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<span id="openzim-page-title" class="mw-page-title-main"><span class="mw-page-title-main">Neuron (software)</span></span>
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</style><table class="infobox vevent"><tbody><tr><th colspan="2" class="infobox-above summary">Neuron</th></tr><tr><th scope="row" class="infobox-label" style="white-space: nowrap;"><a href="Programmer" title="Programmer">Developer(s)</a></th><td class="infobox-data">Michael Hines, <a href="John_Wilson_Moore" title="John Wilson Moore">John W. Moore</a>, and Ted Carnevale</td></tr><tr style="display: none;"><td colspan="2" class="infobox-full-data"></td></tr><tr><th scope="row" class="infobox-label" style="white-space: nowrap;"><a href="Software_release_life_cycle" title="Software release life cycle">Stable release</a></th><td class="infobox-data"><div style="margin:0px;">8.2.0
/ July 1, 2022<span style="display:none"> (<span class="bday dtstart published updated">2022-07-01</span>)</span><sup id="cite_ref-releases_1-0" class="reference"><a href="#cite_note-releases-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup></div></td></tr><tr><th scope="row" class="infobox-label" style="white-space: nowrap;"><a href="Software_release_life_cycle#Beta" title="Software release life cycle">Preview release</a></th><td class="infobox-data"><div style="margin:0px;">8.2a
/ June 7, 2022<span style="display:none"> (<span class="bday dtstart published updated">2022-06-07</span>)</span><sup id="cite_ref-releases_1-1" class="reference"><a href="#cite_note-releases-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup></div></td></tr><tr style="display:none"><td colspan="2">
</td></tr><tr><th scope="row" class="infobox-label" style="white-space: nowrap;"><a href="Repository_(version_control)" title="Repository (version control)">Repository</a></th><td class="infobox-data"><style data-mw-deduplicate="TemplateStyles:r1126788409">
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</style><div class="plainlist"><ul><li><span class="url"><a rel="nofollow" class="external text" href="https://github.com/neuronsimulator/nrn">github<wbr>.com<wbr>/neuronsimulator<wbr>/nrn</a></span> </li></ul>
</div></td></tr><tr><th scope="row" class="infobox-label" style="white-space: nowrap;">Written in</th><td class="infobox-data"><a href="C_(programming_language)" title="C (programming language)">C</a>, <a href="C%2B%2B" title="C++">C++</a>, <a href="FORTRAN" class="mw-redirect" title="FORTRAN">FORTRAN</a></td></tr><tr><th scope="row" class="infobox-label" style="white-space: nowrap;"><a href="Operating_system" title="Operating system">Operating system</a></th><td class="infobox-data"><a href="Cross-platform" class="mw-redirect" title="Cross-platform">Cross-platform</a></td></tr><tr><th scope="row" class="infobox-label" style="white-space: nowrap;"><a href="Software_categories#Categorization_approaches" title="Software categories">Type</a></th><td class="infobox-data">Neuron Simulation</td></tr><tr><th scope="row" class="infobox-label" style="white-space: nowrap;"><a href="Software_license" title="Software license">License</a></th><td class="infobox-data"><a href="BSD-new" class="mw-redirect" title="BSD-new">New BSD License</a></td></tr><tr><th scope="row" class="infobox-label" style="white-space: nowrap;">Website</th><td class="infobox-data"><a rel="nofollow" class="external free" href="https://neuron.yale.edu">https://neuron.yale.edu</a></td></tr></tbody></table>
<p><b>Neuron</b> is a simulation environment for modeling individual and networks of <a href="Neurons" class="mw-redirect" title="Neurons">neurons</a>. It was primarily developed by Michael Hines, <a href="John_Wilson_Moore" title="John Wilson Moore">John W. Moore</a>, and Ted Carnevale at <a href="Yale" class="mw-redirect" title="Yale">Yale</a> and <a href="Duke_University" title="Duke University">Duke</a>.
</p><p>Neuron models individual neurons via the use of sections that are automatically subdivided into individual compartments, instead of requiring the user to manually create compartments. The primary scripting language is <a href="Hoc_(programming_language)" title="Hoc (programming language)">hoc</a> but a <a href="Python_(programming_language)" title="Python (programming language)">Python</a> interface is also available. Programs can be written interactively in a shell, or loaded from a file. Neuron supports parallelization via the <a href="Message_Passing_Interface" title="Message Passing Interface">MPI</a> protocol.
</p><p>Neuron is capable of handling diffusion-reaction models, and integrating diffusion functions into models of synapses and cellular networks.<sup id="cite_ref-2" class="reference"><a href="#cite_note-2"><span class="cite-bracket">[</span>2<span class="cite-bracket">]</span></a></sup> Parallelization is possible via internal multithreaded routines, for use on multi-core computers.<sup id="cite_ref-3" class="reference"><a href="#cite_note-3"><span class="cite-bracket">[</span>3<span class="cite-bracket">]</span></a></sup> The properties of the membrane channels of the neuron are simulated using compiled mechanisms written using the NMODL language or by compiled routines operating on internal data structures that are set up with Channel Builder.
</p><p>Along with the analogous software platform <a href="GENESIS_(software)" title="GENESIS (software)">GENESIS</a>, Neuron is the basis for instruction in <a href="Computational_neuroscience" title="Computational neuroscience">computational neuroscience</a> in many courses and laboratories around the world.
</p>
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<div class="mw-heading mw-heading2"><h2 id="User_interface">User interface</h2></div>
<p>Neuron features a <a href="Graphical_user_interface" title="Graphical user interface">graphical user interface</a> (GUI), for use by individuals with minimal programming experience. The GUI comes equipped with a builder for single and multiple compartment cells, networks, network cells, channels and linear electric circuits. Single and multiple compartment cells differ in that multiple compartment cells features several "sections", each with potentially distinct parameters for dimensions and kinetics. Tutorials are available on the Neuron website, including for getting basic models out of the cell, channel and network builders. With these builders, the user can form the basis of all simulations and models.
</p>
<div class="mw-heading mw-heading3"><h3 id="Cell_Builder">Cell Builder</h3></div>
<p>Cell Builder allows the user to generate and modify stick figure cell structures. These sections form the basis of functionally distinct areas of the neuron.<sup id="cite_ref-4" class="reference"><a href="#cite_note-4"><span class="cite-bracket">[</span>4<span class="cite-bracket">]</span></a></sup>
</p><p>The user can define functionally distinct groups of sections. Sections branching from one another can be labeled "dendrites," while another, single section that projects from the same central one can be labeled as the "axon." The user can define parameters along which certain values are variable as a function across a section. For instance, path length along a subset can be defined as a domain, the functions along which can then be defined later.<sup id="cite_ref-5" class="reference"><a href="#cite_note-5"><span class="cite-bracket">[</span>5<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-6" class="reference"><a href="#cite_note-6"><span class="cite-bracket">[</span>6<span class="cite-bracket">]</span></a></sup>
</p><p>The user can select either individual sections, or groups and set precise parameters for length, diameter, area and length for that group or section. Any of these values can be set as a function of length or some other parameter of the corresponding section. The user can set the number of functional segments in a section, which is a strategy for spatial resolution. The higher the number of segments, the more precisely Neuron can handle a function in a section. Segments are the points where point process managers can be associated.<sup id="cite_ref-7" class="reference"><a href="#cite_note-7"><span class="cite-bracket">[</span>7<span class="cite-bracket">]</span></a></sup>
</p><p>Users can define kinetic and electro-physiological functions across both subsets and sections. Neuron comes equipped with a probabilistic model of <a href="Hodgkin-Huxley_Model" class="mw-redirect" title="Hodgkin-Huxley Model">Hodgkin-Huxley Model</a><sup id="cite_ref-8" class="reference"><a href="#cite_note-8"><span class="cite-bracket">[</span>8<span class="cite-bracket">]</span></a></sup> giant squid axon kinetics, as well as a function to model passive <a href="Leak_channel" class="mw-redirect" title="Leak channel">leak channel</a> kinetics. Both of these functions, and the features they describe, can be added to the membrane of the constructed cell. Values for leak rate, sodium conductance and potassium conductance can be set for modeling these kinetics can be set as functions over a parameterized domain. Channels become available for implementation in a cell membrane.
</p>
<div class="mw-heading mw-heading3"><h3 id="Channel_Builder">Channel Builder</h3></div>
<p>The user can generate both <a href="Voltage-gated_ion_channel" title="Voltage-gated ion channel">voltage</a>- and <a href="Ligand-gated_ion_channel" title="Ligand-gated ion channel">ligand-gated channel</a> models. Channel Builder supports local point channels, generally used for single, large channels whose function is to be modeled, and general channels whose density across the cell can be defined. Maximum conductance, reversal potential, ligand sensitivity, ion permeability, as well as precise dynamics of transitional states using activation and inactivation variables, and including differential conductance, can be defined.<sup id="cite_ref-9" class="reference"><a href="#cite_note-9"><span class="cite-bracket">[</span>9<span class="cite-bracket">]</span></a></sup>
</p>
<div class="mw-heading mw-heading3"><h3 id="Network_and_Network_Cell_Builder">Network and Network Cell Builder</h3></div>
<p>Neuron allows for the generation of mixed models, populated with both artificial cells and neurons. Artificial cells essentially function as point processes, implemented into the network. Artificial cells require only a point process, with defined parameters. The user can create the structure and dynamics of network cells. The user can create synapses, using simulated synapse point processes as archetypes. Parameters on these point processes can be manipulated to simulate both inhibitory and excitatory responses. Synapses can be placed on specific segments of the constructed cell, wherein, again, they will behave as point processes, except that they are sensitive to the activity of a pre-synaptic element. Cells can be managed. The user creates the basic grid of network cells, taking previously completed network cells as archetypes. Connections can be defined between source cells and target synapses on other cells. The cell containing the target synapse becomes the post-synaptic element, whereas the source cells function as pre-synaptic elements. Weights can be added to define strength of activation of a synapse by the pre-synaptic cell. A plot option can be activated to open a graph of spikes across time for individual neurons.
</p>
<div class="mw-heading mw-heading3"><h3 id="Simulation_and_recording">Simulation and recording</h3></div>
<p>Neuron comes equipped with a slew of simulation tools. Most notably, it includes several "point processes," which are simple functions at a particular segment of a cell. Point processes include simulations of <a href="Voltage_clamp" title="Voltage clamp">voltage</a>, <a href="Patch_clamp" title="Patch clamp">patch</a>, <a href="Voltage_clamp#Single-electrode_voltage_clamp" title="Voltage clamp">single electrode</a> and <a href="Current_clamp" title="Current clamp">current</a> clamps, as well as several simulated synapses. Synapse point processes are distinct for their ability to model stimulation intensities that vary non-linearly across time. These can be placed on any segment of any section of a built cell, individual or network, and their precise values, including amplitude and duration of stimulation, delay time of activation in a run and time decay parameters (for synapses), can be defined from the point process manager module. When implemented into a network as synapses, point process parameters are defined in the synapse builder for a particular network cell.<sup id="cite_ref-10" class="reference"><a href="#cite_note-10"><span class="cite-bracket">[</span>10<span class="cite-bracket">]</span></a></sup> Graphs describing voltage, conductance, and current axes over time can be used to describe changes in electrical state at the location of any segment on the cell. Neuron allows for graphs of change at both individual points over time, and across an entire section through time.<sup id="cite_ref-11" class="reference"><a href="#cite_note-11"><span class="cite-bracket">[</span>11<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-12" class="reference"><a href="#cite_note-12"><span class="cite-bracket">[</span>12<span class="cite-bracket">]</span></a></sup> Duration of run can be set. All point processes, including those standing for cells or synapses of artificial neurons, and all graphs reflect the duration.
</p>
<div class="mw-heading mw-heading2"><h2 id="Examples">Examples</h2></div>
<p>This example creates a simple cell, with a single compartment <a href="Soma_(biology)" title="Soma (biology)">soma</a> and a multi compartment <a href="Axon" title="Axon">axon</a>. It has the dynamics of the cell membrane simulated using <a href="Squid_giant_axon" title="Squid giant axon">Hodgkin-Huxley squid axon</a> kinetics. The simulator stimulates the cell and runs for 50 ms.
</p>
<div class="mw-highlight mw-highlight-lang-cpp mw-content-ltr" dir="ltr"><pre><span class="c1">//create two sections, the body of the neuron and a very long axon</span>
<span class="n">create</span><span class="w"> </span><span class="n">soma</span><span class="p">,</span><span class="w"> </span><span class="n">axon</span>
<span class="n">soma</span><span class="w"> </span><span class="p">{</span>
<span class="w"> </span><span class="c1">//length is set to 100 micrometers </span>
<span class="w"> </span><span class="n">L</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">100</span>
<span class="w"> </span><span class="c1">//diameter is set to 100 micrometers</span>
<span class="w"> </span><span class="n">diam</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">100</span>
<span class="w"> </span><span class="c1">//insert a mechanism simulating the standard squid Hodgkin–Huxley channels</span>
<span class="w"> </span><span class="n">insert</span><span class="w"> </span><span class="n">hh</span>
<span class="w"> </span><span class="c1">//insert a mechanism simulating the passive membrane properties</span>
<span class="w"> </span><span class="n">insert</span><span class="w"> </span><span class="n">pas</span>
<span class="p">}</span>
<span class="n">axon</span><span class="w"> </span><span class="p">{</span>
<span class="w"> </span><span class="n">L</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">5000</span>
<span class="w"> </span><span class="n">diam</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">10</span>
<span class="w"> </span><span class="n">insert</span><span class="w"> </span><span class="n">hh</span>
<span class="w"> </span><span class="n">insert</span><span class="w"> </span><span class="n">pas</span>
<span class="w"> </span><span class="c1">//the axon shall be simulated using 10 compartments. By default a single compartment is used</span>
<span class="w"> </span><span class="n">nseg</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">10</span>
<span class="p">}</span>
<span class="c1">//connect the proximal end of the axon to the distal end of the soma</span>
<span class="n">connect</span><span class="w"> </span><span class="n">axon</span><span class="p">(</span><span class="mi">0</span><span class="p">),</span><span class="w"> </span><span class="n">soma</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
<span class="c1">//declare and insert a current clamp into the middle of the soma</span>
<span class="n">objref</span><span class="w"> </span><span class="n">stim</span>
<span class="n">soma</span><span class="w"> </span><span class="n">stim</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="k">new</span><span class="w"> </span><span class="n">IClamp</span><span class="p">(</span><span class="mf">0.5</span><span class="p">)</span>
<span class="c1">//define some parameters of the stimulus: delay, duration (both in ms) and amplitude (in nA)</span>
<span class="n">stim</span><span class="p">.</span><span class="n">del</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">10</span>
<span class="n">stim</span><span class="p">.</span><span class="n">dur</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">5</span>
<span class="n">stim</span><span class="p">.</span><span class="n">amp</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">10</span>
<span class="c1">//load a default NEURON library file that defines the run routine</span>
<span class="n">load_file</span><span class="p">(</span><span class="s">"stdrun.hoc"</span><span class="p">)</span>
<span class="c1">//set the simulation to run for 50 ms</span>
<span class="n">tstop</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">50</span>
<span class="c1">//run the simulation</span>
<span class="n">run</span><span class="p">()</span>
</pre></div>
<p>A plot can be generated showing the voltage traces starting from the soma and the distal end of the axon. The <a href="Action_potential" title="Action potential">action potential</a> at the end of the axon arrives slightly later than it appears in the soma at the point of stimulation. The plot is membrane voltage versus time.
</p><p><span class="mw-default-size" typeof="mw:File"></span>
</p>
<div class="mw-heading mw-heading2"><h2 id="References">References</h2></div>
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<li id="cite_note-releases-1"><span class="mw-cite-backlink">^ <a href="#cite_ref-releases_1-0"><sup><i><b>a</b></i></sup></a> <a href="#cite_ref-releases_1-1"><sup><i><b>b</b></i></sup></a></span> <span class="reference-text"><style data-mw-deduplicate="TemplateStyles:r1238218222">
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</style><cite class="citation web cs1"><a rel="nofollow" class="external text" href="https://github.com/neuronsimulator/nrn/releases">"Releases · neuronsimulator/nrn"</a>. <i>github.com</i><span class="reference-accessdate">. Retrieved <span class="nowrap">2021-04-20</span></span>.</cite></span>
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<li id="cite_note-2"><span class="mw-cite-backlink"><b><a href="#cite_ref-2">^</a></b></span> <span class="reference-text"><cite class="citation web cs1"><a rel="nofollow" class="external text" href="http://www.neuron.yale.edu/neuron/node/85">"New release of NEURON includes reactive diffusion! - NEURON"</a>.</cite></span>
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<li id="cite_note-3"><span class="mw-cite-backlink"><b><a href="#cite_ref-3">^</a></b></span> <span class="reference-text"><cite class="citation web cs1"><a rel="nofollow" class="external text" href="https://www.neuron.yale.edu/phpBB/viewtopic.php?f=22&t=1476#p5263">"www.neuron.yale.edu • View topic - NEURON 7.0 now available"</a>.</cite></span>
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<li id="cite_note-4"><span class="mw-cite-backlink"><b><a href="#cite_ref-4">^</a></b></span> <span class="reference-text"><cite class="citation web cs1"><a rel="nofollow" class="external text" href="http://www.neuron.yale.edu/neuron/static/docs/cbtut/stylized/topol.html">"Specify topology"</a>.</cite></span>
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<li id="cite_note-5"><span class="mw-cite-backlink"><b><a href="#cite_ref-5">^</a></b></span> <span class="reference-text"><cite class="citation web cs1"><a rel="nofollow" class="external text" href="http://www.neuron.yale.edu/neuron/static/docs/cbtut/stylized/subsets.html">"Specify subsets"</a>.</cite></span>
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<li id="cite_note-6"><span class="mw-cite-backlink"><b><a href="#cite_ref-6">^</a></b></span> <span class="reference-text"><cite class="citation web cs1"><a rel="nofollow" class="external text" href="http://www.neuron.yale.edu/neuron/static/docs/cbtut/parameterized/setsdi.html">"Set up a SubsetDomainIterator"</a>.</cite></span>
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<li id="cite_note-7"><span class="mw-cite-backlink"><b><a href="#cite_ref-7">^</a></b></span> <span class="reference-text"><cite class="citation web cs1"><a rel="nofollow" class="external text" href="http://www.neuron.yale.edu/neuron/static/docs/cbtut/stylized/geom.html">"Specify geometry"</a>.</cite></span>
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<li id="cite_note-8"><span class="mw-cite-backlink"><b><a href="#cite_ref-8">^</a></b></span> <span class="reference-text"><a rel="nofollow" class="external text" href="http://Hodgkin%E2%80%93Huxley_model#Ionic_current_characterization">Hodgkin-Huxley ionic current characterization</a></span>
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<li id="cite_note-9"><span class="mw-cite-backlink"><b><a href="#cite_ref-9">^</a></b></span> <span class="reference-text"><cite class="citation web cs1"><a rel="nofollow" class="external text" href="http://www.neuron.yale.edu/neuron/static/docs/chanlbild/hhstyle/outline.html">"Creating a channel from an HH-style specification"</a>.</cite></span>
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<li id="cite_note-10"><span class="mw-cite-backlink"><b><a href="#cite_ref-10">^</a></b></span> <span class="reference-text"><a rel="nofollow" class="external text" href="http://www.neuron.yale.edu/neuron/static/docs/help/neuron/neuron/mech.html#pointprocesses">PointProcess documentation</a></span>
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<li id="cite_note-11"><span class="mw-cite-backlink"><b><a href="#cite_ref-11">^</a></b></span> <span class="reference-text"><cite class="citation web cs1"><a rel="nofollow" class="external text" href="http://www.neuron.yale.edu/neuron/static/docs/netbuild/hybrid/plotwhat.html">"Plotting Variables from Biophysical Cell Models in a Network"</a>.</cite></span>
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<li id="cite_note-12"><span class="mw-cite-backlink"><b><a href="#cite_ref-12">^</a></b></span> <span class="reference-text"><cite class="citation web cs1"><a rel="nofollow" class="external text" href="http://www.neuron.yale.edu/neuron/static/docs/cbtut/parameterized/usemodel.html">"Use the model specification"</a>.</cite></span>
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<div class="mw-heading mw-heading2"><h2 id="External_links">External links</h2></div>
<ul><li><a rel="nofollow" class="external text" href="http://www.cambridge.org/us/academic/subjects/life-sciences/neuroscience/neuron-book">The NEURON Book</a></li>
<li><a rel="nofollow" class="external text" href="https://web.archive.org/web/20120203081139/http://www.anc.ed.ac.uk/school/neuron/">A Neuron tutorial</a></li>
<li><a rel="nofollow" class="external text" href="http://www.neuron.yale.edu/neuron/">NEURON documentation</a> at <a href="Yale_University" title="Yale University">Yale University</a></li>
<li><a class="external text external" href="https://upload.wikimedia.org/wikipedia/commons/4/4b/Neuron_Network_Builder_GUI.jpg">Screenshot of the network builder, displaying a completed simple network</a></li></ul></div><!--htdig_noindex--><div><div class="zim-footer">
This article is issued from <a class="external text" title="Last edited on 2023-08-10" href="https://en.wikipedia.org/wiki/?title=Neuron_(software)&oldid=1169658806">Wikipedia</a>. The text is available under <a class="external text" href="https://creativecommons.org/licenses/by-sa/4.0/deed.en">Creative Commons Attribution-Share Alike 4.0</a> unless otherwise noted. Additional terms may apply for the media files.
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