Understanding individual differences in facial emotion perception and their association with psychiatric risk indicators

了解面部情绪感知的个体差异及其与精神风险指标的关联

• 批准号: MR/S011307/1
• 负责人: Isabelle Mareschal
• 金额: $ 92.11万
• 依托单位: Queen Mary University of London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FS011307%2F1
• 关键词: Understanding; individual; differences; facial; emotion

We use facial expressions to communicate our emotions but there are large differences in how people react to these expressions. At its most severe, failures to respond appropriately to emotional expressions are associated with many clinical conditions. For example, people with high anxiety often report that what other people perceive as neutral expressions appear threatening to them. Critically, the reason why these expressions look different to certain individuals remains unknown. Without this knowledge, it is very difficult to develop targeted and effective therapies for people suffering, for example, from anxiety or other disorders. The aim of this project is to understand why some people are unable to correctly respond to, or identify, particular emotional expressions, and how this relates to indicators of psychiatric risk. We have recently created a unique toolkit that allows us to measure how emotional expressions look to different people. We will use our toolkit to allow individuals to create the facial expressions that they associate with particular emotions. These individualised emotional expressions will allow us to understand the basis of individual differences in emotional expression perception and how they are associated with psychiatric risk indicators. We will establish if these evolved expressions improve current clinical and pre-clinical tests of "emotional processing" using standard, pre-validated tasks. The result of this work will be an improved understanding of how emotional expressions are interpreted in typical and atypical populations, new tools for better characterization of individuals at risk of psychiatric disorders, and therefore the potential for more precise diagnosis and treatment of these disorders.

我们用面部表情来传达我们的情绪，但人们对这些表情的反应有很大的不同。在最严重的情况下，无法对情绪表达做出适当的反应与许多临床状况有关。例如，高度焦虑的人经常报告说，其他人认为中性的表情对他们来说似乎是威胁。至关重要的是，这些表情在某些人看来不同的原因仍然未知。没有这方面的知识，就很难为患有焦虑症或其他疾病的人开发有针对性和有效的治疗方法。该项目的目的是了解为什么有些人不能正确地回应或识别特定的情绪表达，以及这与精神风险指标之间的关系。我们最近创建了一个独特的工具包，可以让我们衡量不同人的情绪表达。我们将使用我们的工具包来允许个人创造与特定情绪相关联的面部表情。这些个性化的情绪表达将使我们了解情绪表达感知的个体差异的基础，以及它们如何与精神风险指标相关联。我们将通过使用标准的、预先验证的任务来确定这些进化的表达是否改善了当前“情绪处理”的临床和临床前测试。这项工作的结果将是提高对典型和非典型人群如何解释情绪表达的理解，为更好地表征有精神疾病风险的个体提供新工具，因此有可能更精确地诊断和治疗这些疾病。

项目成果

Genetic algorithms reveal profound individual differences in emotion recognition.

• DOI: 10.1073/pnas.2201380119
• 发表时间: 2022-11-08
• 期刊: Proceedings of the National Academy of Sciences of the United States of America
• 影响因子: 11.1

Asymmetric contextual effects in age perception.

• DOI: 10.1098/rsos.200936
• 发表时间: 2020-12
• 期刊: Royal Society open science
• 影响因子: 3.5
• 作者: Awad D;Clifford CWG;White D;Mareschal I
• 通讯作者: Mareschal I

Using genetic algorithms to uncover individual differences in how humans represent facial emotion.

• DOI: 10.1098/rsos.202251
• 发表时间: 2021-10
• 期刊: Royal Society open science
• 影响因子: 3.5
• 作者: Carlisi CO;Reed K;Helmink FGL;Lachlan R;Cosker DP;Viding E;Mareschal I
• 通讯作者: Mareschal I