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CRCNS: Neural computations underlying sequence memory consolidation in sleep

CRCNS：睡眠中序列记忆巩固的神经计算

基本信息

批准号：
10646435
负责人：
MAKSIM V BAZHENOV
金额：
$ 35.24万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN DIEGO
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-08-10 至 2025-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10646435
关键词：
Address Animals Behavior Behavioral Biophysical Process Brain Childhood Collaborations Communication Complex Computer Models Coupled Data Data Set Development Electroencephalography Elements Event Exhibits Foundations Generations Goals Hippocampus Human Individual Instruction Intelligence Intervention Knowledge Learning Measurement Mediating Medicine Memory Mental Depression Mental disorders Methods Modeling Motor Mus Neocortex Neurobiology Neurons Outcome Patients Performance Phase Play Post-Traumatic Stress Disorders Principal Investigator Property Psyche structure Research Personnel Retrieval Role Running Schizophrenia Sensory Shapes Sleep Slow-Wave Sleep Synapses Techniques Testing Texture Time Training Travel Weight Whole-Genome Shotgun Sequencing Work awake cognitive performance data modeling density executive function experience experimental study fascinate flexibility genetic manipulation improved in vivo insight memory consolidation neocortical neural neural network novel outcome prediction place fields preservation programs receptive field response sequence learning simulation verbal

项目摘要

The ability to store and retrieve sequentially related information is arguably the foundation of intelligent behavior. It allows us to predict the outcomes of sensory situations, to achieve goals by generating sequences of motor actions, to 'mentally' explore the possible outcomes of different navigational or motor choices, and ultimately to communicate through complex verbal sequences generated by flexibly chaining simpler elemental sequences learned in childhood. Sleep extracts invariant features from the learned information, leading to the generation of explicit knowledge and insight. Despite remarkable progress, including work by PI and co-PI of this project, many critical questions remain about role of sleep in memory and learning. Here we propose to address these questions through the development of computational models that are probed and validated through in vivo experiments in mice. We will explore the hippocampal (HC) and neocortical (NC) mechanisms underlying how sequences are acquired and subsequently consolidated through off-line replay during Slow Wave Sleep (SWS) in a manner that minimizes interference between overlapping and/or reversed sequences and how NC may chain sequence fragments together. We combine computer modelling (Bazhenov) of spiking neural networks that mimic awake and SWS brain dynamics, including NC slow oscillations and HC Sharp Wave Ripples (SWR), with high density neural ensemble recordings (McNaughton) in mice, in a controlled behavioral setting including sequence learning and subsequent, chemogenetically induced SWS, which makes it possible to observe how learned sequence representations in NC evolve spontaneously over prolonged periods of SWS. The PIs have been collaborating on and discussing this topic for the past several years, resulting in specific hypotheses that can be explored in real brains. The project outcome will provide a better understanding of how knowledge is extracted from experience, what brain circuits are involved and how brain dynamics are shaped by the development of a rich internal model of the world, including the ability to predict the outcomes of current situations and one's own actions in that context. RELEVANCE (See instructions): The ability to store and retrieve sequentially related information is the foundation of intelligent behavior and brain executive function. Deficits in this ability, resulting from disruption of brain circuits, are seen in depression, schizophrenia and PTSD. Better understanding of the mechanisms and brain dynamics underlying the acquisition, consolidation and retrieval of sequential information will lead to interventions to improve cognitive performance, memory and learning in healthy subjects and patients with mental illness.

存储和检索顺序相关信息的能力可以说是智能的基础