Neurosimilator for Undergraduate Biophysics and Neurophysiology Courses

Stringent animal welfare principles are forcing undergraduate instructors to avoid the use of animals. Therefore, many hands-on lab sessions using laboratory animals are progressively replaced by computer simulations. These versatile software simulations permit the observation of the behavior of biological systems under a great variety of experimental conditions. While this versatility is important, computer simulations often work even when a student makes wrong assumptions, a situation that poses its own pedagogical problem. Hands-on learning provides pupils with the opportunity to safely make mistakes and learn organically through trial and error and should therefore still be promoted. We propose an electronic model of an excitable cell composed of different modules representing different parts of a neuron - dendrites, soma, axon and node of Ranvier. We describe a series of experiments that allow students to better understand differences between passive and active cell responses and differences between myelinated and demyelinated axons. These circuits can also be used to demonstrate temporal and spatial summation of signals coming to the neuron via dendrites, as well as the neuron coding by firing frequency. Finally, they permit experimental determination along with theoretical calculations of important biophysical properties of excitable cells, such as rheobase, chronaxie and space constant. This open-source model has been successfully integrated into an undergraduate course of the physiology of excitable cells and student feedback assessment reveals that it helped students to understand important notions of the course. Thus, this neuromorphic circuit could be a valuable tool for biophysics and neuroscience courses in other universities.

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Publication Details

Journal
Journal of Undergraduate Neuroscience Education
Published
2024-08-31
DOI
https://doi.org/10.59390/miuv3158
Citations
2
Primary Topic
Neuroscience and Neural Engineering
Type
article
Field-Weighted Citation Impact
0.54
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article

Neurosimilator for Undergraduate Biophysics and Neurophysiology Courses

Freddy Dupuis, Vadim Shlyonsky, David Gall, Bertrand de Prelle
2 citations
Journal of Undergraduate Neuroscience Education
Neuroscience and Neural Engineering
0.54
article

Neurosimilator for Undergraduate Biophysics and Neurophysiology Courses

Freddy Dupuis, Vadim Shlyonsky, David Gall, Bertrand de Prelle
article en
2 citations

Abstract

Stringent animal welfare principles are forcing undergraduate instructors to avoid the use of animals. Therefore, many hands-on lab sessions using laboratory animals are progressively replaced by computer simulations. These versatile software simulations permit the observation of the behavior of biological systems under a great variety of experimental conditions. While this versatility is important, computer simulations often work even when a student makes wrong assumptions, a situation that poses its own pedagogical problem. Hands-on learning provides pupils with the opportunity to safely make mistakes and learn organically through trial and error and should therefore still be promoted. We propose an electronic model of an excitable cell composed of different modules representing different parts of a neuron - dendrites, soma, axon and node of Ranvier. We describe a series of experiments that allow students to better understand differences between passive and active cell responses and differences between myelinated and demyelinated axons. These circuits can also be used to demonstrate temporal and spatial summation of signals coming to the neuron via dendrites, as well as the neuron coding by firing frequency. Finally, they permit experimental determination along with theoretical calculations of important biophysical properties of excitable cells, such as rheobase, chronaxie and space constant. This open-source model has been successfully integrated into an undergraduate course of the physiology of excitable cells and student feedback assessment reveals that it helped students to understand important notions of the course. Thus, this neuromorphic circuit could be a valuable tool for biophysics and neuroscience courses in other universities.

Journal of Undergraduate Neuroscience EducationVol. 22(3)
Université Libre de Bruxelles (BE)
Openalex Percentile: Top 36%
Neuroscience and Neural Engineering
0.54
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