Jove
Visualize
联系我们

相关概念视频

Labeling Emotion01:20

Labeling Emotion

775
Emotional labeling is a cognitive process that involves identifying and naming one's emotions, such as anger, fear, happiness, or sadness. It allows individuals to recognize and express their internal emotional states, a critical aspect of emotional regulation and communication. Labeling emotions requires more than mere recognition; it also involves drawing upon memory and contextual cues to understand the current situation and apply a corresponding emotional label. For instance, feeling...
775
Physiology of Emotion01:20

Physiology of Emotion

3.6K
The physiology of emotions is a multifaceted process involving the autonomic nervous system, brain structures, hormones, and neurotransmitters. This intricate interplay dictates how emotions manifest in the body and influence behavior.
Autonomic Nervous System
The autonomic nervous system (ANS) plays a critical role in emotional responses by regulating involuntary physiological functions. It consists of two main components: the sympathetic and parasympathetic systems. The sympathetic system...
3.6K
Cognitive Theories: Schachter-Singer Theory of Emotion01:20

Cognitive Theories: Schachter-Singer Theory of Emotion

2.0K
Stanley Schachter and Jerome Singer proposed the two-factor theory of emotion, which emphasizes the interplay between physiological arousal and cognitive labeling in forming emotional experiences. This theory suggests that emotions are not simply a result of physiological responses but rather a combination of these responses and the individual's cognitive interpretation of them.
Physiological Arousal and Cognitive Labeling
According to this theory, when an individual experiences...
2.0K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

FDSNet: Frequency-Decoupled Stack Fusion Network for Light Field All-in-Focus Image Generation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same author

Genetic diversity, codon usage, and evolutionary dynamics of bovine parainfluenza virus type-3.

The Journal of veterinary medical science·2025
Same author

Graph attention-driven relation network for 3D lane detection.

Scientific reports·2025
Same author

MentalQLM: A Lightweight Large Language Model for Mental Healthcare Based on Instruction Tuning and Dual LoRA Modules.

IEEE journal of biomedical and health informatics·2025
Same author

Theoretical Analysis and Characteristic Study of Li-Doped P-Type ZnO Ultra-Thin Cantilever Beam Accelerometer.

Materials (Basel, Switzerland)·2025
Same author

Phenotypic discrimination and characterization of microbial populations in enhanced biological phosphorus removal using single-cell raman spectroscopy-based methods.

Water research·2025
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关实验视频

Updated: Feb 26, 2026

Cross-Modal Multivariate Pattern Analysis
13:51

Cross-Modal Multivariate Pattern Analysis

Published on: November 9, 2011

20.6K

MMSTG-Net:具有跨模态对比对齐的多尺度时空图形网络,用于多模态情感识别.

Jiayu Bi, Linjun Lu, Poly Z H Sun

    IEEE journal of biomedical and health informatics
    |February 24, 2026
    PubMed
    概括

    这项研究介绍了MMSTG-Net,这是一种使用EEG和眼睛跟踪进行情绪识别的新型多式联络网络. 它显示出作为临床情绪评估的研究工具的希望,等待进一步验证.

    科学领域:

    • 神经科学是一个神经科学.
    • 计算机科学 计算机科学
    • 精神病学是一个精神病学.

    背景情况:

    • 精神病学当前的情绪识别方法依赖于主观和时间有限的自我报告.
    • 需要客观,细粒度的情绪评估工具.

    研究的目的:

    • 开发一个多式时空图网络 (MMSTG-Net),用于精确的情感分类.
    • 共同建模时间动态,大脑连接和EEG和眼睛跟踪的交叉模式数据.

    主要方法:

    • 开发了MMSTG-Net,这是一个多式模式的时空图形网络.
    • 使用脑电图 (EEG) 和眼睛跟踪数据.
    • 在SEED-VII和SEED-IV公共数据集上进行评估,用于七类情绪分类.

    主要成果:

    • 在SEED-VII数据集上取得了最先进的表现 (82.74%的学科依赖,63.06%的跨学科).
    • 在SEED-IV数据集上获得了竞争性结果 (87.50%取决于学科,84.85%跨学科).
    • 废弃性研究证实了单个网络模块和融合设计的有效性.

    结论:

    • MMSTG-Net在使用EEG和眼睛跟踪的情绪识别方面表现出强的表现.

    更多相关视频

    Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
    06:37

    Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

    Published on: December 15, 2023

    5.5K

    相关实验视频

    Last Updated: Feb 26, 2026

    Cross-Modal Multivariate Pattern Analysis
    13:51

    Cross-Modal Multivariate Pattern Analysis

    Published on: November 9, 2011

    20.6K
    Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
    06:37

    Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

    Published on: December 15, 2023

    5.5K
  • 该模型显示了作为研究工具的潜力,以帮助未来的临床情绪评估.
  • 临床应用需要进一步的多中心,前性验证.