The Cerebellum's Contribution to Working Memory Following Traumatic Brain Injury

描述(由申请人提供)：本申请申请为期两年的资金，用于支持John Medaglia在功能神经成像数据建模和临床神经科学研究方面的博士前培训。这项拟议的研究将应用新的技术来理解小脑作为中重度创伤性脑损伤(TBI)后工作记忆表现的潜在支持机制的作用，以更好地理解认知障碍和康复的潜在过程。该项目不同于传统的FMR研究，该研究试图隔离脑外伤患者和匹配的健康对照组之间的地区差异，因为它为NeuRA网络如何受到伤害的影响提供了明确的定量和定性检查。这一建议包括3个目标，每个目标都有一个相关的实验方法。具体目标1是考察传统上研究不足的区域-小脑在分布式工作记忆(WM)系统中的作用，该系统在学习时间、模式检测、联想学习和信息处理速度方面具有关键作用。它是 假设在任务执行过程中，小脑将与先前发现的与工作记忆相关的区域(即背外侧前额叶皮质、前扣带回皮质和顶叶皮质)高度相关，这些关系的强弱将预测任务表现，特别是小脑和前额叶皮质之间的关系。具体目的2是检验一种假设，即在工作记忆任务中观察到的初级大规模网络(即，涉及对照组的背外侧前额叶皮质、前扣带回皮质、顶叶皮质和小脑)在脑外伤中将被破坏，并且破坏将预测行为表现。重要的是，这超出了目标1的范围，因为它将大型网络的联合功能视为行为的重要因素，而不是孤立的各个部分。据假设，对照组将有更紧密的相互关联的功能网络，松散地受到解剖学连接的限制，而脑外伤患者将有分裂的网络，其小脑和前额叶功能连接具有特定的中断，这是认知功能障碍的预测。目标3将利用扩散张量成像来证实大脑结构连通性的功能发现。假设解剖结构的完整性将预测整个大脑的功能连接程度，以及与小脑具有解剖学联系的背外侧前额叶皮质和顶叶皮质之间的特定功能关系。这一提议的结果将促进我们对大脑作为神经认知系统如何对损伤做出反应的机制的理解，而不是之前的发现，这些发现没有考虑到认知过程中大脑区域之间的复杂关系。这是未来积极治疗严重损伤的关键一步，因为它将有助于我们了解神经系统某些部分的活动中断如何影响其他部分，这可能对神经外科、药物治疗和认知康复具有关键影响。这项建议还将使申请者具备信号分析、线性和非线性方程建模、图论在理解大脑方面的实用价值以及结构连接技术方面的高级专业知识，这将为富有成效的独立研究生涯奠定基础。

DESCRIPTION (provided by applicant): This application requests 2 years of funding to support John Medaglia's pre-doctoral training in functional neuroimaging data modeling and clinical neuroscience research. The proposed research will apply novel techniques to understand the role of the cerebellum as a latent support mechanism for working memory performance following moderate-to-severe traumatic brain injury (TBI) to better understand the processes underlying cognitive deficits and recovery. This project is distinct from traditional fMR research that attempts to isolate regional differences between individuals with TBI and matched healthy controls in that it affords explicit quantitative and qualitative examinations of how neura networks are affected by injuries. This proposal consists of 3 aims, each with an associated experimental approach. Specific Aim 1 is to examine the role of a traditionally understudied region, the cerebellum, in a distributed working memory (WM) system with a critical role in learned timing, pattern detection, associative learning, and speed of information processing. It is hypothesized that the cerebellum will be highly related to previously identified regions involved in WM (i.e., the dorsolateral prefrontal cortex, anterior cingulate cortex, and parietal cortex) during task performance and that the strengths of these relationships will predict performance, particularly those between the cerebellum and the prefrontal cortex. Specific Aim 2 is to test the hypothesis that the primary large-scale networks observed during WM tasks (i.e., involving the dorsolateral prefrontal cortex, anterior cingulate cortex, parietal cortex, and cerebellum) in controls will be disrupted in TBI and that disruption will predict behavioral performance. Importantly, this extends beyond Aim 1 by considering the joint functions of large networks as important to behavior as opposed to each part in isolation. It is hypothesized that controls will have more closely interrelated functional networks loosely constrained by anatomical connections, whereas individuals with TBI will have fractionated networks with specific disruptions in cerebellar and prefrontal functional connections that are predictive of cognitive dysfunction. Aim 3 will seek to corroborate functional findings in brain structural connectivity using diffusion tensor imaging. It is hypothesized that anatomical integrity will predict the degre of functional connectivity across the brain as well as specific functional relationships between the dorsolateral prefrontal cortex and parietal cortex, which have anatomical connections with the cerebellum. The results from this proposal will advance our understanding of the mechanisms of how the brain responds to injury as a neurocognitive system as opposed to previous findings that do not account for the complex relationships among regions in the brain during cognitive processing. This is a critical step toward future aggressive treatment of severe injury because it will aid our understanding of how disrupted activity in certain parts of the neurl system affects others, which may have critical implications for neurosurgery, medication, and cognitive rehabilitation. This proposal will also prepare the Applicant with advanced expertise in signal analysis, linear and nonlinear equation modeling, the utility of graph theory in understanding the brain, and structural connectivity techniques which will provide the basis for a productive independent research career.