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 定义阅读困难的最常见和最被理解的原因是阅读障碍的改变 对口语的处理。而阅读障碍的言语感知缺陷已经被报道为 几十年来，一种新兴的文献描述了依赖于对规则的利用的行为缺陷 感觉环境，以及神经对持续刺激的适应性降低。因为高效的语音 加工依赖于特定声音的声学特征的快速可塑性，与语义相结合 受语境限制的预测，听觉皮质结构中的快速可塑性损害是一个候选因素 阅读障碍的核心缺陷。在这里，我们探索短期经验和/或顶部是否会降低可塑性- 阅读困难症患者的言语知觉表现为向下期望。通过记录脑磁图(MEG) 当个体听成对的单词时，我们将确定可预测性如何差异化地调制神经 阅读障碍患者的反应。目标1是描述听觉重复抑制的时空模式 阅读障碍的缺陷。目前尚不清楚神经适应性降低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 一种刺激，其中单词、声音或两者都意外地重复，具有很高的时空细节 神经群体如何对这些特征进行编码。减弱的重复抑制表明，听觉 由于短期的词形和语音经验，系统变化较少，这可能是一个核心 阅读障碍的神经生物学差异。目标2是描述期望抑制和预测误差 阅读困难症患者的言语缺陷。我们将通过衡量对以下方面的反应来评估自上而下的预期抑制 语言刺激对，听者对刺激重复的期望很高。与一项 预测编码帐户，我们预计满足预期将不会产生什么反应，而违反 预期将引起较大的预测误差响应，表明需要更新预测。在阅读困难症中， 这些现象中的异常表明对语音和/或单词音系学的预测不足， 暗示存在更高级别的赤字。目标3是对预期刺激出现的探索性量化 神经信号中的特征编码。我们将训练一个神经模式分类器来区分单词和声音 MEG数据，调查特征在预测时是否出现得更早、更稳健，而不是 不可预测的，可以用自上而下的影响来解释。我们将调查个体差异是否 在分类器中，准确率与神经预测误差的大小和语言能力相关。这些 AIMS促进了对语音处理差异的机械性理解，这些差异可能导致阅读困难。 由于短期经验和/或对语音特征的预测不足而导致的可塑性降低可能会阻止 大脑通过构建和更新语音-语音关系模型来支持儿童的 语音意识，声音到印刷品的映射，最终是阅读。