Suppressing epileptic activity in a neural mass model using a closed-loop proportional-integral controller

Abstract Synchronization has an important role in neural networks, and their dynamics are mostly accompanied by cognitive activities such as memory, learning, and perception. These activities arise from the collective neural behaviors and are not totally understood yet. This paper aims to investigate a cortical model from this perspective. In this paper, we investigated a network of neural populations in a way the dynamics of each node corresponded to the Jansen-Rit neural mass model. First, we put this dynamic on a single mass of four different input levels. Then, we considered a Watts-Strogatz network of Jansen-Rit oscillators. We observed an epileptic activity in the weak input level. The network to change various parameters is considered. The detailed results including the mean times series, phase spaces and power spectrum revealed a wide range of different behaviors such as epilepsy, unimpaired, and a transition between synchrony and asynchrony states. Since the critical state is a dynamic candidate for healthy brains, we considered some measures of criticality and investigated them on phase transition points. We showed that the criticality hypothesis is not all or nothing theory. It means that due to the nature of specific indicators selected for studying the criticality, the phase transition point can be a critical point or not. Indeed, some markers of criticality can exist in phase transition points, and others may not. As a result, we do not claim that neural models show criticality or not, but we can only admit that they have a percentage of criticality.

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Closed-Loop Proportion-Derivative Control of Suppressing Seizures in a Neural Mass Model

2019 IEEE International Symposium on Circuits and Systems (ISCAS) ◽

10.1109/iscas.2019.8702385 ◽

2019 ◽

Author(s):

Lijuan Xia ◽

Ahmed Soltan ◽

Xuzhi Zhang ◽

Andrew Jackson ◽

Russell Tessier ◽

...

Keyword(s):

Closed Loop ◽

Neural Mass Model ◽

Mass Model ◽

Neural Mass ◽

Derivative Control

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Bifurcation Analysis of Jansen's Neural Mass Model

Neural Computation ◽

10.1162/neco.2006.18.12.3052 ◽

2006 ◽

Vol 18 (12) ◽

pp. 3052-3068 ◽

Cited By ~ 98

Author(s):

François Grimbert ◽

Olivier Faugeras

Keyword(s):

Bifurcation Analysis ◽

Cortical Neurons ◽

Input Parameter ◽

Nonlinear Dynamical System ◽

Epileptic Activity ◽

Neural Mass Model ◽

Mass Model ◽

Nonlinear Dynamical ◽

Neural Mass ◽

Model Features

We present a mathematical model of a neural mass developed by a number of people, including Lopes da Silva and Jansen. This model features three interacting populations of cortical neurons and is described by a six-dimensional nonlinear dynamical system. We address some aspects of its behavior through a bifurcation analysis with respect to the input parameter of the system. This leads to a compact description of the oscillatory behaviors observed in Jansen and Rit (1995) (alpha activity) and Wendling, Bellanger, Bartolomei, and Chauvel (2000) (spike-like epileptic activity). In the case of small or slow variation of the input, the model can even be described as a binary unit. Again using the bifurcation framework, we discuss the influence of other parameters of the system on the behavior of the neural mass model.

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Seizure control in a neural mass model by an active disturbance rejection approach

International Journal of Advanced Robotic Systems ◽

10.1177/1729881419890152 ◽

2019 ◽

Vol 16 (6) ◽

pp. 172988141989015

Author(s):

Wei Wei ◽

Xiaofang Wei ◽

Min Zuo ◽

Tao Yu ◽

Yan Li

Keyword(s):

Disturbance Rejection ◽

Closed Loop ◽

Seizure Control ◽

Neural Mass Model ◽

Active Disturbance Rejection Control ◽

Mass Model ◽

Epileptiform Discharges ◽

Active Disturbance Rejection ◽

Disturbance Rejection Control ◽

Neural Mass

A closed-loop neuromodulation automatically adjusts stimuli according to brain response in real time. It is viewed as a promising way to control medically intractable epilepsy. A suitable closed-loop modulation strategy, which is robust enough to unknown nonlinearities, dynamics, and disturbances, is in great need in the clinic. For the specialization of epilepsy, the Jansen’s neural mass model is utilized to simulate the undesired high amplitudes epileptic activities, and active disturbance rejection control is designed to suppress the high amplitudes of epileptiform discharges. With the help of active disturbance rejection control, closed-loop roots of the system are far from the imaginary axis. Time domain response shows that active disturbance rejection control is able to control seizure no matter whether disturbances exist or not. At the same time, frequency domain response presents that enough stability margins and a broader range of tunable controller parameters can be obtained. Stable regions have also been presented to provide guidance to choose the parameters of active disturbance rejection control. Numerical results show that, compared with proportional-integral control, more accurate modulation with less energy can be achieved by active disturbance rejection control. It confirms that the active disturbance rejection control-based neuromodulation solution is able to achieve a desired performance. It is a promising closed-loop neuromodulation strategy in seizure control.

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Comparative Analysis of Advanced Controllers for Standalone WECs for DC Microgrid Applications

10.4018/978-1-6684-4012-4.ch002 ◽

2022 ◽

pp. 38-82

Author(s):

Bhavya Dharmesh Pandya ◽

Siddharth Joshi

Keyword(s):

Comparative Analysis ◽

Wind Energy ◽

Closed Loop ◽

Simulation Analysis ◽

Gain Scheduling ◽

Proportional Integral ◽

Perturb And Observe ◽

Integral Controller ◽

Proportional Integral Controller ◽

Power Point

The small-scale wind energy generation system is one of the solutions to empower the isolated loads and provides a promising solution to decrease the greenhouse effect. This chapter describes the simulation analysis for wind energy conversion system incorporated with maximum power point tracking feature. The MPPT algorithms like variable current perturb and observe algorithm and variable step perturb and observe algorithm are incorporated with WECS. The comparative analysis is done in the closed-loop model in continuous time-varying wind speed. The closed-loop simulation is performed using a conventional fixed gain controller. To address the limitations of the fixed gain controller, the analysis is done using the gain scheduling proportional integral controller and the good gain method to tune the proportional integral controller. The comparative analysis between the fixed gain controller, the gain scheduling proportional integral controller, and the good gain method to tune proportional integral controller for above-stated MPPT methods is shown.

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