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（由适用提供）：神经科学中的一个基本问题是记忆如何由神经种群中的尖峰集体模式代表。一个相关的问题是，在以后的召回期间，用于表示记忆的相同的集体模式是否被“重新激活”，或者人口代码的性质是否有着不同的不同。虽然先前的理论工作和动物模型中的最新工作为记忆的代表方式提供了宝贵的初步见解，而在网络范围内实际检索的记忆的神经过程，但在检索到的记忆中，第一，第二和高级网络结构的确切方面是对检索到的记忆的信息，并且在迅速的动态模式中会在个人动态模式中进一步依靠的依据。这种有限的理解尤其如此，对于异性缔合性记忆过程，例如提示回忆，其中所召回的项目既没有且完全独一无二，又是用来提示其检索的项目。在这里，我们的目标是首次系统地定义这些基本形式的自动求解（识别）和异方差（回忆）内存的基本形式的组合网络级过程。在这些目的方面，我们将使用两位主要研究人员的共同专业知识来执行恒河猕猴额叶和临时皮质种群的同时多电极录音。设计和测试新的分析方法可以可靠地从随机峰值数据中可靠地推断出集体的一流，第二和高阶功能网络结构；在单个试验中跟踪其快速的下一步动态；确定哪些结构对所回忆的记忆很有帮助；确定在学习过程中观察到的何时何地峰值网络结构在个人日课程中重新激活；而且，也许最重要的是，确定在尖峰网络层面上的模式重新激活是否与行为层面的回忆准确性有关。目前的建议将使我们能够首次直接测试许多中心假设 在记忆处理上，使用一组新型的技术和方法论创新，这些创新将对与记忆相关的发育，行为和神经退行性疾病的研究具有广泛的实际意义。