Abstract: Mathematical cognition is a branch of cognitive science that aims at understanding various aspects of numerical processing in the brain. The field has been receiving an increasing amount of attention during the past two decades, and due to the contributions from such fields as experimental psychology, neuroscience and computational modeling, substantial progress has been made. A novel tool that can be used for the benefit of mathematical cognition studies is robotic modeling, which has a principal advantage over traditional computational modeling methods: it inherently takes into account the aspect of embodiment. This is in line with the growing amount of evidence that many aspects of human mathematical thought (including the number concept itself, despite it's pure and abstract appeal), are deeply rooted in our very basic interactions with the environment.
The presentation will start with a short overview of the up-to-date mathematical cognition research and some of the most interesting findings. Subsequently, we will take a closer look at certain manifestations of an intrinsic connection between representations of number and space in the brain. Building on previous purely computational approaches to model these phenomena, a robotic model of such interactions designed for the iCub humanoid robot will be introduced. We will show that the application of robotic modeling enabled us to achieve two important goals. First, it lead to a model that is less arbitrary than previous computational models. Second, it enabled us to show how certain characteristic patterns of connections, crucial for reproducing aforementioned behavioral phenomena, can emerge as a result of a simple developmental process due to the robot morphology and correlations present in the environment.