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What is going on in the fish's brain? Characterization and Modeling of Neural Dynamics (CNS and ANS and ICNS)

鱼的大脑里发生了什么？

基本信息

批准号：
10686992
负责人：
Florian Engert
金额：
$ 79.63万
依托单位：
HARVARD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-09-25 至 2027-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10686992
关键词：
Affect Algorithms Anatomy Animals Area Autonomic ganglion Autonomic nervous system Behavior Behavioral Behavioral Assay Behavioral Model Biological Assay Brain Calcium Cardiac Cardiovascular system Competence Computational algorithm Data Data Set Electrophysiology (science)Environment Family Fishes Generations Gills Goals Grant Heart Hypothalamic structure Image Imaging technology Individual Knowledge Laboratories Maps Measurement Measures Membrane Mind Modeling Motor Motor output Nature Nervous System Neural Interconnection Neurons Output Oxygen Pathway interactions Pattern Performance Physiological Play Population Preparation Process Quality Control Regulation Research Role Sensorimotor functions Synapses System Technology Testing Transgenic Organisms Validation Visualization Weight Zebrafish connectome data modeling design experimental study in vivo member mind body interaction neural neural circuit neural model neuroregulation novel optogenetics patch clamp reconstruction respiratory response sensory input sensory stimulus simulation environment statistics virtual

项目摘要

Project 2 It is the behavioral algorithms that dictate the questions and framework for any model of neural implementation. Thus, to discover how behavioral algorithms are implemented and to generate a realistic brain-body circuit model for larval zebrafish, we need, in addition to knowledge about the anatomical structure of the circuits, detailed information about neural activity patterns during behavior. Further, behavioral algorithms must be implemented in the context of the embodied animal, which is subject to physiological demands, fluctuations and constraints. In order to accommodate both of these requirements, we will estimate and incorporate these physiological state variables into our modeling framework. In order to obtain the necessary datasets, we propose to add detailed measurements of heart and gills, as well as body wide recordings from the autonomic nervous system (ANS) and the intrinsic cardiac nervous system (ICNS) to our experimental repertoire. Such recordings will be combined with established brain wide imaging technologies, where we will focus on critical regions, such as the hypothalamus and various other areas that were already identified to play an important role in the modulation of behaviors and internal states. To facilitate the quantification and control of state-dependent variability, we have also designed a set of behavioral assays where environmental context is modulated to induce specific changes in the animal's internal and autonomic state. The comprehensive data sets collected in these experiments then allow for the generation of a family of realistic circuit models that could, in principle, implement the behavioral algorithms and that can reproduce and emulate the recorded neural and cardiac activity patterns. These realistic models allow for the generation of specific predictions and hypotheses about many of the unconstrained parameters in the underlying circuits. Such parameters include specific connectivity patterns, the synaptic weights, the excitability of membranes and many more. In order to constrain this large variety of variables one needs to apply a variety of independent approaches. To that end we will take advantage of the extensive experimental toolset already developed in the context of the current U19 grant, which includes the use of optogenetics based circuit interrogation, targeted electrophysiology and sparse connectomics tracing in overlaid EM volumes. Many of these experimental approaches require tethered behavioral preparations which are already established in our laboratories. Such preparations provide the ideal setting for brain wide imaging and targeted perturbation, and they will therefore facilitate the generation of a further refined set of validated circuit models for our various behavioral assays. To summarize, our goal is to first validate and constrain a set of realistic circuit models that we have already generated in the context of the current U19, to integrate these validated models with a novel framework we will generate for the animal's autonomic state, and ultimately to combine all of them into a composite realistic multiscale circuit model of the zebrafish brain and body. This multiscale circuit model will describe how all sensory stimuli, from the outside world as well as from inside the body, are encoded and transformed into distributed neural activity that generates the motor sequences that constitute the final output of the system.

项目2