Dynamical Resetting of the Human Brain at Epileptic Seizures: Application of Nonlinear Dynamics and Global Optimization Techniques

2004 ◽  
Vol 51 (3) ◽  
pp. 493-506 ◽  
Author(s):  
L.D. Iasemidis ◽  
D.-S. Shiau ◽  
J.C. Sackellares ◽  
P.M. Pardalos ◽  
A. Prasad
Keyword(s):  
Nonlinear Dynamics ◽  
Global Optimization ◽  
Human Brain ◽  
Epileptic Seizures ◽  
Optimization Techniques

scholarly journals Locating Objects in the Plane Using Global Optimization Techniques

2009 ◽  
Vol 34 (4) ◽  
pp. 837-858 ◽  
Author(s):  
Rafael Blanquero ◽  
Emilio Carrizosa ◽  
Pierre Hansen
Keyword(s):  
Global Optimization ◽  
Optimization Techniques

An Efficient Approach to Define the Input Stimuli to Suppress Epileptic Seizures Described by the Epileptor Model

2020 ◽  
Vol 30 (11) ◽  
pp. 2050062
Author(s):  
João Angelo Ferres Brogin ◽  
Jean Faber ◽  
Douglas Domingues Bueno
Keyword(s):  
Nonlinear Dynamics ◽  
Mathematical Model ◽  
Exact Solution ◽  
Feedback Control ◽  
Epileptic Seizures ◽  
Neural Dynamics ◽  
Practical Application ◽  
Control Gain ◽  
The World ◽  
The Mathematical Model

Epilepsy affects about 70 million people in the world. Every year, approximately 2.4 million people are diagnosed with epilepsy, two-thirds of them will not know the etiology of their disease, and 1% of these individuals will decease as a consequence of it. Due to the inherent complexity of predicting and explaining it, the mathematical model Epileptor was recently developed to reproduce seizure-like events, also providing insights to improve the understanding of the neural dynamics in the interictal and ictal periods, although the physics behind each parameter and variable of the model is not fully established in the literature. This paper introduces an approach to design a feedback-based controller for suppressing epileptic seizures described by Epileptor. Our work establishes how the nonlinear dynamics of this disorder can be written in terms of a combination of linear sub-models employing an exact solution. Additionally, we show how a feedback control gain can be computed to suppress seizures, as well as how specific shapes applied as input stimuli for this purpose can be obtained. The practical application of the approach is discussed and the results show that the proposed technique is promising for developing controllers in this field.

scholarly journals Nonlinear dynamics of epileptic seizures on basis of intracranial EEG recordings

1997 ◽  
Vol 9 (4) ◽  
pp. 249-270 ◽  
Author(s):  
Jan Pieter M. Pijn ◽  
Demetrios N. Velis ◽  
Marcel J. van der Heyden ◽  
Jaap DeGoede ◽  
Cees W. M. van Veelen ◽  
...  
Keyword(s):  
Nonlinear Dynamics ◽  
Epileptic Seizures ◽  
Intracranial Eeg ◽  
Eeg Recordings

scholarly journals Designing Patient-Specific Optimal Neurostimulation Patterns for Seizure Suppression

2018 ◽  
Vol 30 (5) ◽  
pp. 1180-1208 ◽  
Author(s):  
Roman A. Sandler ◽  
Kunling Geng ◽  
Dong Song ◽  
Robert E. Hampson ◽  
Mark R. Witcher ◽  
...  
Keyword(s):  
Global Optimization ◽  
Closed Loop ◽  
Epileptic Seizures ◽  
Patient Specific ◽  
Spontaneous Seizure ◽  
Global Optimization Algorithm ◽  
Neuron Network ◽  
Seizure State ◽  
Wide Range ◽  
Stimulation Pattern

Neurostimulation is a promising therapy for abating epileptic seizures. However, it is extremely difficult to identify optimal stimulation patterns experimentally. In this study, human recordings are used to develop a functional 24 neuron network statistical model of hippocampal connectivity and dynamics. Spontaneous seizure-like activity is induced in silico in this reconstructed neuronal network. The network is then used as a testbed to design and validate a wide range of neurostimulation patterns. Commonly used periodic trains were not able to permanently abate seizures at any frequency. A simulated annealing global optimization algorithm was then used to identify an optimal stimulation pattern, which successfully abated 92% of seizures. Finally, in a fully responsive, or closed-loop, neurostimulation paradigm, the optimal stimulation successfully prevented the network from entering the seizure state. We propose that the framework presented here for algorithmically identifying patient-specific neurostimulation patterns can greatly increase the efficacy of neurostimulation devices for seizures.

The study of drug–reaction relationships using global optimization techniques

2007 ◽  
Vol 22 (1) ◽  
pp. 99-126 ◽  
Author(s):  
M. A. Mammadov ◽  
A. M. Rubinov ◽  
J. Yearwood
Keyword(s):  
Global Optimization ◽  
Drug Reaction ◽  
Optimization Techniques
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