Modern brain imaging techniques have revolutionized the comprehension of the functioning of the nervous system. The technique of calcium imaging, in particular, has provided radically new opportunities to understand how neurons process and encode information, both individually and collectively. However, the possibility to observe and record the neurons’ activity has also led to the need for adequate statistical methods to extract meaningful insights from these data. In this paper, we delve into the main objectives and challenges associated with a statistical analysis of calcium imaging data. Specifically, we consider a large data repository provided by the Allen Brain Observatory, where the goal is to study how neurons located in the visual cortex respond to different types of stimuli. This repository is an exemplary case study, revealing the multitude of research questions and modeling directions that can emerge from a single experimental study.