Nonlinear dynamics of neurons and networks for vision

To elucidate brain function, it is necessary to simplify dynamical neural systems to tractable proportions. Cortical neurons exhibit complex response patterns mediated by about 12 distinct ionic currents. For many purposes, however, it is possible to describe key response features with a system of just four differential equations containing cubic nonlinearities. Insights gained from these neural equations can then be used to develop a large neural network describing interactions in the cortical form vision system. The network explains a striking perceptual illusion, and an analysis of network dynamics shows that it exhibits highly complex oscillations poised on the edge of chaos