Functional Analysis of Whole-Brain Dynamics in Learning

学习中全脑动态的功能分析

• 批准号: 10527358
• 负责人: Hang Lu
• 金额: $ 47.49万
• 依托单位: HARVARD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-12-01 至 2024-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10527358
• 关键词: Acute; Address; Affect; Anatomy; Animal Model; Animals; Area; Behavior; Behavioral; Biochemical; Brain; Brain imaging; Brain region; Caenorhabditis elegans; Cells; Characteristics; Communication; Complex; Data; Defect; Development; Dimensions; Engineering; Exhibits; Food; Foundations; Genetic; Genetic Identity; Glean; Goals; Head; Human; Image; Impairment; Individual; Interneurons; Intervention; Invertebrates; Learning; Learning Module; Maps; Measures; Methods; Mission; Modeling; Molecular; Molecular Genetics; Nematoda; Nervous System; Nervous System Physiology; Neurons; Neurosciences; Olfactory Learning; Optics; Organism; Outcome; Pattern; Play; Process; Property; Psychophysics; Regulation; Research; Resolution; Role; Sensory; Sensory Process; Smell Perception; Structure; System; Systems Analysis; Taste Perception; Techniques; Testing; Therapeutic; Time; Training; Work; behavior test; connectome; design; experience; genetic makeup; in vivo calcium imaging; innovation; insight; learned behavior; learning ability; learning engagement; nervous system disorder; neural; neuron component; pathogenic bacteria; prevent; sensory input; spatiotemporal; temporal measurement; therapy design; tool

PROJECT SUMMARY Learning is a complex process, and likely involves many areas of the brain that detect and process sensory inputs, integrate experience, and display behavior. Consistently, various neurological diseases that impair different brain areas are associated with profound defects in learning. Thus, bridging different spatial scales and understanding the dynamics of different brain regions are essential to understanding how learning occurs and potentially designing strategies to mitigate learning deficiency. However, it is currently not possible to achieve these goals in most experimental systems, and our understanding of learning is limited by the technical approaches by which either local circuit and cellular properties or coarse psychophysical parameters underlying learning are measured. Here, we propose to address these fundamental questions in a reduced system – the nervous system of the nematode C. elegans. The rationale is that the wiring and genetic make-up of this network are well known, probing whole-brain dynamics with single-cell resolution with exquisite temporal resolution is technically ready for C. elegans, and the fundamental principles for the development and the function of the nervous system are well conserved between C. elegans and more complex animal models. Further, C. elegans exhibits many forms of learning, similar to those displayed by higher organisms in behavioral characteristics and molecular cellular underpinnings. Particularly, we will use an olfactory learning paradigm whereby C. elegans learns to avoid the odorants of pathogenic bacteria, a type of learning similar to the Garcia effect through which many animals, including humans, learn to avoid the smell and/or taste of a food that makes them ill. Our long-term goal is to understand how learning is encoded and executed by the function of the whole brain, and to inform the design of potential therapeutic strategies. The central hypothesis of this project is that learning engages global activity and the learned information is encoded in distinct functional modules. Specifically, we will test whether learned information is encoded in the learning-dependent changes in the activity patterns of individual functional modules and/or the interactions among the modules. To this end, we aim to image and analyze multi-cell and whole-brain dynamics under naive and learned conditions to characterize how learning alters the structure of the brain activities; further, we will introduce perturbations to the whole-brain dynamics and examine the consequences for learning. This work is innovative because (1) it brings a conceptual advance to understanding learning across scales, (2) it introduces technical advancement in whole-brain imaging and analyses, and (3) it demonstrates perturbation strategies for altering whole-brain dynamics that have behavioral consequences. It is significant, because it tests several highly plausible and likely conserved cellular and whole-brain dynamic models for learning and examine their behavioral consequences, it informs and facilitates learning studies in other systems, and it paves the way for designing interventions.

项目摘要 学习是一个复杂的过程，很可能涉及大脑的许多领域，以检测和处理感官 输入，集成经验和显示行为。一致地，各种损害的神经疾病 不同的大脑区域与学习中的深刻缺陷有关。那，桥接不同的空间尺度 了解不同大脑区域的动态对于了解学习的发生至关重要 并可能设计策略来减轻学习缺乏。但是，目前不可能 在大多数实验系统中实现这些目标，我们对学习的理解受到 局部电路和蜂窝特性或粗糙心理物理的技术方法 测量学习的参数。在这里，我们建议解决这些基本问题 降低的系统 - 线虫C.秀隐杆菌的神经系统。理由是接线和 该网络的遗传组成是众所周知的，可以通过单细胞分辨率探测全脑动力学 通过独家临时分辨率在技术上可以为秀丽隐杆线虫做好准备，以及 神经系统的发育和功能很好地构成了秀丽隐杆线虫和更多 复杂的动物模型。此外，秀丽隐杆线虫表现出多种形式的学习，类似于 行为特征和分子细胞基础上的较高生物体。特别是，我们将使用 嗅觉学习范式，秀丽隐杆线虫学会避免致病细菌的气味 类型的学习类型类似于加西亚效应，包括人类在内的许多动物学会避免 使它们生病的食物的气味和/或味道。我们的长期目标是了解学习的方式 由整个大脑的功能编码和执行，并告知潜在疗法的设计 策略。该项目的核心假设是学习与全球活动和学识渊博 信息在不同的功能模块中编码。具体来说，我们将测试是否学到的信息 在各个功能模块的活动模式和/或 模块之间的相互作用。为此，我们旨在对多细胞和全脑进行成像和分析 在天真和学习的条件下的动态，以表征学习如何改变大脑的结构 活动;此外，我们将向整个脑动力学介绍扰动并检查后果 学习。这项工作具有创新性，因为（1）为了解学习带来了概念上的进步 在范围内，（2）它引入了全脑成像和分析的技术进步，（3） 展示了改变具有行为后果的全脑动力学的扰动策略。 它很重要，因为它测试了几个高度合理且可能保守的细胞和全脑 学习和检查其行为后果的动态模型，它为学习提供了信息和促进 在其他系统中进行研究，并为设计干预措施铺平了道路。