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Tutorial: Using NEURON for Neuromechanical Simulations (Fietkiewicz et al., 2023)
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<p class=MsoNormal style='margin-bottom:12.0pt;background:white'><b><span
style='font-size:24.0pt;font-family:"Segoe UI",sans-serif;color:#1F2328'>Introduction</span></b></p>
<p class=MsoNormal style='margin-bottom:12.0pt;background:white'><span
style='font-family:"Segoe UI",sans-serif;color:#1F2328'>This repository
contains models and tools discussed in the following paper:</span></p>
<p class=MsoNormal style='margin-bottom:12.0pt;background:white'><span
style='font-family:"Segoe UI",sans-serif;color:#1F2328'>Fietkiewicz, C.,
Corrales Marco, D., Chiel, H. J. and Thomas, P. J. (2023). Tutorial: Using
NEURON for Neuromechanical Simulations. <i>Frontiers in Computational
Neuroscience</i> 17: 1143323. [<a
href="https://www.frontiersin.org/articles/10.3389/fncom.2023.1143323/"><span
style='text-decoration:none'>Link</span></a>]</span></p>
<p class=MsoNormal style='margin-bottom:12.0pt;background:white'><span
style='font-family:"Segoe UI",sans-serif;color:#1F2328'>All models
require <a href="https://nrn.readthedocs.io"><span
style='text-decoration:none'>NEURON</span></a> to be installed, and Python
versions require <a href="https://python.org/"><span style='text-decoration:
none'>Python</span></a>.</span></p>
<p class=MsoNormal style='margin-bottom:12.0pt;background:white'><span
style='font-family:"Segoe UI",sans-serif;color:#1F2328'>Address questions and
comments to Dr. Chris Fietkiewicz (<a href="mailto:fietkiewicz@hws.edu"><span
style='text-decoration:none'>fietkiewicz@hws.edu</span></a>). The following
sections are available:</span></p>
<p class=MsoNormal style='margin-top:.25in;margin-right:0in;margin-bottom:12.0pt;
margin-left:0in;background:white'><b><span style='font-size:24.0pt;font-family:
"Segoe UI",sans-serif;color:#1F2328'>Models</span></b></p>
<p class=MsoNormal style='margin-bottom:12.0pt;background:white'><span
style='font-family:"Segoe UI",sans-serif;color:#1F2328'>This collection of
NEURON models demonstrates various concepts for neuromechanical simulations
using pointers, as detailed in the paper above (Fietkiewicz et al.).</span></p>
<p class=MsoNormal style='margin-bottom:12.0pt;background:white'><span
style='font-family:"Segoe UI",sans-serif;color:#1F2328'>Each model is
independent of the others, with all necessary files in a single directory. Most
models have both a hoc version and a Python version, each in a separate
directory. The following steps can be used to run each of the models and
produce the output shown in the paper cited above:</span></p>
<ol style='margin-top:0in' start=1 type=1>
<li class=MsoNormal style='color:#1F2328;margin-top:12.0pt;margin-bottom:12.0pt;
background:white'><span style='font-family:"Segoe UI",sans-serif'>Compile
the .mod files in the selected directory.</span></li>
<li class=MsoNormal style='color:#1F2328;margin-top:12.0pt;margin-bottom:12.0pt;
background:white'><span style='font-family:"Segoe UI",sans-serif'>For most
models, run either run.hoc or run.py, depending on the version you are
working with. For “5-AplysiaLoop”, the hoc version has two different .hoc
files, each of which uses a different setting for the parameter “mu” (see
the paper for details).</span></li>
<li class=MsoNormal style='color:#1F2328;margin-top:12.0pt;margin-bottom:12.0pt;
background:white'><span style='font-family:"Segoe UI",sans-serif'>For hoc
versions, click Init & Run from Run Control GUI. Most Python versions
run the simulation automatically. For “5-AplysiaLoop”, however, the Python
version provides a single GUI where certain parameters may be set and the
user must click the Init & Run button.</span></li>
</ol>
<p class=MsoNormal style='margin-bottom:12.0pt;background:white'><span
style='font-family:"Segoe UI",sans-serif;color:#1F2328'>The following models
are available:</span></p>
<p class=MsoNormal style='margin-top:.25in;margin-right:0in;margin-bottom:12.0pt;
margin-left:0in;background:white'><b><span style='font-size:18.0pt;font-family:
"Segoe UI",sans-serif;color:#1F2328'>1-Neuromuscular</span></b></p>
<p class=MsoNormal style='margin-bottom:12.0pt;background:white'><b><span
style='font-family:"Segoe UI",sans-serif;color:#1F2328'>Neuromuscular</span></b><span
style='font-family:"Segoe UI",sans-serif;color:#1F2328'> is adapted from a
neuromuscular model from Kim, Hojeong. "Muscle length-dependent
contribution of motoneuron Cav1. 3 channels to force production in model slow
motor unit." <i>Journal of Applied Physiology</i> 123.1 (2017):
88-105., Kim, Hojeong. "Linking motoneuron PIC location to motor function
in closed-loop motor unit system including afferent feedback: a computational
investigation." <i>Eneuro</i> 7.2 (2020)., and Kim, Hojeong, and
Charles J. Heckman. "A dynamic calcium-force relationship model for sag
behavior in fast skeletal muscle." <i>PLOS Computational Biology</i> 19.6
(2023): e1011178.</span></p>
<p class=MsoNormal style='margin-top:.25in;margin-right:0in;margin-bottom:12.0pt;
margin-left:0in;background:white'><b><span style='font-size:18.0pt;font-family:
"Segoe UI",sans-serif;color:#1F2328'>2-OscillatorLoop</span></b></p>
<p class=MsoNormal style='margin-bottom:12.0pt;background:white'><b><span
style='font-family:"Segoe UI",sans-serif;color:#1F2328'>OscillatorLoop</span></b><span
style='font-family:"Segoe UI",sans-serif;color:#1F2328'> is adapted from a
closed-loop motor control model from Yu, Zhuojun, and Peter J. Thomas.
"Dynamical consequences of sensory feedback in a half-center oscillator
coupled to a simple motor system." <i>Biological Cbernetics</i> 115.2
(2021): 135-160.</span></p>
<p class=MsoNormal style='margin-top:.25in;margin-right:0in;margin-bottom:12.0pt;
margin-left:0in;background:white'><b><span style='font-size:18.0pt;font-family:
"Segoe UI",sans-serif;color:#1F2328'>3-RespirationLoop</span></b></p>
<p class=MsoNormal style='margin-bottom:12.0pt;background:white'><b><span
style='font-family:"Segoe UI",sans-serif;color:#1F2328'>RespirationLoop</span></b><span
style='font-family:"Segoe UI",sans-serif;color:#1F2328'> is adapted from a
closed-loop respiratory model from Diekman, Casey O., Peter J. Thomas, and
Christopher G. Wilson. "Eupnea, tachypnea, and autoresuscitation in a
closed-loop respiratory control model." <i>Journal of Neurophysiology</i> 118.4
(2017): 2194-2215.</span></p>
<p class=MsoNormal style='margin-top:.25in;margin-right:0in;margin-bottom:12.0pt;
margin-left:0in;background:white'><b><span style='font-size:18.0pt;font-family:
"Segoe UI",sans-serif;color:#1F2328'>4-NonsmoothOscillator</span></b></p>
<p class=MsoNormal style='margin-bottom:12.0pt;background:white'><b><span
style='font-family:"Segoe UI",sans-serif;color:#1F2328'>NonsmoothOscillator</span></b><span
style='font-family:"Segoe UI",sans-serif;color:#1F2328'> is a simple (1D)
non-smooth forced oscillator model.</span></p>
<p class=MsoNormal style='margin-top:.25in;margin-right:0in;margin-bottom:12.0pt;
margin-left:0in;background:white'><b><span style='font-size:18.0pt;font-family:
"Segoe UI",sans-serif;color:#1F2328'>5-AplysiaLoop</span></b></p>
<p class=MsoNormal style='margin-bottom:12.0pt;background:white'><b><span
style='font-family:"Segoe UI",sans-serif;color:#1F2328'>AplysiaLoop</span></b><span
style='font-family:"Segoe UI",sans-serif;color:#1F2328'> is adapted from a
closed-loop model of the feeding motor system in Aplysia californica from Shaw,
Kendrick M., David N. Lyttle, Jeffrey P. Gill, Miranda J. Cullins, Jeffrey M.
McManus, Hui Lu, Peter J. Thomas, and Hillel J. Chiel. "The significance
of dynamical architecture for adaptive responses to mechanical loads during
rhythmic behavior." <i>Journal of Computational Neuroscience</i> 38
(2015): 25-51., Lyttle, David N., Jeffrey P. Gill, Kendrick M. Shaw, Peter J.
Thomas, and Hillel J. Chiel. "Robustness, flexibility, and sensitivity in
a multifunctional motor control model." <i>Biological Cybernetics</i> 111
(2017): 25-47., and Wang, Y., Gill, J. P., Chiel, H. J., & Thomas, P. J.
(2022). Variational and phase response analysis for limit cycles with hard
boundaries, with applications to neuromechanical control problems. <i>Biological
Cybernetics</i>, 1-24.</span></p>
<p class=MsoNormal style='margin-top:.25in;margin-right:0in;margin-bottom:12.0pt;
margin-left:0in;background:white'><b><span style='font-size:18.0pt;font-family:
"Segoe UI",sans-serif;color:#1F2328'>6-LotkaVolterra</span></b></p>
<p class=MsoNormal style='margin-bottom:12.0pt;background:white'><b><span
style='font-family:"Segoe UI",sans-serif;color:#1F2328'>LotkaVolterra</span></b><span
style='font-family:"Segoe UI",sans-serif;color:#1F2328'> is based on the
classic Lotka-Volterra two-population predator-prey model <a
href="https://en.wikipedia.org/wiki/Lotka%E2%80%93Volterra_equations"><span
style='text-decoration:none'>(https://en.wikipedia.org/wiki/Lotka-Volterra_equations)</span></a>.</span></p>
<p class=MsoNormal style='margin-top:.25in;margin-right:0in;margin-bottom:12.0pt;
margin-left:0in;background:white'><b><span style='font-size:24.0pt;font-family:
"Segoe UI",sans-serif;color:#1F2328'>PointerBuilder apps</span></b></p>
<p class=MsoNormal style='margin-bottom:12.0pt;background:white'><span
style='font-family:"Segoe UI",sans-serif;color:#1F2328'>These applications are
graphical interfaces for working with NEURON pointers. They can be used to
learn and verify pointer syntax.</span></p>
<ul style='margin-top:0in' type=disc>
<li class=MsoNormal style='color:#1F2328;margin-top:12.0pt;margin-bottom:12.0pt;
background:white'><b><span style='font-family:"Segoe UI",sans-serif'>NEURON:</span></b><span
style='font-family:"Segoe UI",sans-serif'> This graphical interface,
written entirely in NEURON, creates pointer instructions in hoc syntax.</span></li>
<li class=MsoNormal style='color:#1F2328;margin-top:12.0pt;margin-bottom:12.0pt;
background:white'><b><span style='font-family:"Segoe UI",sans-serif'>Python:</span></b><span
style='font-family:"Segoe UI",sans-serif'> This graphical interface,
written entirely in Python, creates pointer instructions in Python syntax.
It requires the Tkinter package, which is common to most Python
installations.</span></li>
</ul>
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Tutorial: Using NEURON for Neuromechanical Simulations (Fietkiewicz et al., 2023)