We present a demand-controlled method for desynchronization of globally coupled oscillatory networks utilizing a configuration with an observed and stimulated subsystem. The stimulated subsystem is subjected to a proportional-integro-differential (PID) feedback derived from the mean field of the observed subsystem. Our method enables to restore desynchronized states in both subsystems in a robust way. We develop an analytical theory for the Kuramoto model and analytically derive a threshold of the stimulation parameters for the desynchronization transition in ensembles of phase and van der Pol oscillators. We also numerically demonstrate the efficacy of the approach for ensembles of globally coupled Landau-Stuart and relaxation van der Pol ...
Several brain diseases are characterized by abnormal neuronal synchronization. Desynchronization of ...
peer reviewedMotivated by the recent development of Deep Brain Stimulation (DBS) for neurological di...
Highly synchronized neural networks can be the source of various pathologies such as Parkinson's dis...
We present a demand-controlled method for desynchronization of globally coupled oscillatory network...
A novel control method for desynchronization of strongly synchronized populations of interacting osc...
Recently extensive work has been done towards developing methods for effective desynchronization of ...
Effective desynchronization can be exploited as a tool for probing the functional significance of sy...
peer reviewedMotivated by neuroscience applications, and in particular by the deep brain stimulation...
We show that nonlinear delayed feedback opens up novel means for the control of synchronization. In ...
We propose a method for the control of synchronization in two oscillator populations interacting acc...
We present nonlinear delayed feedback stimulation as a technique for effective desynchronization. Th...
<div><p>Many collective phenomena in Nature emerge from the -partial- synchronisation of the units c...
Recently, multisite delayed feedback stimulation was proposed as a novel method for mild and effecti...
Many collective phenomena in Nature emerge from the -partial- synchronisation of the units comprisin...
International audienceThis note introduces two notions of desynchronization for interconnected phase...
Several brain diseases are characterized by abnormal neuronal synchronization. Desynchronization of ...
peer reviewedMotivated by the recent development of Deep Brain Stimulation (DBS) for neurological di...
Highly synchronized neural networks can be the source of various pathologies such as Parkinson's dis...
We present a demand-controlled method for desynchronization of globally coupled oscillatory network...
A novel control method for desynchronization of strongly synchronized populations of interacting osc...
Recently extensive work has been done towards developing methods for effective desynchronization of ...
Effective desynchronization can be exploited as a tool for probing the functional significance of sy...
peer reviewedMotivated by neuroscience applications, and in particular by the deep brain stimulation...
We show that nonlinear delayed feedback opens up novel means for the control of synchronization. In ...
We propose a method for the control of synchronization in two oscillator populations interacting acc...
We present nonlinear delayed feedback stimulation as a technique for effective desynchronization. Th...
<div><p>Many collective phenomena in Nature emerge from the -partial- synchronisation of the units c...
Recently, multisite delayed feedback stimulation was proposed as a novel method for mild and effecti...
Many collective phenomena in Nature emerge from the -partial- synchronisation of the units comprisin...
International audienceThis note introduces two notions of desynchronization for interconnected phase...
Several brain diseases are characterized by abnormal neuronal synchronization. Desynchronization of ...
peer reviewedMotivated by the recent development of Deep Brain Stimulation (DBS) for neurological di...
Highly synchronized neural networks can be the source of various pathologies such as Parkinson's dis...