Functional anomaly mapping of aphasia recovery

失语症恢复的功能异常图谱

• 批准号: 10214766
• 负责人: Andrew T DeMarco
• 金额: $ 12.15万
• 依托单位: GEORGETOWN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-01 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10214766
• 关键词: Affect; Algorithms; Anatomy; Aphasia; Architecture; Area; Award; Behavioral; Biological; Blood Vessels; Brain; Characteristics; Chronic; Clinical; Communication; Data; Data Set; Deafferentation procedure; Diagnosis; Distant; Exhibits; Functional Magnetic Resonance Imaging; Functional disorder; Goals; Individual; Knowledge; Language; Lead; Left; Length; Lesion; Location; Longitudinal Studies; Longitudinal prospective study; Machine Learning; Maps; Measures; Mentors; Modeling; National Institute on Deafness and Other Communication Disorders; Neuronal Plasticity; Outcome; Pattern; Performance; Phase; Physiology; Recovery; Reproducibility; Research; Research Training; Residual state; Resolution; Rest; Sample Size; Scanning; Severities; Signal Transduction; Source; Specific qualifier value; Strategic Planning; Stroke; Structure; Symptoms; Testing; Time; Training; aphasia recovery; base; behavior measurement; behavioral outcome; biomarker development; brain behavior; chronic stroke; clinical decision-making; cohort; experience; imaging modality; improved; machine learning algorithm; multimodality; neural correlate; neurobiological mechanism; neuroimaging; neurological rehabilitation; neuromechanism; post stroke; programs; public health relevance; spatiotemporal; stroke recovery; stroke survivor; stroke-induced aphasia; tool; white matter

Project Summary Difficulty communicating (aphasia) is one of the most common and debilitating results of left-hemisphere stroke. Although aphasia symptoms are highly variable and recovery is difficult to predict, much research has shown that lesion size and location are major drivers of aphasia symptoms and recovery. However, this previous research has only considered direct anatomical damage caused by the lesion. This is a critical limitation because stroke lesions also cause indirect effects on the function of brain structures distant from the lesion. Throughout this application, I refer to this as “remote dysfunction.” Although initially thought to resolve quickly after the stroke, remote dysfunction is now known to persist throughout recovery and independently contribute to outcomes. Studies of aphasia recovery have focused almost exclusively on the idea of recovery through reorganization, whereby behavioral improvement occurs through plastic reorganization of brain networks. These studies have eschewed the older idea that recovery occurs through partial resolution of remote dysfunction (RRD) caused by lesions. Consequently, it is not clear how RRD contributes to aphasia recovery. The applicant has developed a new machine learning approach called functional anomaly mapping (FAM) that uses resting BOLD functional MRI signal to map remote dysfunction throughout the brain in individual stroke survivors. FAM maps have much better test-retest reliability than current measures, like task- related fMRI activity and resting state functional connectivity, as well as several other features that make it promising as a clinically useful tool. The applicant has already demonstrated that remote dysfunction measured with FAM relates to behavioral outcomes in people with chronic aphasia. During the mentored phase of this award, the applicant will optimize the FAM approach and test competing hypotheses about the biological mechanisms generating the remote dysfunction measured in chronic aphasia. During the independent phase, the applicant proposes a longitudinal study to understand the contribution of RRD to aphasia recovery. The applicant proposes a comprehensive training plan to expand his knowledge in the following areas: the biological mechanisms of stroke recovery and neuroplasticity beyond aphasia, machine learning, biomarker development, and advanced neuroimaging analysis. The research and training during this award will enable the applicant to develop a long-term, independent research program focused on understanding the neural correlates of aphasia and developing translational brain measures to inform clinical decision-making in aphasia neurorehabilitation.

项目摘要 沟通难度（失语）是左 - 半球最常见和令人衰弱的结果之一 中风。尽管失语症症状是高度可变的，并且恢复很难预测，但很多研究 表明病变的大小和位置是失语症症状和康复的主要驱动因素。但是，这个 先前的研究仅考虑了病变引起的直接解剖损害。这是一个关键 限制是因为中风病变也会对远离大脑结构功能的功能间接影响 病变。通过此应用程序，我将其称为“远程功能障碍”。尽管最初被认为是解决的 中风后很快，现在已知远程功能障碍在整个恢复过程中持续存在，并且独立 有助于结果。失语症恢复的研究几乎完全集中在恢复的想法上 通过重组，行为改善通过大脑的塑性重组发生 网络。这些研究避免了较旧的想法，即通过部分解决 病变引起的远程功能障碍（RRD）。因此，尚不清楚RRD如何导致失语症 恢复。申请人开发了一种新的机器学习方法，称为功能异常映射 （FAM）使用静止大胆的功能性MRI信号在整个大脑中绘制远程功能障碍 个别中风存活。 FAM地图的重测可靠性比当前的措施（例如任务）要好得多。 相关的fMRI活动和静止状态功能连接，以及其他几个功能 作为临床上有用的工具有希望。申请人已经证明了远程功能障碍 用与慢性失语症患者的行为结果有关的FAM衡量。在这件事期间 该奖项的阶段，申请人将优化FAM方法，并测试有关该方法的竞争假设 在慢性失语症中测量的远程功能障碍的生物学机制。在 独立阶段，申请人提出了一项纵向研究，以了解RRD对 失语症恢复。申请人提出一项全面的培训计划，以扩大他的知识 以下领域：中风恢复和神经塑性的生物学机制超出了失语症，机器 学习，生物标志物发展和高级神经影像学分析。在此期间的研究和培训 奖励将使申请人能够制定一项长期独立研究计划，以 了解失语症的神经相关性并制定转化大脑测量以告知临床 失语症神经康复中的决策。