Intervention-induced plasticity of flexibility and learning mechanisms in ASD

项目总结 CNH和乔治敦大学之间的这一探索性项目利用DC-IDDRC 基础设施及其神经影像、神经行为和临床翻译核心测试 关于将所学知识转化为小说能力的个体差异的机械论假说 自闭症谱系障碍(ASD)的设置。ASD干预的历史上充斥着糟糕的现实世界 结果和推广成功的高度异质性(1)。一个已知的促成因素是高管 功能障碍，特别是行为不灵活(2，3)。理解这种学习和执行功能之间的关系 (4)可能掌握着解决ASD中泛化挑战的关键，但它几乎没有受到关注。这个 提出的项目旨在通过测试学习和灵活性之间的关系 干预以促进ASD患者的灵活行为改变了学习和相关的神经机制。 这项拟议研究的科学前提是，灵活使用所学概念依赖于生成 原型，而根据个体样本进行学习会促进特异性(5，6)。当前的概念模型 学习(7)使用了个体泛化绩效的计算模型和基于模型的 功能性磁共振成像(m-fMRI)将原型的产生归因于腹侧前额叶内侧 皮层(VmPFC)和对内侧颞叶(MTL)的样本偏向学习(8)。我们建议 原型/样本学习机制的可变性与行为灵活性和 解释适应性和治疗结果的差异。我们采用纵向病例对照设计。 54例14-18岁的青壮年ASD患者在3个时间点相隔8个月，每个时间点进行m-fMRI检查 执行和适应功能的学习和行为测量。AIM 1检验了假设 学习偏差的个体差异(原型/样本)及其神经关联预测 行为灵活性(Time1)，随时间稳定(Time2)。目标2测试学习的可塑性 认知-行为干预对灵活性(非粘着和目标)的诱导机制 目标是发展原型知识(9)。干预将加强原型学习，并 相关的vmPFC参与将与对干预的更好的行为反应相关。AIM 3测试 关于干预诱导内在功能连接可塑性的假说。更强的休息能力- 具体说明MTL和vmPFC之间的功能连接以及MTL的网络连接 默认模式网络(10)的子系统将与原型学习和干预响应相关联。 我们的方法在方法上是新颖的，在使用个性化的学习机制特征方面， 并从理论上统一学习和执行功能来解释治疗反应的机制和 ASD患者治疗结果的异质性。研究结果将为更大规模的个性化治疗研究提供参考 促进自闭症患者的适应行为。

PROJECT SUMMARY This exploratory project between CNH and Georgetown University leverages the DC-IDDRC infrastructure and its Neuroimaging, Neurobehavioral and Clinical Translational Cores to test mechanistic hypotheses about individual differences in the ability to transfer learned knowledge to novel settings in Autism Spectrum Disorders (ASD). The history of ASD intervention is rife with poor real-world outcomes and high heterogeneity in generalization success (1). One known contributing factor is executive dysfunction, particularly behavioral inflexibility (2, 3). Understanding this nexus of learning and executive function (4) likely holds the key to resolving the generalization challenge in ASD, but it has received little attention. The proposed project aims to elucidate the association between learning and flexibility by testing whether intervening to promote flexible behavior in ASD changes learning and associated neural mechanisms. The scientific premise of the proposed study is that flexible use of learned concepts depends on generating prototypes, whereas learning tuned to individual exemplars promotes specificity (5, 6). Current models of concept learning (7) have used computational modeling of individual generalization performance and model-based functional magnetic resonance imaging (m-fMRI) to attribute prototype-generation to ventral medial prefrontal cortex (vmPFC) and exemplar-biased learning to the medial temporal lobes (MTL) (8). We propose that variability in prototype/exemplar learning mechanisms is associated with behavioral flexibility and explains differences in adaptive and treatment outcomes. We employ a longitudinal case-controlled design in 54 14-18 year old youth with ASD at 3 time-points 8 months apart, each including m-fMRI during category learning and behavioral measurement of executive and adaptive function. Aim 1 tests the hypothesis that individual variation in learning biases (prototype/exemplar) and their neural correlates predicts behavioral flexibility (Time1) and is stable over time (Time2). Aim 2 tests plasticity of learning mechanisms induced by a cognitive-behavioral intervention for flexibility (Unstuck-and-On-Target) that targets development of prototypical knowledge (9). Intervention will strengthen prototype learning, and associated vmPFC involvement will be associated with better behavioral response to intervention. Aim 3 tests hypothesis about intervention-induced plasticity of intrinsic functional connectivity. Stronger resting- state functional connectivity between MTL and vmPFC specifically and network connectivity of the MTL subsystem of the default mode network (10) will be associated with prototype learning and intervention response. Our approach is novel, methodologically in the use of individualized characterization of learning mechanisms, and theoretically in unifying learning and executive function to explain mechanisms of treatment response and heterogeneity in treatment outcome in ASD. Findings will inform larger investigations of personalized treatments for promoting adaptive behavior in ASD.