The Explanatory Force of Dynamical and Mathematical Models in Neuroscience: A Mechanistic Perspective

Abstract

We argue that dynamical and mathematical models in systems and cognitive neuroscience explain (rather than redescribe) a phenomenon only if there is a plausible mapping between elements in the model and elements in the mechanism for the phenomenon. We demonstrate how this model-to-mechanism-mapping constraint, when satisfied, endows a model with explanatory force with respect to the phenomenon to be explained. Several paradigmatic models including the Haken-Kelso-Bunz model of bimanual coordination and the difference-of-Gaussians model of visual receptive fields are explored.