量化异常情绪处理:一种新的计算评估方法和在精神分裂症中的应用
Ellen R Bradley1, Jake Portanova2, Josh D Woolley1
1Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA; San Francisco Veterans Affairs Medical Center, CA, USA.
Psychiatry research
|April 24, 2024
概括
精神分裂症谱系障碍 (SSD) 损害了口语中的情感对齐. 一种新的深度学习方法对评估这种缺陷和通过催产素改善这一缺陷有希望.
科学领域:
- 神经科学是一个神经科学.
- 精神病学是一个精神病学.
- 计算语言学 计算语言学
背景情况:
- 异常的情绪处理是精神分裂症谱系障碍 (SSD) 的核心.
- 通过语言处理情绪对于社会功能至关重要,但在SSD中理解较少.
- 评估情绪处理的现有方法是有限的.
研究的目的:
- 介绍和验证一种新的深度学习方法,用于评估口语语言中的情感处理.
- 与对照组相比,研究男性确诊的SSD患者的情绪对齐 (EA).
- 为了检查催产素对EA和SSD中的形式思维障碍 (FTD) 的影响.
主要方法:
- 开发了一个深度学习模型,从口语中推导出"情感对齐" (EA) 度量.
- 在使用自由反应的SSD (n=37) 和健康对照 (n=51) 的男性患者中测试了该方法.
- 在患者中服用了催产素,并评估了EA和FTD的变化.
主要成果:
- 与对照组相比,SSD患者的EA显著受损.
- 损伤的EA与社会认知,动机和快乐的缺陷相关.
- 当被添加到FTD措施中时,EA改善了SSD的分类.
- 催产素的使用增强了患者的EA,但没有影响FTD.
结论:
- 从口语中自动评估情绪对齐是SSD的一个有希望的工具.
- EA赤字与SSD中的核心症状领域有关.
- 氧化可能会增强SSD中的社会情绪处理,根据EA测量.
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