Neural tracking of natural speech in children in relation to their receptive speech abilities

IF 2.1 3区 心理学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Anton Rogachev , Olga Sysoeva
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引用次数: 0

Abstract

Receptive speech is the ability to understand speech addressed to a person. It is a crucial process for a child’s cognitive development. We examine the relationship between receptive speech and neural tracking of natural speech in 52 children aged 3–8 years to infer the neurophysiological mechanisms underlying speech development. We registered a 32-channel electroencephalogram (EEG) while children listened to narrative audio stories. The temporal response function (TRF) approach was used to study neural tracking features at acoustic and semantic levels. We found a strong positive correlation between the TRF prediction accuracy values that demonstrate the magnitude of neural tracking, and receptive speech abilities measured by the Preschool Language Scales (PLS-5). Topographic analysis of these correlations showed significant clusters of EEG channels in the right temporal region for acoustic tracking, and in the left fronto-central and right parieto-occipital regions for semantic tracking. We assume that these results reflect the development of the brain systems necessary for speech comprehension. To sum up, we suggest that the TRF measures are easy-to-assess neurophysiological markers of receptive speech development in children.

儿童自然语音的神经跟踪与接受语音能力的关系
感知语言是指理解对人讲话的能力。这是儿童认知发展的关键过程。我们研究了 52 名 3-8 岁儿童的接受言语与自然言语神经跟踪之间的关系,以推断言语发展的神经生理机制。我们在儿童聆听叙事性音频故事时记录了 32 通道脑电图 (EEG)。我们采用时间反应函数(TRF)方法研究了声学和语义层面的神经跟踪特征。我们发现,TRF 预测准确度值与学前语言量表(PLS-5)测量的接受性言语能力之间存在很强的正相关性,而TRF 预测准确度值可证明神经跟踪的程度。对这些相关性的拓扑分析表明,声学追踪的脑电图通道在右侧颞区,语义追踪的脑电图通道在左侧前中央区和右侧顶枕区。我们认为,这些结果反映了语音理解所需的大脑系统的发展。总之,我们认为 TRF 测量是儿童接受性言语发展的易于评估的神经生理学标记。
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来源期刊
Cognitive Systems Research
Cognitive Systems Research 工程技术-计算机:人工智能
CiteScore
9.40
自引率
5.10%
发文量
40
审稿时长
>12 weeks
期刊介绍: Cognitive Systems Research is dedicated to the study of human-level cognition. As such, it welcomes papers which advance the understanding, design and applications of cognitive and intelligent systems, both natural and artificial. The journal brings together a broad community studying cognition in its many facets in vivo and in silico, across the developmental spectrum, focusing on individual capacities or on entire architectures. It aims to foster debate and integrate ideas, concepts, constructs, theories, models and techniques from across different disciplines and different perspectives on human-level cognition. The scope of interest includes the study of cognitive capacities and architectures - both brain-inspired and non-brain-inspired - and the application of cognitive systems to real-world problems as far as it offers insights relevant for the understanding of cognition. Cognitive Systems Research therefore welcomes mature and cutting-edge research approaching cognition from a systems-oriented perspective, both theoretical and empirically-informed, in the form of original manuscripts, short communications, opinion articles, systematic reviews, and topical survey articles from the fields of Cognitive Science (including Philosophy of Cognitive Science), Artificial Intelligence/Computer Science, Cognitive Robotics, Developmental Science, Psychology, and Neuroscience and Neuromorphic Engineering. Empirical studies will be considered if they are supplemented by theoretical analyses and contributions to theory development and/or computational modelling studies.
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