Abstract
Computational models are a useful tool to characterize the mechanisms underlying visual perception. They avoid the ambiguity inherent in verbal model descriptions, and, when published together with the code, they can be (re-)used by different people and their predictions can be replicated in a straight-forward way. For this reason, many journals now require authors to publish their code alongside the paper. While this is a commendable practice, we think it is not yet sufficient, because readers with little background in software engineering might still find it difficult to connect the published code with the theoretical concepts in the paper. With our increased understanding of perceptual processes, the corresponding models become more and more complex. For example, extending purely spatial models by a temporal dimension adds significant complexity to such models. The mental and computational handling of multidimensional structures is objectively difficult and makes it hard for readers to understand relevant model parts, let alone assess their adequacy. We suggest to showcase models accessibly using interactive programming tools (Jupyter). These tools naturally bridge the gap between mathematical model descriptions in the text and corresponding functions in the code. We chose a model that incorporates spatio-temporal processing characteristics of retinal ganglion cells but is still relatively straight-forward. It was presented in a recent paper (2019) in a journal that explicitly encourages the publication of code. We present and visualize functional components of the model individually, together with their respective in- and outputs, helping the reader to understand the components and their interactions. The use of an interactive tool allows the reader to tinker with parameters and observe the resulting effects. Despite best efforts, we encountered a number of ambiguities in the original authors' presentation which can be avoided with a more comprehensive approach of model presentation as the one we advocate here.