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.

项目概要/摘要 定义阅读障碍的阅读困难的最常见和最容易理解的原因是阅读障碍的改变 口语的处理。据报道，阅读障碍患者的言语感知缺陷 几十年来，新兴的文献描述了依赖于利用规律性的行为缺陷。 感觉环境，以及神经对持续刺激的适应能力降低。因为高效的演讲 处理依赖于特定声音的声学特征的快速可塑性，以及语义 预测受到上下文的限制，听觉皮层层次结构中的快速可塑性损伤是一个候选者 阅读障碍的核心缺陷。在这里，我们探讨是否由于短期经验和/或顶部而导致可塑性降低 低期望是阅读障碍患者言语感知的特征。通过记录脑磁图（MEG） 当个人听单词对时，我们将确定可预测性如何差异调节神经 阅读障碍的反应。目标 1 是表征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能力下降是由于自下而上还是自上而下造成的 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，揭示出高时空细节 神经群体如何编码这些特征。减弱的重复抑制表明听觉 由于词形和语音的短期经验，系统变化较小，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误差 阅读障碍患者的言语缺陷。我们将通过衡量对以下问题的反应来评估自上而下的期望抑制 一对语音刺激，听众对刺激重复的期望很高。符合一个 预测编码帐户，我们预计满足的期望将产生很少的响应，而违反 期望会引起较大的预测误差响应，表明需要更新预测。在阅读障碍中， 这些现象的异常表明对语音语音和/或单词音系的预测不充分， 暗示着高阶赤字。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，调查特征在预测时与预测时是否更早、更稳健地出现。 不可预测，正如自上而下的影响所解释的那样。我们将调查是否存在个体差异 分类器的准确性与神经预测误差的大小和语言能力相关。这些 目的是促进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/或语音特征预测不充分而导致的可塑性降低可能会阻止 大脑建立和更新构成儿童学习基础的语音-语音关系模型 语音意识、声音到印刷品的映射，以及最终的阅读。