ArticlePLoS computational biology2023
An electrophysiological and kinematic model of Paramecium, the "swimming neuron".
Article in PLoS computational biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Geometrical preference of anchoring sites in the unicellular organismProceedings of the National Academy of Sciences of the United States of America · 2026Article
- Cell motility: Bioelectrical control of behavior without neurons.Current biology : CB · 2024Article
- Methods and Measures for Investigating Microscale Motility.Integrative and comparative biology · 2023Review
- Perspectives on Principles of Cellular Behavior from the Biophysics of Protists.Integrative and comparative biology · 2023Review
- Active oscillations in microscale navigation.Animal cognition · 2023Review
- Interaction of the mechanosensitive microswimmerRoyal Society open science · 2023Article
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Authors and funding
6 authors.
Funding
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Abstract
Paramecium is a large unicellular organism that swims in fresh water using cilia. When stimulated by various means (mechanically, chemically, optically, thermally), it often swims backward then turns and swims forward again in a new direction: this is called the avoiding reaction. This reaction is triggered by a calcium-based action potential. For this reason, several authors have called Paramecium the "swimming neuron". Here we present an empirically constrained model of its action potential based on electrophysiology experiments on live immobilized paramecia, together with simultaneous measurement of ciliary beating using particle image velocimetry. Using these measurements and additional behavioral measurements of free swimming, we extend the electrophysiological model by coupling calcium concentration to kinematic parameters, turning it into a swimming model. In this way, we obtain a model of autonomously behaving Paramecium. Finally, we demonstrate how the modeled organism interacts with an environment, can follow gradients and display collective behavior. This work provides a modeling basis for investigating the physiological basis of autonomous behavior of Paramecium in ecological environments.
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