Abstract

The subject of bioelectricity is for many life science students the first encounter with biophysics. The transfer of knowledge on electricity from the context of physics to the context of physiology is not without difficulty. Use of computer simulations is expected to enhance the students’ understanding and interest, and to promote critical and integrative thinking. This paper discusses models, simulations, and activities designed for life science students that help them come to grips with biophysical processes underlying action potentials of a single neuron through ‘virtual labs’. Key models and computer simulations are presented, including their use in exploring phenomena such as firing threshold, spike train and refractory period. Experiences and opinions of biomedical students regarding the virtual labs have been collected and are discussed in this paper.

Highlights

  • Physics becomes more and more important in other disciplines, such as life sciences

  • The subject of bioelectricity is for many life science students the first encounter with biophysics

  • This paper discusses models, simulations, and activities designed for life science students that help them come to grips with biophysical processes underlying action potentials of a single neuron through ‘virtual labs’

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Summary

Introduction

Electrical concepts are needed to describe and explain electrophysiological processes in the human body. The life science textbooks and supplemental materials contain a lot of pictures and animations of the processes taking place, many students have difficulties in understanding the analogy between electric circuits and neural models; grasping all of the required physics concepts; realizing how the physics-based models help them mastering the fundamentals of neurophysiology. One reason might be that prior physics courses focussed on other contexts, irrelevant for life sciences. Another plausible reason is that a textbook with accompanying lectures alone is insufficient to mediate transfer from physics to life science. Authors [2,3,4,5,6] propose simulating neural computer models

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