The Role of LFP Spatial Structure in the Hippocampus

描述（由申请人提供）：这项工作的长期目标是了解神经元的活动是如何在海马体中协调的，海马体是一个涉及记忆存储的大脑区域。这种协调的表现之一是局部场电位（LFP），即一小部分神经组织的电活动总和。最近，多电极阵列（MEAs）已经能够在动物执行任务时同时测量大脑内多个部位的lfp和单个神经元的活动。这一进步推动了新的计算方法的发展，这些方法可以识别这些丰富的大型数据集中存在的关系。海马lfp的时间结构与单个神经元的活动以及行为状态有关。相比之下，这些lfp的空间结构仍然相对未被探索。这种空间结构的一个有趣的例子是在海马体中传播的LFP波。该项目将研究海马体LFP的空间动力学是否影响神经元活动及其与行为的关系。其目的是：1)确定一个简洁的模型来解释LFP中观测到的时空结构；2)研究LFP结构与单个神经元活动的关系；3)了解LFP结构如何控制海马体内回路水平的神经元加工。为了实现这些目标，本项目将采用统计学习技术从LFP中提取时空规律，并使用预测模型来研究不同LFP结构对海马神经元群体活动的影响。这项工作将确定捕捉高维海马LFP测量的丰富性的简明指标。此外，它将检查将复杂的动态特征纳入当前海马处理模型的效用。这项工作可能有助于理解海马体内电活动的扭曲是如何导致癫痫和健忘症等疾病的。它将评估LFP作为神经假体干预的直接目标的适用性。最后，它可能会导致快速发现患者大脑活动潜在异常的筛选程序，并有助于了解这种异常对患者生活方式的影响。

DESCRIPTION (provided by applicant): The long-term objective of this work is to understand how the activity of neurons is coordinated within the hippocampus, a brain region involved in the storage of memories. One manifestation of this coordination is the local field potential (LFP), the summed electrical activity of a small volume of neural tissue. Recently, multi- electrode arrays (MEAs) have enabled the simultaneous measurement of LFPs and single-neuron activity from multiple sites within the brain of an animal as it performs a task. This advance motivates the development of new computational methods that can identify the relationships that exist within these rich, large data sets. The temporal structure of hippocampal LFPs is known to correlate with single-neuron activity, as well as with behavioral state. In contrast, the spatial structure of these LFPs remains relatively unexplored. An interesting example of this spatial structure are the traveling LFP waves that propagate through the hippocampus. This project will examine whether the spatial dynamics of the hippocampal LFP influence neuronal activity and its relationship to behavior. Its aims are 1) to identify a parsimonious model for explaining the observed spatio- temporal structure in the LFP; 2) to investigate the relationship of LFP structure to single-neuron activity; and 3) to understand how LFP structure governs circuit-level neuronal processing within the hippocampus. To achieve these goals, this project will employ statistical learning techniques to extract spatio-temporal regularities from within the LFP, and use predictive models to examine the influence of different LFP structures on the population activity of hippocampal neurons. This work will identify concise metrics that capture the richness of high-dimensional hippocampal LFP measurements. Furthermore, it will examine the utility of incorporating complex dynamical features into current models of hippocampal processing. This work may help understand how distortions in electrical activity within the hippocampus lead to conditions such as epilepsy and amnesia. It will evaluate the suitability of the LFP as a direct target for neuroprosthetic interventions. Finally, it may lead to screening procedures for rapidly finding potential abnormalities in patients' brain activity, and help understand the implications of such abnormalities for patients' lifestyles. PUBLIC HEALTH RELEVANCE: The goal of this project is to develop a more complete description of the electrical waves of activity found in the hippocampus, a region of the brain that stores memories. These waves exhibit spatial patterns that may help guide the proper function of the hippocampus. This work could potentially explain how distortions in electrical activity relate to defects in people's abilities to form and recall memories.