Discrete and Continuous Dynamical Systems · 2010 · 40 citations · 26 references
Life SciencesElectrical EngineeringNeuroscienceComputational NeuroscienceDynamical SystemsNeural EngineeringBiophysical Neuron ModelingControl TheoryNeural Circuit DynamicsNeural Circuit ModelingNeuronal DynamicsSpiking Neural NetworksEnergy-optimal ControlEvent-based ModelingImpulsive ControlNeuron DynamicsPacemaker NeuronsSpike TrainsSpiking Neural Network ModelsSpiking Neuron Models
This paper explores event-based feedback schemes for controlling spike timing in phase models of neurons with the constraint of a charge-balanced stimulus over a period of stimulation. We present an energy-optimal control system based on variational methods. We also present a biologically-inspired quasi-impulsive control system that, mimicking the signaling behavior of real neurons, can achieve reference phase tracking. Applied to a pacemaker-driven ensemble, this control can achieve desynchronization using a set of charge-balanced stimuli.
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