Animals evolved in complex environments, producing a wide range of behaviors, including navigation, foraging, prey capture, and conspecific interactions, which vary over timescales ranging from milliseconds to days. Historically, these behaviors have been the focus of study for ecology and ethology, while systems neuroscience has largely focused on short timescale behaviors that can be repeated thousands of times and occur in highly artificial environments. Thanks to recent advances in machine learning, miniaturization, and computation, it is newly possible to study freely moving animals in more natural conditions while applying systems techniques: performing temporally specific perturbations, modeling behavioral strategies, and recording from large numbers of neurons while animals are freely moving. The authors of this review are a group of scientists with deep appreciation for the common aims of systems neuroscience, ecology, and ethology. We believe it is an extremely exciting time to be a neuroscientist, as we have an opportunity to grow as a field, to embrace interdisciplinary, open, collaborative research to provide new insights and allow researchers to link knowledge across disciplines, species, and scales. Here we discuss the origins of ethology, ecology, and systems neuroscience in the context of our own work and highlight how combining approaches across these fields has provided fresh insights into our research. We hope this review facilitates some of these interactions and alliances and helps us all do even better science, together.

动物在复杂的环境中进化，产生各种各样的行为，包括导航、觅食、捕获猎物和同种相互作用，这些行为的时间尺度从几毫秒到几天不等。从历史上看，这些行为一直是生态学和动物行为学研究的焦点，而系统神经科学主要关注可以重复数千次并在高度人工环境中发生的短时间尺度行为。由于机器学习、微型化和计算方面的最新进展，在应用系统技术的同时，研究在更自然的条件下自由移动的动物成为可能：执行特定时间的扰动、建模行为策略以及在动物活动时记录大量神经元。自由移动。这篇综述的作者是一群对系统神经科学、生态学和行为学的共同目标有着深刻理解的科学家。我们相信，对于一名神经科学家来说，这是一个极其激动人心的时刻，因为我们有机会作为一个领域不断发展，拥抱跨学科、开放、协作的研究，以提供新的见解，并允许研究人员将跨学科、跨物种和跨规模的知识联系起来。在这里，我们在自己的工作背景下讨论了行为学、生态学和系统神经科学的起源，并强调了这些领域的结合方法如何为我们的研究提供了新的见解。我们希望这次审查能够促进其中一些互动和联盟，并帮助我们所有人共同做出更好的科学研究。