重新思考在自闭症中进行的制作:从个体差异和网络分析方法中获得细微的见解
Talia Liu1, Kelsey E Davison1, Ayelet M Kershenbaum2
1Department of Speech, Language & Hearing Sciences, Boston University, MA.
Journal of speech, language, and hearing research : JSLHR
|January 14, 2026
概括
自闭症儿童表现出明显的音调模式和较慢的语音速度,但这些在个体上有所不同. 网络分析揭示了自闭症中的异常差异是复杂的,并且在所有自闭症患者中不均.
科学领域:
- 语音和听力科学 语言和听力科学
- 发展心理学 发展心理学
- 神经发育障碍 神经发育障碍
背景情况:
- 在自闭症中认可了prosodic差异,但由于异质性,缺乏一致的表征.
- 现有的研究往往产生了关于"自闭症声音"的特定声学标记的混合发现.
研究的目的:
- 调查在自闭症和非自闭症儿童和青少年中散文的细微差别.
- 探索个体差异,并应用网络分析来理解自闭症中的前性变异.
主要方法:
- 从66名学龄自闭症和非自闭症参与者的叙事演讲声学分析.
- 基调和时刻特征的群体间比较,随后进行群体内部分析,将曲与语言技能相关联.
- 网络分析以基于共享的prosodic配置文件来识别参与者社区.
主要成果:
- 与非自闭症同龄人相比,自闭症参与者表现出更大的音调范围和变化.
- 在自闭症患者中观察到语音和发音速度较慢,这与整体语言能力有关.
- 社区检测发现了三个prosodic集群,其中自闭症个体分布在它们之间,而不是形成不同的群体.
结论:
- 在自闭症中,prosody的特点是多样化的模式,支持"以不同的方式不同"的想法.
- 强调需要超越简单的群体比较,以了解自闭症中的个体前性差异.
- 突出了群体内部和数据驱动方法的价值,以获得对自闭症的细微洞察力.
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