Cargando…
Tutorial: using NEURON for neuromechanical simulations
The dynamical properties of the brain and the dynamics of the body strongly influence one another. Their interaction generates complex adaptive behavior. While a wide variety of simulation tools exist for neural dynamics or biomechanics separately, there are few options for integrated brain-body mod...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10424731/ https://www.ncbi.nlm.nih.gov/pubmed/37583894 http://dx.doi.org/10.3389/fncom.2023.1143323 |
_version_ | 1785089731781984256 |
---|---|
author | Fietkiewicz, Chris McDougal, Robert A. Corrales Marco, David Chiel, Hillel J. Thomas, Peter J. |
author_facet | Fietkiewicz, Chris McDougal, Robert A. Corrales Marco, David Chiel, Hillel J. Thomas, Peter J. |
author_sort | Fietkiewicz, Chris |
collection | PubMed |
description | The dynamical properties of the brain and the dynamics of the body strongly influence one another. Their interaction generates complex adaptive behavior. While a wide variety of simulation tools exist for neural dynamics or biomechanics separately, there are few options for integrated brain-body modeling. Here, we provide a tutorial to demonstrate how the widely-used NEURON simulation platform can support integrated neuromechanical modeling. As a first step toward incorporating biomechanics into a NEURON simulation, we provide a framework for integrating inputs from a “periphery” and outputs to that periphery. In other words, “body” dynamics are driven in part by “brain” variables, such as voltages or firing rates, and “brain” dynamics are influenced by “body” variables through sensory feedback. To couple the “brain” and “body” components, we use NEURON's pointer construct to share information between “brain” and “body” modules. This approach allows separate specification of brain and body dynamics and code reuse. Though simple in concept, the use of pointers can be challenging due to a complicated syntax and several different programming options. In this paper, we present five different computational models, with increasing levels of complexity, to demonstrate the concepts of code modularity using pointers and the integration of neural and biomechanical modeling within NEURON. The models include: (1) a neuromuscular model of calcium dynamics and muscle force, (2) a neuromechanical, closed-loop model of a half-center oscillator coupled to a rudimentary motor system, (3) a closed-loop model of neural control for respiration, (4) a pedagogical model of a non-smooth “brain/body” system, and (5) a closed-loop model of feeding behavior in the sea hare Aplysia californica that incorporates biologically-motivated non-smooth dynamics. This tutorial illustrates how NEURON can be integrated with a broad range of neuromechanical models. CODE AVAILABLE AT: https://github.com/fietkiewicz/PointerBuilder. |
format | Online Article Text |
id | pubmed-10424731 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-104247312023-08-15 Tutorial: using NEURON for neuromechanical simulations Fietkiewicz, Chris McDougal, Robert A. Corrales Marco, David Chiel, Hillel J. Thomas, Peter J. Front Comput Neurosci Neuroscience The dynamical properties of the brain and the dynamics of the body strongly influence one another. Their interaction generates complex adaptive behavior. While a wide variety of simulation tools exist for neural dynamics or biomechanics separately, there are few options for integrated brain-body modeling. Here, we provide a tutorial to demonstrate how the widely-used NEURON simulation platform can support integrated neuromechanical modeling. As a first step toward incorporating biomechanics into a NEURON simulation, we provide a framework for integrating inputs from a “periphery” and outputs to that periphery. In other words, “body” dynamics are driven in part by “brain” variables, such as voltages or firing rates, and “brain” dynamics are influenced by “body” variables through sensory feedback. To couple the “brain” and “body” components, we use NEURON's pointer construct to share information between “brain” and “body” modules. This approach allows separate specification of brain and body dynamics and code reuse. Though simple in concept, the use of pointers can be challenging due to a complicated syntax and several different programming options. In this paper, we present five different computational models, with increasing levels of complexity, to demonstrate the concepts of code modularity using pointers and the integration of neural and biomechanical modeling within NEURON. The models include: (1) a neuromuscular model of calcium dynamics and muscle force, (2) a neuromechanical, closed-loop model of a half-center oscillator coupled to a rudimentary motor system, (3) a closed-loop model of neural control for respiration, (4) a pedagogical model of a non-smooth “brain/body” system, and (5) a closed-loop model of feeding behavior in the sea hare Aplysia californica that incorporates biologically-motivated non-smooth dynamics. This tutorial illustrates how NEURON can be integrated with a broad range of neuromechanical models. CODE AVAILABLE AT: https://github.com/fietkiewicz/PointerBuilder. Frontiers Media S.A. 2023-07-31 /pmc/articles/PMC10424731/ /pubmed/37583894 http://dx.doi.org/10.3389/fncom.2023.1143323 Text en Copyright © 2023 Fietkiewicz, McDougal, Corrales Marco, Chiel and Thomas. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Fietkiewicz, Chris McDougal, Robert A. Corrales Marco, David Chiel, Hillel J. Thomas, Peter J. Tutorial: using NEURON for neuromechanical simulations |
title | Tutorial: using NEURON for neuromechanical simulations |
title_full | Tutorial: using NEURON for neuromechanical simulations |
title_fullStr | Tutorial: using NEURON for neuromechanical simulations |
title_full_unstemmed | Tutorial: using NEURON for neuromechanical simulations |
title_short | Tutorial: using NEURON for neuromechanical simulations |
title_sort | tutorial: using neuron for neuromechanical simulations |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10424731/ https://www.ncbi.nlm.nih.gov/pubmed/37583894 http://dx.doi.org/10.3389/fncom.2023.1143323 |
work_keys_str_mv | AT fietkiewiczchris tutorialusingneuronforneuromechanicalsimulations AT mcdougalroberta tutorialusingneuronforneuromechanicalsimulations AT corralesmarcodavid tutorialusingneuronforneuromechanicalsimulations AT chielhillelj tutorialusingneuronforneuromechanicalsimulations AT thomaspeterj tutorialusingneuronforneuromechanicalsimulations |