One of the greatest research challenges of this century is to understand the neural basis for how behavior emerges in brain-body-environment systems. To this end, research has flourished along several directions but have predominantly focused on the brain. While there is in an increasing acceptance and focus on including the body and environment in studying the neural basis of behavior, animal researchers are often limited by technology or tools. Computational models provide an alternative framework within which one can study model systems where ground-truth can be measured and interfered with. These models act as a hypothesis generation framework that would in turn guide experimentation. Furthermore, the ability to intervene as we please, allows us to conduct in-depth analysis of these models in a way that cannot be performed in natural systems. For this purpose, information theory is emerging as a powerful tool that can provide insights into the operation of these brain-body-environment models. In this work, I provide an introduction, a review and discussion to make a case for how information theoretic analysis of computational models is a potent research methodology to help us better understand the neural basis of behavior.

中文翻译：

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计算模型的信息论分析作为理解行为神经基础的工具

本世纪最大的研究挑战之一是了解大脑-身体-环境系统中行为如何出现的神经基础。为此，研究在几个方向上蓬勃发展，但主要集中在大脑上。虽然越来越多的人接受并关注在研究行为的神经基础时将身体和环境包括在内，但动物研究人员往往受到技术或工具的限制。计算模型提供了一种替代框架，可以在其中研究可以测量和干扰地面实况的模型系统。这些模型充当假设生成框架，进而指导实验。此外，根据我们的意愿进行干预的能力使我们能够以在自然系统中无法执行的方式对这些模型进行深入分析。为此，信息论正在成为一种强大的工具，可以提供对这些脑-身体-环境模型运行的见解。在这项工作中，我提供了一个介绍、回顾和讨论，以说明计算模型的信息理论分析如何成为一种有效的研究方法，以帮助我们更好地理解行为的神经基础。