Studying Memory Retrieval at the Dynamic Neural Network Level

研究动态神经网络级别的记忆检索

• 批准号: 8863829
• 负责人: Ziv Williams
• 金额: $ 36.96万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-04-01 至 2020-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8863829
• 关键词: Algorithms; Alzheimer' s Disease; Animal Model; Animals; Area; Behavior Disorders; Behavioral; Biological Neural Networks; Code; Computational Technique; Cues; Data; Degenerative Disorder; Electrodes; Genes; Higher Order Chromatin Structure; Individual; Inferior; Ising model; Lateral; Learning; Linear Models; Macaca mulatta; Memory; Methodology; Methods; Microelectrodes; Modeling; Nature; Neurodegenerative Disorders; Neurons; Neurosciences; Parkinson Disease; Pattern; Population; Primates; Principal Investigator; Process; Research; Retrieval; Stimulus; Structure; Techniques; Testing; Theoretical Studies; Time; Training; Trees; Up-Regulation; Visual; Work; awake; base; cognitive function; cognitive process; developmental disease; information model; innovation; insight; memory process; memory recall; memory retrieval; millisecond; novel; optogenetics; public health relevance; relating to nervous system; theories; way finding

 DESCRIPTION (provided by applicant): A fundamental question in neuroscience is how memories are represented by the collective pattern of spiking within neural populations. A related question is whether the same collective pattern used to represent memories during learning are "reactivated" during later recall, or if the nature of the population code is vitally different. While prior theoretical work and more recent work in animal models have provided valuable initial insights into how memories are likely represented, the neural process by which memories are actually retrieved at the network-wide level, what exact aspects of the first-, second- and higher-order network structure are informative of the retrieved memories, and by what rapid sub-second dynamic do such informative patterns evolve within individual trials remain fundamentally unknown. This limited understanding is particularly true of hetero-associative memory processes such as cued recollection in which the items being recalled are both absent and completely unique from the presented items used to cue their retrieval. Here, we aim to systematically define, for the first time, the combined network-level processes that underlie these basic forms of auto-associative (recognition) and hetero-associative (recollection) memory. Towards these ends, we will use the shared expertise of the two principal investigators to perform simultaneous multi-electrode recordings from frontal and temporal cortical populations in Rhesus macaques; devise and test novel analysis methodologies that can both reliably infer the collective first-, second- and higher-order functional network structures from stochastic spiking data; track their rapid sub-second dynamics within individual trials; identify which structures are informative of the memories being recalled; determine when and to what extent spiking network structures observed during learning reactivate during recall within individual-day sessions; and, perhaps most importantly, determine whether pattern reactivation, at the spiking network-level, is causatively related to recall accuracy at the behavioral level. Th present proposal will allow us to directly test, for the first time, a number of central hypotheses on memory processing using a novel set of technical and methodological innovations that will have broad practical implications to the study of memory-related developmental, behavioral and neurodegenerative disorders.

 描述（由申请人提供）：神经科学中的一个基本问题是记忆如何由神经群体内的集体尖峰模式表示。一个相关的问题是，在学习过程中用来代表记忆的相同集体模式是否在后来的回忆中被“重新激活”，或者群体代码的性质是否有着本质的不同。虽然先前的理论工作和最近在动物模型中的工作已经为记忆可能如何表示提供了有价值的初步见解，但在网络范围内实际检索记忆的神经过程，一阶，二阶和高阶网络结构的确切方面是检索记忆的信息，以及在个体试验中，这种信息模式是如何快速地以亚秒级的动态演变的，这基本上仍然是未知的。这种有限的理解尤其适用于异质联想记忆过程，例如线索回忆，其中被回忆的项目既不存在，也完全不同于用于提示其检索的项目。在这里，我们的目标是系统地定义，第一次，结合网络级的过程，这些基本形式的自联想（识别）和异联想（回忆）的记忆。为了实现这些目标，我们将利用两位主要研究者的共同专业知识，从恒河猴的额叶和颞叶皮层人群中进行同步多电极记录;设计和测试新的分析方法，这些方法可以可靠地从随机尖峰数据中推断出集体的第一，第二和高阶功能网络结构;在单个试验中跟踪其快速的亚秒动态;识别哪些结构是被回忆的记忆的信息;确定在学习期间观察到的尖峰网络结构在个体日会话期间的回忆期间何时以及在何种程度上重新激活;并且，也许最重要的是，确定在尖峰网络水平上的模式重新激活是否与行为水平上的回忆准确性有因果关系。目前的建议将使我们能够直接测试，第一次，一些核心假设 使用一套新的技术和方法创新，将有广泛的实际意义的研究与记忆有关的发展，行为和神经退行性疾病的记忆处理。