Neurocognitive Basis of Treatment Resistance in Young Children with SLI

SLI 幼儿治疗抵抗的神经认知基础

• 批准号: 8707512
• 负责人: Jason D Zevin
• 金额: $ 13.16万
• 依托单位: GEORGIA STATE UNIVERSITY
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至 2015-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8707512
• 关键词: Accounting; Address; Age; Back; Base of the Brain; Behavioral; Brain; Categories; Child; Cognitive; Computer Simulation; Consensus; Data; Development; Developmental reading disorder; Diagnosis; Education; Functional Magnetic Resonance Imaging; Genetic; Goals; Health; Hour; Impairment; Individual Differences; Instruction; Intervention; Language Development; Learning; Life; Linguistics; Link; Measures; Nature; Neurobiology; Neurocognitive; Participant; Phase; Prevention; Process; Protocols documentation; Quality of life; Reader; Reading; Recruitment Activity; Relative (related person); Research; Resistance; Sampling; Scanning; Specific qualifier value; Subgroup; Testing; Theoretical model; Treatment Factor; Work; base; behavior test; cognitive process; cognitive testing; cohort; disability; eighth grade; gray matter; improved; information organization; meetings; neuroimaging; processing speed; research study; response; seventh grade; skills; treatment response

PROJECT SUMMARY (See instructions): There is growing evidence of genetic and neurobiological differences between readers with developmental dyslexia (DD) and typically developing (TD) readers, but there is no consensus on the specific origins of DD. The central goal of the proposed research is to develop a well specified brain-based account of DD, to better understand how neurocomputational mechanisms give rise to behavioral deficits, and their relation to response to treatment. Project 1 will use integrated cognitive and neuroimaging experiments to examine neurocomputational mechanisms that have been hypothesized to interfere with reading acquisition in DD resisters, by placing limits on processing speed, capacity, and learning and consolidation. Computational modeling will clarify the nature of these neurocomputational mechanisms and provide evidence as to which types and degrees of impairment(s) give rise to the behavioral profiles of different DD participant groups. Using younger (3rd/4th graders) and older (7th graders) cohorts of DD readers, it will develop detailed behavioral and neurobiological profiles of DDs who are treatment resisters and responders, to be analyzed with a focus on isolating specific factors that differentiate them, and predict variability within well-defined subgroups at different ages. A total of 120 3rd/4th graders, and 70 7th/8th graders, will receive treatment (Phase I). After post-testing, 30 resisters and 30 responders from each age category will be identified for the Phase II. In Phase II, in addition to the 60 DD responders and 60 DD resisters, 60 typically developing (TD) 3''*4* graders, and 60 TD 7'^'8''' grade controls, will participate in the cognitive and neuroimaging experiments. Phase II includes an fMRI session using the N-back task, structural scanning to measure grey matter volume, and DTI measures. Phase II also includes linguistic and non-linguistic learning and plasticity experiments, which are used to evaluate those brain-related predictors of group and individual differences in rate and retention. Ultimately, through this identification of the neurocomputation mechanisms that best describe DD resisters and responders at different ages, this work will inform development of better-tailored and optimized treatments for DD.

项目摘要（请参阅说明）： 越来越多的证据表明患有发育阅读障碍（DD）的读者和通常发育（TD）读取器之间存在遗传和神经生物学差异，但就DD的特定起源尚无共识。拟议的研究的核心目标是开发一个特定的基于大脑的DD帐户，以更好地了解神经计算机制如何导致行为缺陷及其与治疗反应的关系。项目1将使用集成的认知和神经影像学 通过对处理速度，能力，学习和巩固的限制来检查已假设以干扰DD回复者阅读获得的神经计算机制的实验。计算建模将阐明这些神经计算机制的性质，并提供证据表明哪种类型和程度的损害产生了损害的类型和程度 不同的DD参与者组。使用年轻（3年级/4年级）和年龄较大的DD读取器（7年级）同类群，它将开发出是治疗人员和响应者的DDS的详细行为和神经生物学概况，以分析以隔离特定因素，并预测不同AGES的特定因素的特定因素，并预测良好的亚基中的变异性。 总共120个三年级学生和70个70年级/8年级的学生将获得治疗（I阶段）。经过测试后，将为II阶段确定每个年龄段的30名撤退者和30个响应者。在第二阶段中，除了60个DD响应者和60个DD抗议者外，通常有60个通常开发的（TD）3''* 4*级别和60 TD 7'^'8'''''' 等级控制将参加认知和神经影像学实验。第二阶段包括fMRI 使用N-BACK任务，结构扫描来测量灰质体积和DTI测量。 第二阶段还包括语言和非语言学习和可塑性实验，这些学习和可塑性实验用于评估群体和率的脑部差异的那些与大脑相关的预测指标。最终，通过对最能描述不同年龄段DD回复者和响应者的神经功能机制的识别，这项工作将为DD的详尽和优化处理的开发提供信息。