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All Journal Indonesian Journal of Electrical Engineering and Computer Science Universitas Muhammadiyah Yogyakarta Undergraduate Conference Proceeding
Selmi, Kaouther
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Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Economics, Econometrics & Finance Education Public Health Social Sciences

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Electrical circuit approaches to modeling brain chaos: insights into neural dynamics Selmi, Kaouther; Bachta, Kods; Bouallegue, Kais
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 3: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i3.pp1503-1511

Abstract

This paper investigates the simulation of brain chaos dynamics using a combination of the Chua circuit and diode tunnel mechanisms, aiming to examine chaotic behavior in brain networks. Leveraging the inherent chaotic properties of the Chua circuit, Fitzhugh-Nagumo (FHN) function and the nonlinear characteristics of diode tunneling, our model offers a platform to mimic the intricate synaptic interactions observed in the brain. By subjecting the model to various stimuli and perturbations, we analyze the emergence and evolution of chaotic patterns, shedding light on the underlying mechanisms of cerebral chaos. Through numerical simulations and experimental validation, we demonstrate the effectiveness of our approach in replicating key features of brain chaos and highlight its potential implications for understanding neurological disorders and cognitive processes. This research contributes to the broader effort of leveraging computational models to explore the complex dynamics of the brain and their implications for neuroscience and microengineering.
Simulating Epileptic Seizure Dynamics: A Perturbed Lorenz Attractor Approach with Bessel Filtering Selmi, Kaouther; Bouallegue , Kais
Proceedings of Universitas Muhammadiyah Yogyakarta Graduate Conference Vol. 4 No. 1 (2024): Renewable Energy, Environment, and Technology for Sustainable Transformation
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/umygrace.v4i1.661

Abstract

In this study, we present a novel approach to model epileptic seizures using a perturbed Lorenz attractor combined with Bessel filtering. The Lorenz attractor, known for its chaotic behavior, is modified by introducing stochastic perturbations to simulate the irregular and complex patterns observed in epileptic EEG signals. By applying a Bessel filter, we enhance the signal’s temporal characteristics, ensuring the preservation of critical information. Our results demonstrate that this methodology effectively captures the chaotic dynamics inherent in epileptic episodes, providing a clearer and more accurate representation of the signal. This approach holds significant potential for improving the diagnosis and understanding of epilepsy, paving the way for advanced treatment strategies.
Co-Authors Bachta, Kods Bouallegue , Kais Bouallegue, Kais