Brain Connectivity Supporting Language Recovery in Aphasia

大脑连接支持失语症的语言恢复

• 批准号: 10408786
• 负责人: Leonardo F Bonilha
• 金额: $ 54.91万
• 依托单位: EMORY UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-06-10 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10408786
• 关键词: Achievement; Affect; Aftercare; Anaerobic Bacteria; Anatomy; Aphasia; Area; Basic Science; Behavioral; Brain; Brain Injuries; Brain Mapping; Brain region; Chronic; Communication; Comprehension; Data; Data Set; Diffusion; Diffusion Magnetic Resonance Imaging; Dorsal; Exhibits; Gliosis; Goals; Grain; Image; Impairment; Individual; Injury; Intervention; Knowledge; Language; Lead; Lesion; Location; Magnetic Resonance Imaging; Maps; Measures; Mediating; Methodology; Methods; Modeling; Modernization; Names; Necrosis; Neurobiology; Neurologic Deficit; Neurons; Neuropsychology; Pathway interactions; Peer Review; Perfusion; Persons; Process; Production; Publications; Recovery; Rehabilitation therapy; Research; Research Proposals; Residual state; Resistance; Retrieval; Role; Science; Semantics; Severities; Site; Speech; Stream; Stroke; Structure; Symptoms; Testing; Wallerian Degeneration; aphasia recovery; base; brain behavior; cerebrovascular; cerebrovascular lesion; chronic stroke; clinical practice; clinical translation; connectome; experience; gray matter; improved; innovation; language impairment; language outcome; language processing; multimodality; network models; neural network; neuroimaging; neuroimaging marker; neuronal circuitry; novel; novel strategies; outcome prediction; phonology; post stroke; stroke survivor; success; support network; white matter; white matter injury

Abstract Aphasia is one of the most common neurological deficits after a stroke, typically resulting from injury to cortical brain regions related to language processing in the dominant hemisphere. However, many individuals with aphasia can exhibit language impairments that are out of proportion to the degree of gray matter injury, with severe deficits from relatively smaller subcortical lesions, or less severe deficits in spite of relatively large lesions. This discrepancy is frequently attributed to the notion that language relies not only on the integrity of gray matter regions, but also on the white matter pathways supporting their ability to act in concert. Nonetheless, white matter disconnections beyond the necrotic or gliotic post-stroke brain lesions are not always measured or taken into account in models of brain-behavior relationships. To fully understand the neurobiology of aphasia, brain damage should be quantified as the combination of direct necrosis / gliosis as well as cortical disconnection. The overarching purpose of this research proposal is to comprehensively map residual white matter networks in stroke survivors to determine their role in the neurobiology of language processing and aphasia recovery. Using newer advancements in structural neuroimaging, our group developed Connectome-Lesion Symptom Mapping (CLSM) to test specific questions related to aphasia mechanisms and aphasia recovery. During the first cycle of this project, this research yielded 15 high-impact peer-reviewed publications. Based on this success, the novel research proposed in this project will build on these achievements to evaluate three independent new conceptual topics related to aphasia: we will define multimodal network dynamic modeling approaches to elucidate the relationship between structural and functional neuronal network integrity post-stroke, including direct and indirect neuronal communication, and their relationship with aphasia (Aim 1). The dual stream model is a promising new theoretical framework for language processing, however, it is still an oversimplification and our recent data suggests that each stream is composed of finer grained sub-networks. Using the connectome approach, we will define the sub-networks that form the dorsal and ventral streams of language processing (Aim 2). We will determine stream-specific white matter microstructural network plasticity supporting aphasia recovery after treatment (Aim 3). To accomplish these aims, we will leverage a large baseline behavioral and imaging chronic aphasia dataset from the Center for the Study of Aphasia Recovery (C-STAR) (n-199) (Aims 1 and 2), and data from the ongoing treatment study Predictor of Outcome of Language Rehabilitation (POLAR) (n=150) (Aim 3). Overall, this project will build on connectome and network science to advance translational and personalized research in aphasia. It will advance knowledge on neuroimaging methods, provide mechanistic information about language processing, and determine markers for therapy-related language improvement.

抽象的 失语症是中风后最常见的神经系统缺陷之一，通常是由受伤引起的 与主要半球的语言处理有关的皮质大脑区域。但是，许多人 失语症可以表现出与灰质伤害程度不成比例的语言障碍， 皮下病变较小的严重缺陷，或者尽管相对较大 病变。这种差异经常归因于语言不仅依赖于语言的完整性的观念 灰质区域，以及有关白质途径的支持，以支持其共同行动的能力。 尽管如此，白质断开了坏死或胶质性后脑脑损伤之外 始终在脑行为关系的模型中考虑或考虑。充分了解 失语症，脑损伤的神经生物学应被量化为直接坏死 /神经病的组合 以及皮质断开连接。该研究建议的总体目的是全面绘制 中风幸存者中的残留白质网络，以确定其在语言神经生物学中的作用 处理和失语症恢复。使用结构神经影像中的新进步，我们的小组开发了 连接仪症状映射（CLSM），以测试与失语机制有关的特定问题 失语症恢复。在该项目的第一个周期中，这项研究产生了15个高影响同行评审 出版物。基于这一成功，该项目提出的小说研究将基于这些 评估与失语症有关的三个独立新概念主题的成就：我们将定义 多模式网络动态建模方法，以阐明结构与 中风后功能性神经网络完整性，包括直接和间接的神经元通信，以及 他们与失语症的关系（AIM 1）。双流模型是一个有希望的新理论框架 但是，语言处理仍然是一个过度的简化，我们最近的数据表明每个流是 由更细的子网络组成。使用Connectome方法，我们将定义子网络 形成语言处理的背面和腹侧流（AIM 2）。我们将确定特定于流的白色 物质微观结构网络可塑性支持治疗后的失语症恢复（AIM 3）。完成 这些目的，我们将利用中心的大型基线行为和成像慢性失语数据集 为了研究失语症恢复（C-Star）（N-199）（目标1和2），以及正在进行的治疗的数据 语言康复结果的研究预测指标（Polar）（n = 150）（AIM 3）。总体而言，这个项目将建立 关于Connectome和Network Science，以提高失语症的转化和个性化研究。会 提前了解神经影像学方法，提供有关语言处理的机械信息， 并确定与治疗相关语言改进的标记。