Data_Sheet_8_Atypical low-frequency cortical encoding of speech identifies children with developmental dyslexia.PDF

Slow cortical oscillations play a crucial role in processing the speech amplitude envelope, which is perceived atypically by children with developmental dyslexia. Here we use electroencephalography (EEG) recorded during natural speech listening to identify neural processing patterns involving slow oscillations that may characterize children with dyslexia. In a story listening paradigm, we find that atypical power dynamics and phase-amplitude coupling between delta and theta oscillations characterize dyslexic versus other child control groups (typically-developing controls, other language disorder controls). We further isolate EEG common spatial patterns (CSP) during speech listening across delta and theta oscillations that identify dyslexic children. A linear classifier using four delta-band CSP variables predicted dyslexia status (0.77 AUC). Crucially, these spatial patterns also identified children with dyslexia when applied to EEG measured during a rhythmic syllable processing task. This transfer effect (i.e., the ability to use neural features derived from a story listening task as input features to a classifier based on a rhythmic syllable task) is consistent with a core developmental deficit in neural processing of speech rhythm. The findings are suggestive of distinct atypical neurocognitive speech encoding mechanisms underlying dyslexia, which could be targeted by novel interventions.

慢皮层振荡在言语振幅包络的加工过程中发挥关键作用，而发展性阅读障碍儿童对该包络的感知存在异常。本研究采用自然言语聆听过程中采集的脑电图（electroencephalography, EEG）数据，旨在识别与阅读障碍儿童特征相关的、涉及慢皮层振荡的神经加工模式。在故事聆听实验范式中，我们发现相较于典型发育对照组及其他语言障碍对照组，阅读障碍组的δ节律与θ节律间存在异常的功率动态及相位振幅耦合特征。我们进一步分离出言语聆听过程中跨δ与θ节律的EEG公共空间模式（common spatial patterns, CSP），该模式可用于识别阅读障碍儿童。采用4个δ波段公共空间模式变量构建的线性分类器，对阅读障碍状态的预测曲线下面积（AUC）达0.77。尤为重要的是，当将这些空间模式应用于节奏性音节加工任务中采集的EEG数据时，同样能够有效识别阅读障碍儿童。这种迁移效应——即通过故事聆听任务提取的神经特征可作为分类器输入特征，应用于节奏性音节加工任务的分类——与言语节律神经加工中存在的核心发育缺陷相一致。本研究结果表明，阅读障碍背后存在独特的异常神经认知言语编码机制，可为新型干预手段提供靶向方向。