title: Frequency modulation of large oscillatory neural networks.
abstract: Dynamical systems which generate periodic signals are of interest as models of biological central pattern generators and in a number of robotic applications. A basic functionality that is required in both biological modelling and robotics is frequency modulation. This leads to the question of whether there are generic mechanisms to control the frequency of neural oscillators. Here we describe why this objective is of a different nature, and more difficult to achieve, than modulating other oscillation characteristics (like amplitude, offset, signal shape). We propose a generic way to solve this task which makes use of a simple linear controller. It rests on the insight that there is a bidirectional dependency between the frequency of an oscillation and geometric properties of the neural oscillator's phase portrait. By controlling the geometry of the neural state orbits, it is possible to control the frequency on the condition that the state space can be shaped such that it can be pushed easily to any frequency.
authors: Electronics and Information Systems Department, Ghent University, Sint-Pietersnieuwstraat 41, 9000 , Ghent, Belgium, Francis.wyffels@UGent.be.
authors: Francis
authors: F
authors: Wyffels
authors: Jiwen
authors: J
authors: Li
authors: Tim
authors: T
authors: Waegeman
authors: Benjamin
authors: B
authors: Schrauwen
authors: Herbert
authors: H
authors: Jaeger
mesh_terms: D000818:Animals; D001185:Artificial Intelligence; D003198:Computer Simulation; D003491:Cybernetics; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D016571:Neural Networks, Computer; D012371:Robotics