Experience-dependent modulation of collective behavior in larval zebrafish

Roy Harpaz, Morgan Phillips, Ronan Goel, Florian Engert, Mark C Fishman
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Abstract

Complex group behavior can emerge from simple inter-individual interactions. Commonly, these interactions are considered static and hardwired and little is known about how experience and learning affect collective group behavior. Young larvae use well described visuomotor transformations to guide inter-individual interactions and collective group structure. Here, we use naturalistic and virtual-reality (VR) experiments to impose persistent changes in population density and measure their effects on future visually evoked turning behavior and the resulting changes in group structure. We find that neighbor distances decrease after exposure to higher population densities, and increase after the experience of lower densities. These adaptations develop slowly and gradually, over tens of minutes and remain stable over many hours. Mechanistically, we find that larvae estimate their current group density by tracking the frequency of neighbor-evoked looming events on the retina and couple the strength of their future interactions to that estimate. A time-varying state-space model that modulates agents' social interactions based on their previous visual-social experiences, accurately describes our behavioral observations and predicts novel aspects of behavior. These findings provide concrete evidence that inter-individual interactions are not static, but rather continuously evolve based on past experience and current environmental demands. The underlying neurobiological mechanisms of experience dependent modulation can now be explored in this small and transparent model organism.
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斑马鱼幼体集体行为的经验调控
复杂的群体行为可以从简单的个体间互动中产生。通常,这些互动被认为是静态和硬性的,人们对经验和学习如何影响集体群体行为知之甚少。幼年幼虫使用描述良好的视觉运动转换来引导个体间的互动和集体群体结构。在这里,我们利用自然实验和虚拟现实(VR)实验对种群密度施加持续变化,并测量其对未来视觉诱发的转向行为以及由此导致的群体结构变化的影响。我们发现,在暴露于较高的种群密度后,相邻距离会减少,而在经历较低的种群密度后,相邻距离会增加。这些适应性在数十分钟内缓慢而逐渐地形成,并在数小时内保持稳定。从机理上讲,我们发现幼虫通过跟踪视网膜上邻居诱发的隐现事件的频率来估计其当前的群体密度,并将其未来互动的强度与这一估计值联系起来。一个时变状态空间模型可以根据幼虫以前的视觉社交经验调节它们的社交互动,它能准确地描述我们的行为观察结果,并预测行为的新方面。这些发现提供了具体证据,证明个体间的互动并非一成不变,而是根据过去的经验和当前的环境需求不断演变的。现在,我们可以在这个小而透明的模型生物体中探索依赖经验调节的潜在神经生物学机制。
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