewing task.
Soc Neurosci. 2014;9(4):364-77. doi: 10.1080/17470919.2014.896827. Epub 2014 Mar 7.
8
Comparing three models of arousal in the human brain.
Soc Cogn Affect Neurosci. 2020 Jan 30;15(1):1-11. doi: 10.1093/scan/nsaa012.
9
Differences in neural activity when processing emotional arousal and valence in autism spectrum disorders.
Hum Brain Mapp. 2016 Feb;37(2):443-61. doi: 10.1002/hbm.23041. Epub 2015 Nov 3.
10
Distinct cerebellar lobules process arousal, valence and their interaction in parallel following a temporal hierarchy.
Neuroimage. 2015 Apr 15;110:149-61. doi: 10.1016/j.neuroimage.2015.02.006. Epub 2015 Feb 7.

引用本文的文献

2
Functional brain connectivity changes associated with day-to-day fluctuations in affective states.
Cogn Affect Behav Neurosci. 2024 Dec;24(6):1141-1154. doi: 10.3758/s13415-024-01216-6. Epub 2024 Sep 25.
5
Audiovisual Representations of Valence: a Cross-study Perspective.
Affect Sci. 2020 Nov 25;1(4):237-246. doi: 10.1007/s42761-020-00023-9. eCollection 2020 Dec.
6
Representing the Good and Bad: fMRI signatures during the encoding of multisensory positive, negative, and neutral events.
Cortex. 2022 Jun;151:240-258. doi: 10.1016/j.cortex.2022.02.014. Epub 2022 Mar 28.
7
Test-retest reliability of dynamic functional connectivity in naturalistic paradigm functional magnetic resonance imaging.
Hum Brain Mapp. 2022 Mar;43(4):1463-1476. doi: 10.1002/hbm.25736. Epub 2021 Dec 6.
8
Predictive processing models and affective neuroscience.
Neurosci Biobehav Rev. 2021 Dec;131:211-228. doi: 10.1016/j.neubiorev.2021.09.009. Epub 2021 Sep 10.
9
Negative content enhances stimulus-specific cerebral activity during free viewing of pictures, faces, and words.
Hum Brain Mapp. 2020 Oct 15;41(15):4332-4354. doi: 10.1002/hbm.25128. Epub 2020 Jul 7.
10
Distinct neural mechanisms underlying conceptual knowledge of manner and instrument verbs.
Neuropsychologia. 2019 Oct;133:107183. doi: 10.1016/j.neuropsychologia.2019.107183. Epub 2019 Sep 4.

本文引用的文献

1
Differences in neural activity when processing emotional arousal and valence in autism spectrum disorders.
Hum Brain Mapp. 2016 Feb;37(2):443-61. doi: 10.1002/hbm.23041. Epub 2015 Nov 3.
2
Conjunctive Coding of Complex Object Features.
Cereb Cortex. 2016 May;26(5):2271-2282. doi: 10.1093/cercor/bhv081. Epub 2015 Apr 28.
3
Visual representations are dominated by intrinsic fluctuations correlated between areas.
Neuroimage. 2015 Jul 1;114:275-86. doi: 10.1016/j.neuroimage.2015.04.026. Epub 2015 Apr 17.
4
Abstract representations of associated emotions in the human brain.
J Neurosci. 2015 Apr 8;35(14):5655-63. doi: 10.1523/JNEUROSCI.4059-14.2015.
5
Multivariate neural biomarkers of emotional states are categorically distinct.
Soc Cogn Affect Neurosci. 2015 Nov;10(11):1437-48. doi: 10.1093/scan/nsv032. Epub 2015 Mar 25.
6
The Brain Basis of Positive and Negative Affect: Evidence from a Meta-Analysis of the Human Neuroimaging Literature.
Cereb Cortex. 2016 May;26(5):1910-1922. doi: 10.1093/cercor/bhv001. Epub 2015 Jan 28.
7
Emotion recognition in animated compared to human stimuli in adolescents with autism spectrum disorder.
J Autism Dev Disord. 2015 Jun;45(6):1785-96. doi: 10.1007/s10803-014-2338-9.
8
Neural processing of emotion in multimodal settings.
Front Hum Neurosci. 2014 Oct 21;8:822. doi: 10.3389/fnhum.2014.00822. eCollection 2014.
9
Population coding of affect across stimuli, modalities and individuals.
Nat Neurosci. 2014 Aug;17(8):1114-22. doi: 10.1038/nn.3749. Epub 2014 Jun 22.
10
GLMdenoise: a fast, automated technique for denoising task-based fMRI data.
Front Neurosci. 2013 Dec 17;7:247. doi: 10.3389/fnins.2013.00247. eCollection 2013.

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