The Role of LFP Spatial Structure in the Hippocampus

LFP 空间结构在海马中的作用

• 批准号: 8207317
• 负责人: Gautam Agarwal
• 金额: $ 5.52万
• 依托单位: UNIVERSITY OF CALIFORNIA BERKELEY
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-01-18 至 2014-01-17
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8207317
• 关键词: Accounting; Affect; Algorithms; Amnesia; Animals; Behavior; Behavioral; Brain; Brain Part; Brain region; Complex; Computing Methodologies; Data Analyses; Data Set; Defect; Development; Dictionary; Electrodes; Employee Strikes; Epilepsy; Event; Exhibits; Fire - disasters; Frequencies; Goals; Hippocampus (Brain); Intervention; Investigation; Lead; Life Style; Location; Machine Learning; Measurement; Measures; Memory; Metric; Modeling; Neurons; Patients; Pattern; Phase; Play; Population; Process; Property; Reporting; Role; Screening procedure; Signal Transduction; Site; Structure; Sum; Techniques; Testing; Theta Rhythm; Time; Tissues; Travel; Variant; Work; base; cell type; information processing; interest; memory recall; network models; neuronal patterning; predictive modeling; public health relevance; relating to nervous system; spatiotemporal

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.

描述(申请人提供)：这项工作的长期目标是了解海马体内神经元的活动是如何协调的，海马体是一个涉及记忆存储的大脑区域。这种协调的一个表现是局部场电位(LFP)，即小体积神经组织的总和电活动。最近，多电极阵列(MEA)实现了在动物执行任务时同时测量动物大脑内多个位置的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。众所周知，海马区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通过海马体传播的LFP波。这个项目将研究海马区LFP的空间动力学是否影响神经元的活动及其与行为的关系。其目的是1)找出一个简洁的模型来解释LFP中观察到的时空结构；2)研究LFP结构与单个神经元活动的关系；3)了解LFP结构是如何调控海马区内电路水平的神经元处理的。为了实现这些目标，本项目将使用统计学习技术从LFP内提取时空规律性，并使用预测模型来检测不同LFP结构对海马神经元群体活动的影响。这项工作将确定简明的衡量标准，以捕捉高维海马LFP测量的丰富性。此外，它还将研究将复杂的动力学特征融入到当前的海马体处理模型中的实用性。这项工作可能有助于理解海马体内电活动的扭曲如何导致癫痫和健忘症等疾病。它将评估LFP作为神经假体干预的直接靶点的适宜性。最后，它可能导致快速发现患者大脑活动中潜在异常的筛查程序，并有助于了解此类异常对患者生活方式的影响。 与公共健康相关：该项目的目标是对海马体中发现的活动电波进行更完整的描述，海马体是大脑中存储记忆的区域。这些波表现出的空间模式可能有助于引导海马体的正常功能。这项工作可能会解释电活动的扭曲如何与人们形成和回忆记忆的能力缺陷有关。