• DocumentCode
    74862
  • Title

    Control and Synchronization of Neuron Ensembles

  • Author

    Jr-Shin Li ; Dasanayake, Isuru ; Ruths, Justin

  • Author_Institution
    Dept. of Electr. & Syst. Eng., Washington Univ., St. Louis, MO, USA
  • Volume
    58
  • Issue
    8
  • fYear
    2013
  • fDate
    Aug. 2013
  • Firstpage
    1919
  • Lastpage
    1930
  • Abstract
    Synchronization of oscillations is a phenomenon prevalent in natural, social, and engineering systems. Controlling synchronization of oscillating systems is motivated by a wide range of applications from surgical treatment of neurological diseases to the design of neurocomputers. In this paper, we study the control of an ensemble of uncoupled neuron oscillators described by phase models. We examine controllability of such a neuron ensemble for various phase models and, furthermore, study the related optimal control problems. In particular, by employing Pontryagin´s maximum principle, we analytically derive optimal controls for spiking single- and two-neuron systems, and analyze the applicability of the latter to an ensemble system. Finally, we present a robust computational method for optimal control of spiking neurons based on pseudospectral approximations. The methodology developed here is universal to the control of general nonlinear phase oscillators.
  • Keywords
    approximation theory; biocontrol; controllability; maximum principle; neural nets; nonlinear control systems; oscillations; synchronisation; Pontryagin maximum principle; controllability; neurocomputers; neurological diseases; neuron ensemble synchronization; nonlinear phase oscillators; optimal control problems; oscillating systems; phase models; pseudospectral approximations; spiking single-neuron systems; spiking two-neuron systems; surgical treatment; uncoupled neuron oscillator ensemble control; Controllability; Mathematical model; Neurons; Optimal control; Oscillators; Synchronization; Vectors; Controllability; Lie algebra; optimal control; pseudospectral methods; spiking neurons;
  • fLanguage
    English
  • Journal_Title
    Automatic Control, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9286
  • Type

    jour

  • DOI
    10.1109/TAC.2013.2250112
  • Filename
    6472024