Vol. 5 No. 1 (2025): Issue 5
Articles

Neural Circuits Modeling using Efficient Genetic Algorithm

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  • Elin Svensson,
  • Lars Johansson,
  • Freja Eriksson
Elin Svensson
Department of Computational Neuroscience, Örebro University, Örebro, Sweden
Lars Johansson
Institute for Neuroinformatics, Mid Sweden University, Sundsvall, Sweden
Freja Eriksson
Center for Neural Research and Modeling, Karlstad University, Karlstad, Sweden
DOI: https://doi.org/10.71070/jcbm.v5i1.92

Published 2025-01-26

Keywords

  • Neural Circuit Modeling,
  • Model Parameter Optimization,
  • Genetic Algorithm,
  • Parameter Space Exploration,
  • Simulation Accuracy

How to Cite

Svensson, E., Johansson, L., & Eriksson, F. (2025). Neural Circuits Modeling using Efficient Genetic Algorithm. Journal of Computational Biology and Medicine, 5(1). https://doi.org/10.71070/jcbm.v5i1.92

Abstract

 Neural circuit modeling is essential for understanding brain functions, but current research faces challenges in efficiently optimizing model parameters. This paper highlights the necessity of developing novel approaches to improve the accuracy and efficiency of neural circuit modeling. Presently, researchers encounter difficulties in effectively exploring the vast parameter space and optimizing complex neural network models. To address these challenges, this study proposes an innovative approach utilizing an efficient genetic algorithm for neural circuit modeling. Our work focuses on optimizing model parameters and enhancing the accuracy of neural circuit simulations. This research contributes to advancing the field of neural circuit modeling by offering a more effective and robust methodology for exploring and optimizing complex neural networks.

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