Flag Counter
AKILLI SİSTEMLER VE UYGULAMALARI DERGİSİ
JOURNAL OF INTELLIGENT SYSTEMS WITH APPLICATIONS
J. Intell. Syst. Appl.
E-ISSN: 2667-6893
Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License.

pyNeuroSim: Python-Based Neuron Simulator

pyNeuroSim: Python-Based Neuron Simulatörü

How to cite: Şen , İşler Y. Pyneurosim: python-based neuron simulator. Akıllı Sistemler ve Uygulamaları Dergisi (Journal of Intelligent Systems with Applications) 2022; 5(2): 110-113. DOI: 10.54856/jiswa.202212225

Full Text: PDF, in Turkish.

Total number of downloads: 142

Title: pyNeuroSim: Python-Based Neuron Simulator

Abstract: The action potential of the neuron membrane corresponds to the biophysiological process of communication among neurons that make up the nervous system. It involves the transmission of information received from other neighboring cells and the external environment. Mathematical models have been developed to observe the formation and transmission of the action potential by tracking changes in the neuron membrane potential. One widely used mathematical model in neuroscience is the Hodgkin-Huxley Neuron Model. Programs have been created to simulate neural transmission using these mathematical models. The main purpose of this study is to develop a user-friendly computational program that provides an accessible and simple interface to understand the Hodgkin-Huxley neuron model computation with the forward Euler method. The program's structure allows users to modify the parameters that affect their membrane potential.

Keywords: Nöron modeli; aksiyon potansiyeli; simülator; Python


Başlık: pyNeuroSim: Python-Based Neuron Simulatörü

Özet: Sinir sistemini oluşturan nöronların; birbirleri ile iletişimi, diğer komşu hücreler ve dış çevreden aldıkları bilgilerin aktarılmasının biyofizyolojik sürecine nöron membranın aksiyon potansiyeli karşılık gelir. Nöron membran potansiyelindeki değişimi dolasıyla aksiyon potansiyelinin oluşması ve iletimini gözlemlemeye olanak sağlayan matematiksel modeller geliştirilmiştir. Bu çalışmada, matematiksel modellerden birisi olan ve sinirbilim alanında oldukça yaygın olarak kullanılan Hodgkin-Huxley nöron modeli kullanılmıştır. Nöronal iletimini inceleyebilmek adına bu geliştirilen matematiksel modelleri kullanarak simüle eden programlar oluşturulmuştur. Bu çalışmanın temel amacı erişilebilir, basit arayüzlü ve kolay anlaşılabilir bir eğitim programı sunmaktır. Bu amaç doğrultusunda Hodgkin-Huxley nöron modelinin ileri Euler yöntemi ile hesaplaması Python ortamına aktarılmış ve gerçekleştirilen programda kullanıcının membran potansiyeli üzerinde etki eden parametreleri değiştirmeye imkân tanıyan yapılar oluşturulmuştur.

Anahtar kelimeler: Neuron model; action potential; simulator; Python


Bibliography:
  • Sousa AMM, Meyer KA, Santpere G, Gulden FO, Sestan N. Evolution of the human nervous system function, structure, and development. Cell 2017; 170(2): 226–247.
  • Cohen LB. Changes in neuron structure during action potential propagation and synaptic transmission. Physiological Reviews 1973; 53(2): 373-418.
  • Cole KS. The advance of electrical models for cells and axons: "Arma virumque cano". Biophysical Journal 1962; 2(2): 101-119.
  • Hodgkin AL, Huxley AF. Currents carried by sodium and potassium ions through the membrane of the giant axon of Loligo. The Journal of Physiology 1952; 116(4): 449-472.
  • Catterall WA, Raman IM, Robinson HPC, Sejnowski TJ, PaulsenO. The Hodgkin-Huxley heritage: From channels to circuits. Journal of Neuroscience 2012; 32(41): 14064-14073.
  • Nelson M, Rinzel J. The Hodgkin—Huxley Model. Book chapter in The Book of GENESIS. 1988, Springer, New York, NY.
  • Bower JM, Cornelis H, Beeman D. GENESIS: The GEneral NEural SImulation System. Book chapter in Encyclopedia of Computational Neuroscience. 2013, Springer, New York, NY.
  • De Schutter E. Computer software for development and simulation of compartmental models of neurons. Computers in Biology and Medicine 1989; 19(2): 71-81.
  • Goodman D, Brette R. Brian: A simulator for spiking neural networks in Python. Frontiers in Neuroinformatics 2008; 2(1).
  • Ozer M, Isler Y, Ozer H. A computer software for simulating single-compartmental model of neurons. Computer Methods and Programs in Biomedicine 2004; 75(1): 51–57.
  • Isler Y. A software for simulating steady-state properties of passive dendrites based on the cable theory. Computer Methods and Programs in Biomedicine 2007; 88(3): 264–272.
  • McDougal RA, Hines ML, Lytton WW, Jedrzejewski-Szmek Z. Reaction-diffusion in the NEURON simulator. Frontiers in Neuroinformatics 2013; 7.
  • Migliore M, Cannia C, Lytton WW, Markram H, Hines ML. Parallel network simulations with NEURON. Journal of Computational Neuroscience 2006; 21(2): 119–129.
  • Plesser HE, Diesmann M, Gewaltig M-O, Morrison A. NEST: An Environment for Neural Systems Simulations. Book chapter in Encyclopedia of Computational Neuroscience. 2002; 1849–1852, Springer Link.
  • Hodgkin AL, Huxley AF. A quantitative description of membrane current and its application to conduction and excitation in nerve. The Journal of Physiology 1952; 117(4): 500–544.
  • Podrzaj P. A brief demonstration of some Python GUI libraries. In The 8th International Conference on Informatics and Applications (ICIA2019), Takamatsu: The Society of Digital Information and Wireless Communications (SDIWC), Aug. 2019.