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

描述（由申请人提供）：本申请要求2年的资金，以支持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。拟议的研究将应用新技术来了解小脑作为中度至重度创伤性脑损伤（TBI）后工作记忆表现的潜在支持机制的作用，以更好地了解认知缺陷和恢复的潜在过程。该项目与传统的fMR研究不同，传统的fMR研究试图隔离TBI个体与匹配的健康对照之间的区域差异，因为它提供了明确的定量和定性检查神经网络如何受到损伤的影响。该提案包括3个目标，每个目标都有一个相关的实验方法。具体目标1是研究传统上未充分研究的区域，小脑，在分布式工作记忆（WM）系统中的作用，在学习的时间，模式检测，联想学习和信息处理速度的关键作用。是 假设小脑将与先前鉴定的涉及WM的区域高度相关（即，背外侧前额叶皮层，前扣带皮层和顶叶皮层），这些关系的强度将预测性能，特别是小脑和前额叶皮层之间的关系。具体目标2是检验假设，即在WM任务期间观察到的主要大规模网络（即，涉及背外侧前额叶皮层、前扣带皮层、顶叶皮层和小脑）将在TBI中被破坏，并且该破坏将预测行为表现。重要的是，这超出了目标1，因为它认为大型网络的联合功能对行为很重要，而不是孤立的每个部分。据推测，控制将有更密切相关的功能网络松散的解剖连接的约束，而TBI的个人将有细分的网络与特定的中断小脑和前额叶功能连接，是预测认知功能障碍。目的3将寻求证实功能的结果，在脑结构连接使用扩散张量成像。假设解剖完整性将预测整个大脑的功能连接程度，以及背外侧前额叶皮层和顶叶皮层之间的特定功能关系，它们与小脑有解剖学联系。这项提议的结果将促进我们对大脑如何作为神经认知系统对损伤做出反应的机制的理解，而不是以前的发现，这些发现没有解释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，这可能对神经外科手术，药物治疗和认知康复具有重要意义。该提案还将为申请人提供信号分析，线性和非线性方程建模，图论在理解大脑中的实用性以及结构连接技术方面的先进专业知识，这些技术将为富有成效的独立研究生涯提供基础。

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.