Predictive coding in typical speech perception and dyslexia

典型语音感知和阅读障碍的预测编码

• 批准号: 10005028
• 负责人: Sara Dawley Beach
• 金额: $ 3.37万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-12-01 至 2021-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10005028
• 关键词: Acoustics; Affect; Attenuated; Auditory; Auditory system; Base of the Brain; Behavior; Behavioral; Brain; Brain imaging; Brain region; Categories; Characteristics; Child; Classification; Code; Cognitive; Complement; Coupled; Data; Detection; Developmental Communication Disorders; Dyslexia; Environment; Esthesia; Exhibits; Goals; Impairment; Individual; Individual Differences; Inherited; Knowledge; Language; Lead; Learning; Learning Disabilities; Literature; Magnetoencephalography; Measures; Modeling; Neurobiology; Pattern; Perceptual learning; Phonetics; Population; Process; Reading; Reporting; Resolution; Role; Semantics; Sensory; Signal Transduction; Speech; Speech Perception; Stimulus; Structure; System; Techniques; Therapeutic; Time; Training; Update; Voice; auditory stimulus; expectation; experience; improved; insight; language processing; learning ability; literacy; neural patterning; neuroadaptation; neuromechanism; neuroregulation; neurotransmission; novel; phonological awareness; phonology; prevent; reading difficulties; relating to nervous system; response; sensory input; skills; sound; spatiotemporal; speech processing; statistical learning; voice recognition

PROJECT SUMMARY/ABSTRACT The most common and best understood cause of the reading difficulty that defines dyslexia is an alteration in the processing of spoken language. While speech perception deficits in dyslexia have been reported for decades, a burgeoning literature describes behavioral deficits that rely on the exploitation of regularities in the sensory environment, as well as reduced neural adaptation to consistent stimulation. Because efficient speech processing relies on rapid plasticity for acoustic features characteristic of particular voices, coupled to semantic predictions constrained by context, a rapid plasticity impairment in the auditory cortical hierarchy is a candidate core deficit in dyslexia. Here we explore whether reduced plasticity due to short-term experience and/or top- down expectation characterizes speech perception in dyslexia. By recording magnetoencephalography (MEG) while individuals listen to pairs of words, we will determine how predictability differentially modulates neural responses in dyslexia. Aim 1 is to characterize the spatiotemporal patterns of auditory repetition suppression deficits in dyslexia. It is not known whether reduced neural adaptation is due to bottom-up or top-down mechanisms. We will assess bottom-up repetition suppression by measuring responses to pairs of speech stimuli in which the word, voice, or both are repeated unexpectedly, revealing with high spatiotemporal detail how neural populations encode these features. Attenuated repetition suppression suggests that the auditory system changes less due to short-term experience with word forms and voices, which may be a core neurobiological difference in dyslexia. Aim 2 is to characterize expectation suppression and prediction error deficits for speech in dyslexia. We will assess top-down expectation suppression by measuring responses to pairs of speech stimuli in which listeners have high expectation that stimuli will repeat. Consistent with a predictive coding account, we expect that fulfilled expectations will generate little response, while violated expectations will evoke large prediction error responses, signaling a need to update the prediction. In dyslexia, abnormalities in these phenomena suggest inadequate prediction of voice phonetics and/or word phonology, implicating a higher-order deficit. Aim 3 is an exploratory quantification of the emergence of expected stimulus feature encoding in neural signals. We will train a neural pattern classifier to distinguish words and voices from the MEG data, investigating whether features emerge earlier and more robustly when they are predicted vs. unpredicted, as would be explained by top-down influences. We will investigate whether individual differences in classifier accuracy correlate with the magnitude of neural prediction error and with language abilities. These aims advance a mechanistic understanding of speech processing differences that can lead to dyslexia. Reduced plasticity due to short-term experience and/or inadequate prediction of speech features may prevent the brain from building and updating models of phonetic-phonological relationships that underlie children's phonological awareness, sound-to-print mapping, and, ultimately, reading.

项目摘要/摘要 定义阅读障碍的阅读困难的最常见和最佳理解的原因是改变 口语的处理。据报道，阅读障碍的语音感知缺陷 几十年来，新兴的文献描述了依赖于规律性剥削的行为缺陷 感觉环境以及减少对一致刺激的神经适应性。因为有效的语音 处理依赖于特定声音特征的声学特征的快速可塑性，并耦合语义 受到上下文限制的预测，听觉皮层层次结构中的可塑性障碍是候选者 阅读障碍的核心赤字。在这里，我们探讨是否由于短期经验和/或顶部而降低了可塑性 降低的期望是阅读障碍中的语音感知。通过录制磁脑电图（MEG） 当个人听单词对时，我们将确定可预测性如何差异化神经 阅读障碍的反应。目的1是表征听觉重复抑制的时空模式 阅读障碍的缺陷。尚不清楚神经适应性减少是由于自下而上还是自上而下 机制。我们将通过测量对语音对的反应来评估自下而上的重复抑制 单词，声音或两者都意外重复的刺激，以高时空的细节揭示 神经种群如何编码这些特征。减弱的重复抑制表明听觉 由于具有单词形式和声音的短期经验，系统变化较少，这可能是核心 阅读障碍的神经生物学差异。目标2是表征期望抑制和预测错误 阅读障碍的言语缺陷。我们将通过衡量对 言语刺激对，听众对刺激会重复的期望很高。与a一致 预测性编码帐户，我们期望满足的期望几乎不会产生响应，而违反 期望将引起大量预测错误响应，这表明需要更新预测。在阅读障碍中， 这些现象中的异常表明语音语音和/或单词语音的预测不足， 暗示高阶赤字。 AIM 3是对预期刺激的出现的探索性量化 神经信号中编码的功能。我们将训练一个神经模式分类器，以区分单词和声音 MEG数据，调查特征在预测VS时是否提早出现，更强大地出现。 自上而下的影响所解释的那样，没有预测。我们将调查个体差异是否存在 在分类器中，精度与神经预测错误的大小以及语言能力相关。这些 目的是对可能导致阅读障碍的语音处理差异的机械理解。 由于短期经验和/或语音特征的预测不足可能导致可塑性降低 建立和更新语音 - 主持关系模型的大脑，这是儿童的基础 语音意识，声音到印刷映射以及最终阅读。