Mechanistic neural circuit models and principles

机械神经回路模型和原理

• 批准号: 10294675
• 负责人: Ila R. Fiete
• 金额: $ 47.38万
• 依托单位: COLUMBIA UNIV NEW YORK MORNINGSIDE
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-15 至 2026-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10294675
• 关键词: Accounting; Anatomy; Animals; Architecture; Attention; Bar Codes; Behavior; Behavioral; Benchmarking; Biological; Brain; Brain region; Cellular Structures; Collaborations; Communication; Coupled; Data; Data Analyses; Decision Making; Development; Dimensions; Electrophysiology (science); Environment; Experimental Designs; Future; Genetic Markers; Goals; Infrastructure; International; Laboratories; Learning; Left; Link; Measurement; Methods; Modeling; Mus; Neural Network Simulation; Output; Performance; Population; Process; Research Personnel; Rewards; Running; Sensory; Standardization; Statistical Data Interpretation; Statistical Models; Stimulus; Structure; Synapses; Task Performances; Testing; Training; Work; base; cell type; data sharing; design; experimental study; learning strategy; network models; neural circuit; neural model; neuromechanism; novel; operation; predictive modeling; recurrent neural network; relating to nervous system; sensory input; theories; tool

Summary/Abstract, Project 3 Even in the same environment, an animal may make different decisions on different occasions, because its internal state, such as engagement in a task, interacts powerfully with external inputs to determine behavior. This proposal’s overarching goal is to understand how internal states influence decisions and to identify the underlying neural mechanisms. The team is part of the International Brain Laboratory (IBL), an established consortium that has developed a standardized mouse decision-making task and standardized methods for training, neural measurement, and data analysis, along with a working, scalable infrastructure for sharing data. The goal of Project 3 is to synthesize the findings of experimental Projects 1, 2, 4, and 5 into circuit-level mechanistic models of the IBL task. The task involves hierarchical, probabilistic decision-making through sensory evidence integration to make left-right decisions about where the stimulus is on the current trial, along with integration on a longer timescale to estimate the slowly varying left-right biases in where the stimuli are more likely to appear. Initial models not only will be trained to reproduce expert-level task performance, but also will include general biological constraints on neural dynamics and anatomical connectivity gradients. They will be analyzed for their learning dynamics, and for which parameters are the handles through which internal states exert their effects on circuit computation and dynamics. These models will yield predictions on multiple levels of abstraction: state-space predictions, network structure predictions, and anatomical predictions. The resulting models will be deployed in a tight loop with all experimental projects, to guide experimental design; serve as ground-truth testbeds for perturbative and causal connectivity analysis studies; and link statistical analysis results from data with mechanistic interpretations. The results of these experiment-model prediction comparisons will then be used to further refine and elaborate the models. Project 3 researchers will incorporate the experimentally derived neural activity data, causal connectivity by anatomical region data, and structural cell-type and connectivity data to further constrain the models. Finally, Project 3 will also generate highly simplified abstract neural circuit models, using novel methods of model compression to elucidate the general principles underlying hierarchical decision-making in the brain. All this work involves the use and de novo development of cutting-edge modeling, statistical, and data analysis tools. The work of Project 3 will thus deliver a mechanistic circuit- level understanding of this proposal’s overarching hypothesis that information flow and communication across brain regions during decision-making depends on internal state.

摘要/摘要，项目3