Multi-Modal Imaging of the Mechanisms Underlying Impaired Executive Attention After Traumatic Brain Injury

创伤性脑损伤(TBI)是导致死亡和长期残疾的主要原因，目前有超过5.3例 仅在美国就有数百万人患有慢性执行注意力和认知障碍。有一个基金会- 对行政注意损害的功能和结构机制的认识上的心理差距- 在TBI之后的部分。如果没有这些知识，就不可能建立可靠的方法来预测 康复，或者，最终，创造个性化的治疗。这项综合研究工作的长期目标是 目的：明确脑外伤患者认知障碍的机制(S)，因为这将使准确的分类成为可能。 评估他们的损害，更准确地预测和准确评估干预措施的效果。 这项建议的总体目标是将管理人员注意力的临床适用脑电指标联系起来 前脑中环(额叶内侧)结构连通性改变的定量测量 并评价它们在预测脑外伤后认知结果中的作用。这个 中心假设是单独测量的电生理反应和解剖损伤 脑外伤受试者的前脑前脑中环路将与执行注意缺陷相关，通过 蚂蚁，并准确预测广泛的认知结果。这一假设是基于两位科学家的初步工作。 颅脑损伤患者的脑电和弥散磁共振研究，以及相关的已发表的研究支持的不足- 在更严重的脑损伤受试者中建立ING模型。这项拟议的研究的基本原理是： 前脑前部中层环路与执行注意缺陷的关系 视觉水平，使用生理和解剖学测量，将允许洞察生物学上的缺陷。 减少赤字，并帮助制定未来诊断和治疗的机械化方法。指导原则 强劲的初步数据，这一假设将用两个具体的目标进行检验。第一个目标是确定 用ANT测量的执行注意力损害与损伤相关的变化的程度 前脑前部中回路a)生理学(EEG)和b)白质连通性(弥散磁共振成像)。C) 目标1将整合这两种模式，并将它们与临床适用的脑电联系起来。{目标2是为了a) 横向关联和b)通过尖端机器学习纵向预测认知结果 应用于在AIM 1中收集的成像指标的技术。}在申请人的观点中，该方法是创新的- 离子，因为他们建议将由蚂蚁测量的注意力障碍与生理测量联系起来 和连接性，并预测认知结果(使用机器学习)。 提出的研究意义重大，因为对潜在注意力障碍的生物学知识将允许 它的评估是一种预测措施，并为有效的个体化干预提供目标。最终， 这种知识有可能使治疗方法的开发能够显著提高质量。 对于数百万在TBI后仍无法在其社区内恢复以前的运作水平的人来说，他们的生活得到了改善。

Traumatic Brain Injury (TBI) is a leading cause of death and long-term disability, and there are more than 5.3 million persons in the US alone with chronic executive attention and cognitive dysfunction. There is a funda- mental gap in knowledge of the functional and structural mechanisms underlying executive attention impair- ments after TBI. Without this knowledge it will not be possible to establish reliable ways to predict potential for recovery or, ultimately, create individualized therapies. The long-term goal of this integrated research effort is to identify the mechanism(s) underlying cognitive deficits in TBI patients, as this will enable accurate classifica- tion of their impairments, more accurate prognoses and precise evaluation of the effectiveness of interventions. The overall objective of this proposal is to relate clinically applicable EEG metrics of executive attention to quantitative metrics of structural connectivity alterations within the anterior forebrain mesocircuit (medial frontal cortex, striatum and central thalamus) and to evaluate their role in predicting cognitive outcomes after TBI. The central hypothesis is that individually measured electrophysiologic responses and anatomical injuries within the anterior forebrain mesocircuit of TBI subjects will correlate with executive attention deficits, as measured by the ANT, and accurately predict broad cognitive outcomes. This hypothesis is based on preliminary work from two studies of EEG and diffusion MRI in TBI patients, as well as related published research supporting the underly- ing model in more severely brain-injured subjects. The rationale underlying the proposed research is that char- acterizing the relationship between the anterior forebrain mesocircuit and executive attention deficits at an indi- vidual level, using both physiological and anatomical measurements, will allow insight into the biological un- derpinnings of the deficits and help frame mechanistic approaches to future diagnosis and therapy. Guided by strong preliminary data, this hypothesis will be tested with two specific aims. The first Aim is to determine the extent to which executive attentional impairment, measured with the ANT, relates to injury-related changes in the anterior forebrain mesocircuit a) physiology (EEG) and b) white matter connectivity (diffusion MRI). Part c) of Aim 1 will integrate the two modalities and relate them back to clinically-applicable EEG. {Aim 2 is to a) cross-sectionally relate and b) longitudinally predict cognitive outcomes via cutting-edge machine learning techniques applied to imaging metrics collected in Aim 1.} The approach is innovative, in the applicant's opin- ion, because they propose to link attentional impairments, as measured by the ANT, to measures of physiology and connectivity on an individual basis and predict cognitive outcomes {using machine learning.} The pro- posed research is significant, because knowledge of the biology underlying attention impairment will allow for its evaluation as a prognostic measure and provide targets for effective individualized interventions. Ultimately, such knowledge has the potential to enable development of therapies that can dramatically improve the quality of life for millions that remain unable to return to prior levels of functioning within their communities after TBI.