Conclusions
Changes of brain activity are often of greater interest than the current state per se. On the cortical sheet, two-dimensional patterns can be defined by boundaries between high and low states of activity, and their dynamics can be specified by tracking the evolution of these interfaces. Using a simple cMFM, we show here that one can describe the motion of activity fronts with equations of reduced complexity, which nevertheless reproduce the observed dynamics faithfully. This improves our ability to study pattern formation and suggests more generally that modelling the interfaces of patterns, rather than the patterns themselves, may lead to novel, efficient descriptions of brain activity.