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

项目摘要-一个真实的多尺度电路模型的幼体斑马鱼大脑 BRAIN倡议（BRAIN 2025，科学愿景）的工作组确定了“对大脑回路的分析”。 相互作用的神经元特别富有机会，具有革命性进步的潜力。他们进一步 他指出，“真正理解一个电路需要识别和表征组成单元，定义它们的 突触之间的连接，观察它们在体内电路功能时的动态活动模式 在行为过程中，并扰乱这些模式来测试它们的意义。它还需要对算法的理解 控制着整个大脑中一个回路内和相互作用的回路之间的信息处理。 我们建议生成一个逼真的多尺度电路模型的幼体斑马鱼大脑-多尺度虚拟鱼 (MVF)，这与BRAIN倡议的指导方针非常一致。该模型将基于推断的算法 它将跨越三个层次的空间范围：从突触水平的纳米级， 从描述局部回路的微观尺度，到分布在许多区域的宏观尺度的全脑活动模式。的 模型将通过识别电路的光遗传学询问和稀疏连接组学进行约束和验证 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 响应不同时间尺度上的感官输入，并探索这些发现如何与平行整合 在另外两个重要的行为模型系统中工作， 果蝇幼虫和老鼠。 我们之前的U 01项目实现了该模型的第一个实例化，从而我们成功地解剖了optomotor 响应（OMR）1 ，其中幼斑马鱼将转向并游泳以匹配全场视觉刺激的方向3-5。 我们会在这个模式的基础上，进一步达致三个目的：第一，我们会扩大“流动资源报告”计划， 行为学相关行为：趋光性、趋流性、逃跑和狩猎。我们将提取精确的算法 每个行为的基础，并开发一个版本的电路模型，以了解他们的神经实现。第二、 我们将进一步完善该模型，以解释多模式集成和决策，这些事件自然发生 当驱动不同行为的冲突刺激同时出现时。例如，一条鱼可能会被驱赶到 通过向左移动的全场运动（OMR）执行左转，同时通过以下方式诱导右转 右侧亮度增加（趋光性）。第三，我们将研究大脑内部的状态，如饥饿或 压力，影响和调节特定行为（目标1）或行为互动（目标2）。执行 神经化学调制到MVF的框架将通过模拟高度保守的 神经调节神经递质系统，如血清素、乙酰胆碱、肾上腺素和多巴胺。 为了揭示电路设计和功能的普遍原则，我们将把我们的发现与两个 其他模型系统，果蝇幼虫和大鼠。这将有助于阐明神经网络的规则、基序和算法。 超越任何给定模型的潜在特性的电路功能。

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.