Sensorimotor processing, decision making, and internal states: towards a realistic multiscale circuit model of the larval zebrafish brain

感觉运动处理、决策和内部状态：建立幼虫斑马鱼大脑的真实多尺度电路模型

基本信息

批准号：
10241477
负责人：
Florian Engert
金额：
$ 362.97万
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 2022-08-31
项目状态：
已结题

项目摘要

Project Summary - A realistic multiscale circuit model of the larval zebrafish brain The working group of the BRAIN initiative (BRAIN 2025, a Scientific Vision) identified “the analysis of circuits of interacting neurons as being particularly rich in opportunity, with potential for revolutionary advances”. They further pointed out that “truly understanding a circuit requires identifying and characterizing the component cells, defining their synaptic connections with one another, observing their dynamic patterns of activity as their circuit functions in vivo during behavior, and perturbing these patterns to test their significance. It also requires an understanding of the algorithms that govern information processing within a circuit and between interacting circuits in the brain as a whole”. We propose to generate a realistic multiscale circuit model of the larval zebrafish brain – the multiscale virtual fish (MVF), which is well aligned with the BRAIN initiative's guidelines. The model will be based on algorithms inferred from behavioral assays and it will span spatial ranges across three levels: from the nanoscale at the synaptic level, to the microscale describing local circuits, to the macroscale brain-wide activity patterns distributed across many regions. The model will be constrained and validated by optogenetic interrogation and sparse connectomics of identified circuit elements 1 ,2. The ultimate purpose is to explain and simulate the quantitative and qualitative nature of behavioral outputs in response to sensory inputs across various timescales, and to explore how these findings might integrate with parallel work in two other important behavioral model systems, the Drosophila larva and the rat. Our prior U01 project achieved the first instantiation of this model, whereby we successfully dissected the optomotor response (OMR)1 , where a larval zebrafish will turn and swim to match the direction of a whole-field visual stimulus 3–5. We will build on this model by achieving three further aims: First, we will expand the OMR project with four additional ethologically relevant behaviors: phototaxis, rheotaxis, escape, and hunting. We will extract the precise algorithms underlying each behavior and develop a version of the circuit model to understand their neural implementation. Second, we will further refine the model to account for multimodal integration and decision making, events that naturally happen when conflicting stimuli driving different behaviors are presented simultaneously. For example, a fish might be driven to execute a left turn by whole field motion moving to the left (OMR), while simultaneously being induced to turn right by increased brightness on its right side (phototaxis). Third, we will examine how internal brain states, such as hunger or stress, influence and modulate the specific behaviors (Aim 1) or behavioral interactions (Aim 2). Implementation of neurochemical modulation into the framework of the MVF will be achieved through simulation of highly conserved neuromodulatory neurotransmitter systems such as serotonin, acetylcholine, epinephrine and dopamine. To uncover generalizable principles of circuit design and function, we will compare our findings with those from two other model systems, the fruit fly larva and the rat. This will serve to elucidate the rules, motifs and algorithms of neural circuit function that transcend the potential idiosyncrasies of any given model.

项目摘要 - 幼虫斑马鱼大脑的现实多尺度电路模型大脑计划的工作组（大脑2025，科学视觉）确定了“电路的分析将神经元互动是特别丰富的机会，并具有革命进步的潜力。” 指出“真正了解电路需要识别和表征组件单元，并定义其突触连接相互连接，观察其动态活动模式，因为它们的电路在体内功能在行为过程中，并扰动这些模式以测试其重要性。它还需要了解算法控制电路内的信息处理以及整个大脑中的相互作用电路之间。” 我们建议生成幼虫斑马鱼大脑的逼真的多尺度电路模型 - 多尺度虚拟鱼（MVF），它与大脑计划的指南非常吻合。该模型将基于推断的算法从行为分析到它将跨越三个层次的空间范围：从突触层的纳米级，到描述局部电路的微观图，分布在许多区域的宏观脑部整个活动模式。模型将受到光遗传学询问和稀疏连接的限制和验证。元素1,2。最终目的是解释和模拟行为输出的定量和定性性质响应各个时间尺度的感觉输入，并探讨这些发现如何与并行集成在另外两个重要的行为模型系统中工作，果蝇幼虫和大鼠。我们先前的U01项目实现了该模型的第一个实例化，我们成功地剖析了验光剂响应（OMR）1，其中幼虫斑马鱼会转动和游泳以匹配全场视觉刺激3-5的方向。我们将通过实现三个目标来建立在该模型的基础上：首先，我们将扩大OMR项目的额外四个。与伦理学相关的行为：光性，风湿性，逃生和狩猎。我们将提取精确的算法每种行为的基础并开发了电路模型的版本以了解其神经实现。第二，我们将进一步完善模型以说明多模式集成和决策，自然发生的事件当相互冲突的刺激驱动不同行为时，会很简单。例如，鱼可能被驱车到执行左转弯的整个场运动向左移动（OMR），同时诱使向右转动右侧的亮度提高（光疗）。第三，我们将研究内部大脑状态，例如饥饿或压力，影响和调节特定行为（AIM 1）或行为相互作用（AIM 2）。实施通过模拟高度保守的神经化学调制将实现MVF框架神经调节性神经递质系统，例如5-羟色胺，乙酰胆碱，肾上腺素和多巴胺。为了揭示电路设计和功能的可概括原则，我们将与两个的发现进行比较其他模型系统，果蝇幼虫和大鼠。这将有助于阐明中立的规则，基础和算法超越任何给定模型的潜在特质的电路函数。