A generalized phase resetting method for phase-locked modes prediction.
We derived analytically and checked numerically a set of novel conditions for the existence and the stability of phase-locked modes in a biologically relevant master-slave neural network with a dynamic feedback loop. Since neural oscillators even in the three-neuron network investigated here receive multiple inputs per cycle, we generalized the concept of phase resetting to accommodate multiple inputs per cycle. We proved that the phase resetting produced by two or more stimuli per cycle can be recursively computed from the traditional, single stimulus, phase resetting. We applied the newly derived generalized phase resetting definition to predicting the relative phase and the stability of a phase-locked mode that was experimentally observed in this type of master-slave network with a dynamic loop network.
Department of Physics and Astronomy, College of Charleston, Charleston, SC, United States of America.
Sorinel A
SA
Oprisan
Department of Physics and Astronomy, College of Charleston, Charleston, SC, United States of America.
Dave I
DI
Austin
D000200:Action Potentials / Q000502:physiology*; D001921:Brain / Q000502:physiology; D058256:Brain Waves / Q000502:physiology*; D019295:Computational Biology / Q000379:methods; D003198:Computer Simulation; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009474:Neurons / Q000502:physiology*; D009435:Synaptic Transmission / Q000502:physiology*