Neurocognitive Basis of Treatment Resistance in Young Children with SLI

项目总结(见说明)： 越来越多的证据表明，患有发展性阅读障碍(DD)的读者和典型发育中(TD)的读者之间存在遗传和神经生物学差异，但对于DD的具体起源还没有达成共识。这项拟议研究的中心目标是建立一个明确的基于大脑的DD描述，以更好地理解神经计算机制如何导致行为缺陷，以及它们与治疗反应的关系。项目1将使用集成的认知和神经成像 通过对处理速度、容量、学习和巩固施加限制，来检验神经计算机制，这些机制被假设为干扰DD抵抗器中的阅读习得。计算建模将阐明这些神经计算机制的性质，并提供证据说明哪些类型和程度的损害会引起 不同的DD参与者群体。使用较年轻的(3/4年级)和较大的(7年级)DD读者队列，它将开发作为治疗抵抗者和应答者的DDs的详细行为和神经生物学特征，重点是分离区分他们的特定因素，并预测不同年龄段定义明确的亚组内的变异性。 共有120名3/4年级学生和70名7/8年级学生将接受治疗(第一期)。经过后期测试，将确定每个年龄段的30名应答者和30名应答者。在第二阶段，除了60名DD应答者和60名DD应答者外，60名典型的(TD)3‘*4*等级机和60名TD 7’^‘8’ 年级对照，将参加认知和神经成像实验。第二阶段包括功能磁共振成像 会话使用N-back任务，结构扫描测量灰质体积，DTI测量。 第二阶段还包括语言和非语言学习和可塑性实验，这些实验被用来评估与大脑相关的预测因素，即群体和个体在速度和保持能力方面的差异。最终，通过识别最能描述不同年龄段的DD抵抗者和应答者的神经计算机制，这项工作将为开发更好地定制和优化DD治疗方法提供信息。

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.