Systems Neuroscience of Natural Behaviors in Rodents
Systems Neuroscience of Natural Behaviors in Rodents
复制标题
DOI：
10.1523/jneurosci.1877-20.2020
复制
发表时间：
2021-02-03
影响因子：
5.3
通讯作者：
Datta, Sandeep Robert
中科院分区：
文献类型：
--
作者：
Dennis, Emily Jane;El Hady, Ahmed;Datta, Sandeep Robert
动物在复杂的环境中进化，产生了广泛的行为，包括导航，觅食，猎物捕获和同种相互作用，这些行为在从毫秒到几天的时间尺度上变化。从历史上看，这些行为一直是生态学和动物行为学研究的重点，而系统神经科学主要集中在短时间尺度的行为，可以重复数千次，并发生在高度人工化的环境中。由于机器学习、小型化和计算的最新进展，在更自然的条件下研究自由移动的动物，同时应用系统技术成为可能：执行时间特定的扰动，建模行为策略，以及在动物自由移动时记录大量神经元。这篇综述的作者是一群对系统神经科学、生态学和动物行为学的共同目标深表赞赏的科学家。我们相信这是一个非常令人兴奋的时刻，是一个神经科学家，因为我们有机会成长为一个领域，拥抱跨学科，开放，合作研究，以提供新的见解，并允许研究人员跨学科，物种和规模的知识联系。在这里，我们讨论了行为学，生态学和系统神经科学在我们自己的工作背景下的起源，并强调如何将这些领域的方法结合起来，为我们的研究提供了新的见解。我们希望这篇评论能促进其中的一些互动和联盟，并帮助我们所有人一起做得更好。
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.