Delayed Feedback Control of Oscillations in a Spiking Neural Network Model of Aberrant Brain Dynamics

Ioannis Vlachos, Arvind Kumar

Abstract

Open-loop methods for deep-brain stimulation have been effective in controlling aberrant activity associated with various neurological disorders such as Parkinson's disease. Recently, adaptive control strategies have emerged, which promise to increase the efficacy of these existing stimulation methods. Here, we investigate the effects of closed-loop control schemes in networks of spiking neurons that operate in a synchronous irregular regime. In this regime the population activity is highly regular, despite the fact that individual neurons fire stochastically. These oscillations are known to be robust compared to synchronous regular activity and are not easily affected by noise or heterogeneity. We design an appropriate control strategy, based on delayed state-feedback to quench these stochastic oscillations. We also show that our control protocol is able to restore the network transfer function thus overcoming the undesired side-effects of existing methods.

References

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Paper Citation


in Harvard Style

Vlachos I. and Kumar A. (2014). Delayed Feedback Control of Oscillations in a Spiking Neural Network Model of Aberrant Brain Dynamics . In - NEUROTECHNIX, ISBN , pages 0-0


in Bibtex Style

@conference{neurotechnix14,
author={Ioannis Vlachos and Arvind Kumar},
title={Delayed Feedback Control of Oscillations in a Spiking Neural Network Model of Aberrant Brain Dynamics},
booktitle={ - NEUROTECHNIX,},
year={2014},
pages={},
publisher={SciTePress},
organization={INSTICC},
doi={},
isbn={},
}


in EndNote Style

TY - CONF
JO - - NEUROTECHNIX,
TI - Delayed Feedback Control of Oscillations in a Spiking Neural Network Model of Aberrant Brain Dynamics
SN -
AU - Vlachos I.
AU - Kumar A.
PY - 2014
SP - 0
EP - 0
DO -