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Studying Memory Retrieval at the Dynamic Neural Network Level

研究动态神经网络级别的记忆检索

基本信息

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
项目类别：
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&apos 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

项目摘要

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.