在精神分裂症和抑郁症中,语言流性任务执行的独特特征在精神分裂症和抑郁症中
Sunghye Cho1, Yan Cong2, Aarush Mehta3,4
1Linguistic Data Consortium & Linguistics Department, University of Pennsylvania, Philadelphia, PA, USA.
Schizophrenia research. Cognition
|December 11, 2025
概括
精神分裂症和抑郁症患者表现出明显的语言流利模式,特别是在类别任务中. 自动化分析有助于区分精神病诊断中的认知语言障碍.
科学领域:
- 认知神经科学 认知神经科学
- 精神疾病 精神疾病
- 语言学的语言学.
背景情况:
- 语言流任务对于理解精神分裂症 (SSD) 中的语义和认知处理至关重要.
- 有限的研究将SSD的口头流利与其他精神疾病进行比较,阻碍了独特与共享障碍的识别.
- 这项研究旨在通过比较SSD,单极抑郁症和健康志愿者的口头流利来区分认知语言缺陷.
研究的目的:
- 为了比较精神分裂症,单极抑郁症和健康志愿者的口头流利表现.
- 调查观察到的口语流性障碍是否与精神分裂症特异或在诊断中普遍存在.
- 探索自动化分析在识别精神病患者群体中独特的认知语言模式的实用性.
主要方法:
- 64名SSD患者,70名单极性抑郁症患者和37名健康志愿者完成了字母和类别指导的口头流利任务.
- 自动管道提取了包括总响应,暂停持续时间,响应延迟,语义/语音距离和集群特征在内的指标.
- 在患者组内,分析了流利度指标和语音障碍临床评级之间的关联.
主要成果:
- 观察到总流利度得分的显著差异,SSD的损害最大,抑郁症的中间影响最大,特别是在类别流利性任务上.
- 语义和语音集群的数量在各组之间有显著差异,而集群大小显示的变化较少.
- 健康的志愿者表现出战略集群切换 (增加语义/语音距离与更长的暂停),这种模式在SSD和抑郁症组中不存在. SSD显示延长的延迟和暂停,而抑郁症显示延长的暂停但正常的延迟.
结论:
- 精神分裂症和抑郁症表现出不同的口语流模式,类别任务突出了更明显的群体差异.
- 自动化口语流性分析提供了一种可扩展的方法,用于在不同精神病患者群体中区分认知语言障碍.
- 这些发现有助于更好地了解精神健康障碍中认知缺陷的异质性.
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