Real-time, all-optical interrogation of neural microcircuitry in the pretectum

对顶盖神经微电路进行实时、全光学询问

基本信息

批准号：
9978318
负责人：
Eva Aimable Naumann
金额：
$ 71.35万
依托单位：
DUKE UNIVERSITY
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：
2020-05-01 至 2022-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9978318
关键词：
3-Dimensional Algorithms Area Behavior Behavioral Biological Models Brain Calcium Cells Communities Complex Computer software Computing Methodologies Data Data Analyses Development Equilibrium Family Future Generations Goals Image Individual Lead Maps Measures Methodology Methods Microscopy Modeling Motor Nervous system structure Neurons Neurophysiology - biologic function Neurosciences Online Systems Optical Methods Optics Output Pattern Play Preparation Process Randomized Resolution Role Running Scientist Sensory Shapes Stimulus System Techniques Technology Testing Time Visual Motion Work Zebrafish base behavioral response brain volume cell type computational platform experimental study extrastriate visual cortex nervous system disorder neural circuit novel open source optogenetics relating to nervous system response sensor time use tool two photon microscopy visual motor visual processing

项目摘要

Abstract One of the major barriers to understanding how neural circuits give rise to behavior is that typical experimental preparations make it difficult to study these circuits across different brain areas. Recent advances in microscopy and calcium sensors have made it possible to simultaneously record up to thousands of individual neurons, and optical methods have made it possible to stimulate hundreds at a time, but current approaches, which stimulate only subsets of predetermined neurons, are not adequate for dissecting large-scale neural circuits. Here, we propose to develop a novel integrated experimental- computational platform to test neural circuit hypotheses of the zebrafish optomotor response, a representative sensorimotor behavior. This platform will allow us to characterize the relationships among functionally defined groups of neurons as the data are collected in real-time. By using prior-guided algorithms that adaptively choose scanless 3D holographic photostimulation patterns of up to hundreds of neurons in response to previously observed data, we will be able to exponentially increase data efficiency, simultaneously inferring multiple classes of functional connections between visually responsive neurons in the zebrafish pretectum and their downstream targets. Once established, this approach will allow us to perform adaptive experiments that selectively perturb neural function based on function, accelerating the process of model generation and hypothesis testing. Moreover, these tools will be applicable to other types of calcium imaging data, with broad implications for systems neuroscience.

抽象的了解神经回路如何产生行为的主要障碍之一是典型实验制剂使得很难研究各个大脑区域的这些电路。最近的显微镜和钙传感器的进步使同时记录到成千上万个单独的神经元和光学方法使得在A处刺激数百个时间，但是当前的方法仅刺激预定神经元的子集，这是不够的用于解剖大型神经回路。在这里，我们建议开发一种新颖的综合实验性 - 测试斑马鱼验光反应的神经回路假设的计算平台，一个代表性的感觉运动行为。这个平台将使我们能够表征功能定义的神经元组，因为数据是实时收集的。通过使用先前的引导自适应选择无扫描的3D全息刺激模式的算法多达数百种神经元响应先前观察到的数据，我们将能够成倍增加数据效率，同时推断出视觉响应之间的多个类别的功能连接斑马鱼预性及其下游靶标的神经元。建立后，这种方法将允许我们执行自适应实验，以基于功能有选择性扰动神经功能，加速模型产生和假设检验的过程。而且，这些工具将是适用于其他类型的钙成像数据，对系统神经科学具有广泛的影响。