研究自闭症儿童处理汉语递归句的脑电反应,发现预测能力弱导致理解负担重。
An ERP Study on Recursive Locative Processing in Mandarin-Speaking Children with Autism
- 用脑电图分析自闭症与正常儿童对嵌套方位句的实时加工
- 自闭症儿童早期预测反应弱、后期修正能力差,但语义整合更吃力
- 结果提示语言困难源于时间动态和神经差异,适合关注发展障碍者
递归能力支持层级语言结构生成,但在实时理解中带来显著加工负担。尽管自闭症谱系障碍(ASD)存在复杂句法困难,其递归加工的时间动态仍不清楚。本研究采用事件相关电位(ERPs)考察汉语自闭症儿童对双层递归方位结构的处理。24名儿童参与(12名ASD,12名典型发育TD),完成跨模态句图匹配任务,控制心理年龄。分析三个阶段:结构预测(P200)、语义整合(N400)和句法再分析(P600)。结果显示组间系统性差异:TD儿童在结构错配时表现出明显的P200与P600调制,而ASD儿童早期分化减弱、晚期再分析效应降低;相反,ASD儿童在错配条件下出现增强的N400反应,表明语义整合成本更高。此外,ASD组在半球偏侧化上表现出显著更大的个体差异,但偏侧化强度与接受性词汇量无关。这些发现支持一个级联模型:自闭症中早期预测参与减少,导致整合代价上升且再分析效率下降。更广泛而言,结果强调了时间加工动态与神经变异性在理解自闭症语言差异中的重要性。
原文摘要 · Abstract (English)
Recursion enables the generation of hierarchical linguistic structures but imposes substantial processing demands during real-time comprehension. While difficulties with complex syntax have been reported in autism spectrum disorder (ASD), the temporal dynamics of recursive processing remain poorly understood. This study used event-related potentials (ERPs) to examine how Mandarin-speaking children with ASD process two-level recursive locative constructions. Twenty-four children (12 ASD, 12 typically developing, TD) participated in a cross-modal sentence-picture matching task. Neural responses were analyzed across three processing stages associated with structural prediction (P200), semantic integration (N400), and syntactic reanalysis (P600), with mental age controlled. Results revealed a systematic divergence between groups. TD children showed clear P200 and P600 modulation in response to structural mismatch, whereas ASD children exhibited attenuated early differentiation and reduced late reanalysis effects. In contrast, ASD children showed enhanced N400 responses under mismatch conditions, indicating increased semantic integration demands. In addition, the ASD group displayed significantly greater inter-individual variability in hemispheric lateralization, although lateralization strength was not associated with receptive vocabulary performance. These findings support a cascading account in which reduced early predictive engagement in ASD leads to increased integration costs and diminished reanalysis efficiency during recursive processing. More broadly, the results highlight the importance of both temporal processing dynamics and neural variability in understanding language differences in ASD.
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