Explaining aphasic impairment in the context of contemporary models of speech and language processing

在当代言语和语言处理模型的背景下解释失语症障碍

• 批准号: 9083048
• 负责人: Gregory Hickok
• 金额: $ 32.74万
• 依托单位: UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/9083048
• 关键词: Accounting; Affect; Aphasia; Area; Assessment tool; Auditory; Back; Basic Science; Behavior; Brain; Brain region; Clinical; Complex; Computer Simulation; Data; Data Set; Development; Diagnostic; Dorsal; Evaluation; Foundations; Generations; Goals; Impairment; Individual; Investigation; Knowledge; Language; Lead; Lesion; Location; Maps; Measures; Minor; Modeling; Modification; Motor; Names; Neurobiology; Outcome Measure; Patients; Pattern; Process; Production; Proxy; Research; Role; Science; Self-Correction; Self-Examination; Semantics; Speech; Stream; Stroke; Symptoms; TNFRSF5 gene; Testing; Theoretical model; Treatment outcome; Weight; Work; acute stroke; aphasia recovery; aphasic; base; chronic stroke; feeding; improved; individual patient; language processing; lexical; motor control; phonology; predicting response; relating to nervous system; response; speech processing; targeted treatment; theories; tool; treatment effect; treatment response; Accounting; Affect; Aphasia; Area; Assessment tool; Auditory; Back; Basic Science; Behavior; Brain; Brain region; Clinical; Complex; Computer Simulation; Data; Data Set; Development; Diagnostic; Dorsal; Evaluation; Foundations; Generations; Goals; Impairment; Individual; Investigation; Knowledge; Language; Lead; Lesion; Location; Maps; Measures; Minor; Modeling; Modification; Motor; Names; Neurobiology; Outcome Measure; Patients; Pattern; Process; Production; Proxy; Research; Role; Science; Self-Correction; Self-Examination; Semantics; Speech; Stream; Stroke; Symptoms; TNFRSF5 gene; Testing; Theoretical model; Treatment outcome; Weight; Work; acute stroke; aphasia recovery; aphasic; base; chronic stroke; feeding; improved; individual patient; language processing; lexical; motor control; phonology; predicting response; relating to nervous system; response; speech processing; targeted treatment; theories; tool; treatment effect; treatment response

Project Summary: Project 4 Model-driven therapies are only as effective as the models that drive them. The goal of Project 4 is to establish a synergistic interaction between clinical and theoretical progress in language science. Data collected as part of Projects 1 and 2 will serve as input to basic science research that will lead to new knowledge regarding the computational and neural foundation of speech production. And feeding back in the other direction, basic science models of speech production will be explored as possible diagnostic and treatment outcome measure tools, opening the door to a new era in model-driven aphasia treatment. Aim 1: Map the neural organization of computational subcomponents of naming. Naming is a multistep process. A complete understanding of its neural basis, and how it can breakdown in aphasia, depends on our ability to map the computational subcomponents of the process. Using both VLSM (error type maps) and VLPM (parameter maps), in this aim we investigate the neural organization of the subcomponents of naming in chronic and acute stroke. Aim 2: Improve and extend the model and the neurobiological mappings. While existing computational models are successful in accounting for the range of naming response types that have been fed into the models, aphasic production deficits are rather more complex than standard operational definitions admit. For this reason, and in keeping with the overall goal of the P50 to bring together theory and practice, Aim 2 seeks to push the computational models more toward clinical reality. We will use our recently-developed SLAM model to simulate and map speech repetition behavior and we will map the neural basis of a common behavior in both naming and connected speech context, self-correction. Aim 3: Assess the utility of model-driven diagnostics. The premise of Project 1 is that identifying functional deficits to the dorsal or ventral streams— i.e., dorsal stream aphasia (DSA) vs. ventral stream aphasia (VSA) vs. dual stream aphasia (DuSA)—provides useful information for aphasia treatment. In Project 1, DSA, VSA, and DuSA are classified on the basis of lesion location, which is a good (arguably the best available) proxy for the functional deficit that is targeted by the subsequent treatment. The possibility we will assess in this aim is whether we can do better at classifying patients pretreatment by measuring their functional deficit “directly” using functional/computational models rather than relying on a lesion-based proxy. This investigation could result in the development of new, clinically available assessment tools for aphasia.

项目摘要：项目4 模型驱动的疗法仅与驱动它们的型号一样有效。项目4的目标是建立 语言科学中临床和理论进步之间的协同互动。作为一部分收集的数据 项目1和2将作为基础科学研究的意见，这将导致有关 语音生产的计算和神经元基础。并朝另一个方向喂养 语音生产的科学模型将作为可能的诊断和治疗结果指标。 工具，在模型驱动的失语症治疗方面打开了新时代的大门。目标1：映射神经组织 命名的计算子组成部分。命名是一个多步骤过程。完全理解 它的神经基础以及它如何在失语中分解，取决于我们映射计算的能力 该过程的子组件。在此目标中，使用VLSM（错误类型映射）和VLPM（参数映射） 我们研究了慢性和急性中风中命名子组的神经组织。目标2： 改进并扩展模型和神经生物学映射。而现有的计算模型 成功地考虑了已馈入模型的命名响应类型的范围， 失语性生产定义比允许的标准操作定义更为复杂。为了这 原因，并符合P50的总体目标，以汇集理论和实践，Aim 2试图 将计算模型更多地推向临床现实。我们将使用最近开发的SLAM模型 模拟和映射语音重复行为，我们将绘制两者中共同行为的神经元基础 命名和连接的语音上下文，自我纠正。目标3：评估模型驱动的效用 诊断。项目1的前提是，识别功能定义为背或腹流的定义 - 即，背面失语症（DSA）与腹流失语症（VSA）与双流失语症（DUSA） - 预科 有用的失语治疗信息。在项目1中，DSA，VSA和DUSA是根据 病变位置，这是针对功能防御的好（可以说是最好的）代理 随后的治疗。我们将在此目标中评估的可能性是我们是否可以更好地分类 使用功能/计算模型“直接”测量其功能不足来预处理患者 而不是依靠基于病变的代理。这项投资可能导致新的，临床上的发展 可用的评估工具以进行失语。