Wiki source code of Neuron

Version 171.1 by abonard on 2025/05/23 13:20
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adavison 1.1 1
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abonard 3.1 3 * ((( ==== **[[Beginner >>||anchor = "HBeginner-1"]]** ==== )))
jessicamitchell 2.1 4
abonard 136.1 5 * ((( ==== **[[Advanced >>||anchor = "HAdvanced-1"]]** ==== )))
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abonard 3.1 7 === **Beginner** ===
jessicamitchell 2.1 8
9 === [[A NEURON Programming Tutorial - part C>>http://web.mit.edu/neuron_v7.4/nrntuthtml/tutorial/tutC.html||rel=" noopener noreferrer" target="_blank"]] ===
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abonard 3.1 11 **Level**: beginner(%%) **Type**: user documentation
jessicamitchell 2.1 12
abonard 3.1 13 After this tutorial, students will be able to replicate neurons using templates and connect these neurons together.
abonard 128.1 14 === [[A NEURON Programming Tutorial - Part A>>http://web.mit.edu/neuron_v7.4/nrntuthtml/tutorial/tutA.html||rel=" noopener noreferrer" target="_blank"]] ===
jessicamitchell 2.1 15
abonard 128.1 16 **Level**: beginner(%%) **Type**: user documentation
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18 After this tutorial, students will be able to know how to create a single compartment neuron model with Hodgkin-Huxley conductances, how to run the simulator and how to display the simulation results
abonard 129.1 19 === [[A NEURON Programming Tutorial - Part B>>http://web.mit.edu/neuron_v7.4/nrntuthtml/tutorial/tutB.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 128.1 20
abonard 129.1 21 **Level**: beginner(%%) **Type**: user documentation
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23 After this tutorial, students will be able to work with more advanced topics of building multi-compartmental neurons and using different types of graphs to display the results
abonard 130.1 24 === [[A NEURON Programming Tutorial - Part D>>http://web.mit.edu/neuron_v7.4/nrntuthtml/tutorial/tutE.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 129.1 25
abonard 130.1 26 **Level**: beginner(%%) **Type**: user documentation
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28 After this tutorial, students will be able to add new membrane mechanisms to the simulator and incorporate them in our neurons.
abonard 131.1 29 === [[Construction and Use of Models: Part 1. Elementary tools>>https://neuron.yale.edu/neuron/static/docs/elementarytools/outline.htm||rel=" noopener noreferrer" target="_blank"]] ===
abonard 130.1 30
abonard 131.1 31 **Level**: beginner(%%) **Type**: user documentation
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33 A good beginner's tutorial to get an introduction to some of NEURON's basic GUI tools.
abonard 132.1 34 === [[A NEURON Programming Tutorial - Introduction>>https://web.mit.edu/neuron_v7.4/nrntuthtml/index.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 131.1 35
abonard 132.1 36 **Level**: beginner(%%) **Type**: user documentation
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38 This is a web based tutorial in the NEURON Simulation package. It will hopefully take you step by step, through the process of creating a complex simulation of a small network of neurons.
39 Starting by creating a single compartment neuron model with Hodgkin-Huxley conductances, how to run the simulator and how to display the simulation results, building multi-compartmental neurons, using different types of graphs to display the results, how to replicate neurons using templates, add new membrane mechanisms to the simulator and incorporate them into our neurons, increasing simulation speed and ways of getting data out of NEURON.
abonard 133.1 40 === [[Outline of "Construction and Use of Models: Part 1. Elementary tools">>https://neuron.yale.edu/neuron/static/docs/elementarytools/outline.htm||rel=" noopener noreferrer" target="_blank"]] ===
abonard 132.1 41
abonard 133.1 42 **Level**: beginner(%%) **Type**: interactive tutorial
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44 In this beginner tutorial you will learn how to make a simple model using hoc and how to use NEURON's graphical tools to create an interface for running simulations and to modify the model itself.
abonard 134.1 45 === [[The hoc programming language>>https://neuron.yale.edu/neuron/static/docs/programming/hoc_slides.pdf||rel=" noopener noreferrer" target="_blank"]] ===
abonard 133.1 46
abonard 134.1 47 **Level**: beginner(%%) **Type**: slide deck
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49 Slides from a presentation on hoc syntax. Clear and concise. Includes an example of program analysis (walkthrough of code for a model cell generated by the CellBuilder).
abonard 135.1 50 === [[A NEURON Programming Tutorial - Part E>>http://web.mit.edu/neuron_v7.4/nrntuthtml/tutorial/tutE.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 134.1 51
abonard 135.1 52 **Level**: beginner(%%) **Type**: user documentation
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54 After this tutorial, students will be able to save data from the simulations and methods for increasing simulation speed.
abonard 136.1 55 === **Advanced** ===
abonard 135.1 56
abonard 136.1 57 === [[Reaction-Diffusion – Radial Diffusion>>https://neuron.yale.edu/neuron/docs/radial-diffusion||rel=" noopener noreferrer" target="_blank"]] ===
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59 **Level**: advanced(%%) **Type**: -
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61 Using NEURON Radial diffusion can be implemented in rxd using multicompartment reactions. By creating a series of shells and borders with reactions between them dependent the diffusion coefficient.
abonard 137.1 62 === [[Reaction-Diffusion Example – Calcium Wave>>https://neuron.yale.edu/neuron/docs/reaction-diffusion-calcium-wave||rel=" noopener noreferrer" target="_blank"]] ===
abonard 136.1 63
abonard 137.1 64 **Level**: advanced(%%) **Type**: interactive tutorial
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66 The model presented in this tutorial generates Ca2+ waves and is a simplification of the model we used in Neymotin et al., 2015.
abonard 138.1 67 === [[Reaction-Diffusion – 3D/Hybrid Intracellular Tutorial>>https://neuron.yale.edu/neuron/docs/3dhybrid-intracellular-tutorial||rel=" noopener noreferrer" target="_blank"]] ===
abonard 137.1 68
abonard 138.1 69 **Level**: advanced(%%) **Type**: interactive tutorial
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71 This tutorial provides an overview of how to set up a simple travelling wave in both cases.
abonard 139.1 72 === [[Reaction-Diffusion – Initialization strategies>>https://neuron.yale.edu/neuron/docs/initialization-strategies||rel=" noopener noreferrer" target="_blank"]] ===
abonard 138.1 73
abonard 139.1 74 **Level**: advanced(%%) **Type**: interactive tutorial
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76 In this tutorial you will learn how to implement cell signalling function in the reaction-diffusion system by characterising your problems by the answers to three questions: (1) Where do the dynamics occur, (2) Who are the actors, and (3) How do they interact?
abonard 140.1 77 === [[Ball and Stick model part 3>>https://neuron.yale.edu/neuron/docs/ball-and-stick-model-part-3||rel=" noopener noreferrer" target="_blank"]] ===
abonard 139.1 78
abonard 140.1 79 **Level**: advanced(%%) **Type**: user documentation
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abonard 141.1 81 === [[Using the CellBuilder – Introduction>>https://neuron.yale.edu/neuron/static/docs/cbtut/main.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 140.1 82
abonard 141.1 83 **Level**: advanced(%%) **Type**: interactive tutorial
84
85 The following tutorials show how to use the CellBuilder, a powerful and convenient tool for constructing and managing models of individual neurons. It breaks the job of model specification into a sequence of tasks:
86 1. Setting up model topology (branching pattern).
87 2. Grouping sections with shared properties into subsets.
88 3. Assigning geometric properties (length, diameter) to subsets or individual sections, and specifying a discretization strategy (i.e. how to set nseg).
89 4. Assigning biophysical properties (Ra, cm, ion channels, buffers, pumps, etc.) to subsets or individual sections.
abonard 142.1 90 === [[Using Import3D – Exploring morphometric data and fixing problems>>https://neuron.yale.edu/neuron/docs/import3d/fix_problems||rel=" noopener noreferrer" target="_blank"]] ===
abonard 141.1 91
abonard 142.1 92 **Level**: advanced(%%) **Type**: user documentation
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94 Import3D tool can be used to translate common varieties of cellular morphometric data into a CellBuilder that specifies the anatomical properties of a model neuron. This Tutorial will guide you through how to fix problems in your morphometric data.
abonard 143.1 95 === [[Randomness in NEURON models– The solution>>https://neuron.yale.edu/neuron/docs/solution||rel=" noopener noreferrer" target="_blank"]] ===
abonard 142.1 96
abonard 143.1 97 **Level**: advanced(%%) **Type**: user documentation
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99 In this part of the tutorial we will show you how to give NetStim its own random number generator.
abonard 144.1 100 === [[Segmentation intro: Dealing with simulations that generate a lot of data>>https://neuron.yale.edu/neuron/docs/dealing-simulations-generate-lot-data||rel=" noopener noreferrer" target="_blank"]] ===
abonard 143.1 101
abonard 144.1 102 **Level**: advanced(%%) **Type**: user documentation
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104 How to deal with simulations that generate a lot of data that must be saved? We will showcase different approaches.
abonard 145.1 105 === [[Using the Channel Builder – Creating a channel from an HH-style specification>>https://neuron.yale.edu/neuron/static/docs/chanlbild/hhstyle/outline.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 144.1 106
abonard 145.1 107 **Level**: advanced(%%) **Type**: interactive tutorial
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109 Our goal is to implement a new voltage-gated macroscopic current whose properties are described by HH-style equations.
abonard 146.1 110 === [[Using the Channel Builder – Creating a channel from a kinetic scheme specification>>https://neuron.yale.edu/neuron/static/docs/chanlbild/kinetic/outline.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 145.1 111
abonard 146.1 112 **Level**: advanced(%%) **Type**: interactive tutorial
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114 Here we will implement a new voltage-gated macroscopic current whose properties are described by a family of chemical reactions.
abonard 147.1 115 === [[Randomness in NEURON models– Source code that demonstrates the solution>>https://neuron.yale.edu/neuron/docs/source-code-demonstrates-solution||rel=" noopener noreferrer" target="_blank"]] ===
abonard 146.1 116
abonard 147.1 117 **Level**: advanced(%%) **Type**: user documentation
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abonard 148.1 119 === [[Using the Network Builder – Introduction to Network Construction>>https://neuron.yale.edu/neuron/static/docs/netbuild/intro.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 147.1 120
abonard 148.1 121 **Level**: advanced(%%) **Type**: user documentation
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abonard 149.1 123 === [[Python introduction>>https://neuron.yale.edu/neuron/docs/python-introduction||rel=" noopener noreferrer" target="_blank"]] ===
abonard 148.1 124
abonard 149.1 125 **Level**: advanced(%%) **Type**: user documentation
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127 This page provides a brief introduction to Python syntax, Variables, Lists and Dicts, For loops and iterators, Functions, Classes, Importing modules, Writing and reading files with Pickling.
abonard 150.1 128 === [[Reaction-Diffusion Example – RxD with MOD files>>https://neuron.yale.edu/neuron/docs/rxd-mod-files||rel=" noopener noreferrer" target="_blank"]] ===
abonard 149.1 129
abonard 150.1 130 **Level**: advanced(%%) **Type**: user documentation
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132 NEURON's reaction-diffusion infrastructure can be used to readily allow intracellular concentrations to respond to currents generated in MOD files. This example shows you a simple model with just a single point soma, of length and diameter 10 microns, with Hodgkin-Huxley kinetics, and dynamic sodium (declared using rxd but without any additional kinetics).
abonard 151.1 133 === [[Segmenting a simulation of a model network - Introduction>>https://neuron.yale.edu/neuron/docs/segmenting-simulation-model-network||rel=" noopener noreferrer" target="_blank"]] ===
abonard 150.1 134
abonard 151.1 135 **Level**: advanced(%%) **Type**: user documentation
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abonard 152.1 137 === [[Using the Network Builder – Tutorial 1: Making Networks of Artificial Neurons>>https://neuron.yale.edu/neuron/static/docs/netbuild/artnet/outline.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 151.1 138
abonard 152.1 139 **Level**: advanced(%%) **Type**: interactive tutorial
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141 Learn how to Artificial Integrate and Fire cell with a synapse that is driven by an afferent burst of spikes.
abonard 153.1 142 === [[Reaction-Diffusion Example – Restricting a reaction to part of a region>>https://neuron.yale.edu/neuron/docs/example-restricting-reaction-part-region||rel=" noopener noreferrer" target="_blank"]] ===
abonard 152.1 143
abonard 153.1 144 **Level**: advanced(%%) **Type**: user documentation
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146 Implementation example for the restriction of the reaction to part of a region.
abonard 154.1 147 === [[Segmenting a simulation of a model cell - Introduction>>https://neuron.yale.edu/neuron/docs/segmenting-simulation-model-cell||rel=" noopener noreferrer" target="_blank"]] ===
abonard 153.1 148
abonard 154.1 149 **Level**: advanced(%%) **Type**: user documentation
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abonard 155.1 151 === [[Scripting NEURON basics>>https://neuron.yale.edu/neuron/docs/scripting-neuron-basics||rel=" noopener noreferrer" target="_blank"]] ===
abonard 154.1 152
abonard 155.1 153 **Level**: advanced(%%) **Type**: user documentation
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155 The objectives of this part of the tutorial are to get familiar with basic operations of NEURON using Python. In this worksheet we will: Create a passive cell membrane in NEURON. Create a synaptic stimulus onto the neuron. Modify parameters of the membrane and stimulus. Visualize results with bokeh.
abonard 156.1 156 === [[Reaction-Diffusion – Thresholds>>https://neuron.yale.edu/neuron/docs/reaction-diffusion-thresholds||rel=" noopener noreferrer" target="_blank"]] ===
abonard 155.1 157
abonard 156.1 158 **Level**: advanced(%%) **Type**: interactive tutorial
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160 Learn how to scale reaction rates by a function of the form f(x) for suitably chosen a and m to approximately threshold them by a concentration.
abonard 157.1 161 === [[Randomness in NEURON models>>https://neuron.yale.edu/neuron/docs/randomness-neuron-models||rel=" noopener noreferrer" target="_blank"]] ===
abonard 156.1 162
abonard 157.1 163 **Level**: advanced(%%) **Type**: user documentation
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165 We will touch upon the following subjects in this tutorial:
166 How to create model specification code that employs randomization to avoid undesired correlations between parameters, and to produce a model cell or network that has the same architecture and biophysical properties, and generates the same simulation results regardless of whether it is run on serial or parallel hardware.
167 How to generate spike streams or other signals that fluctuate in ways that are statistically independent of each other.
abonard 158.1 168 === [[Using the CellBuilder– Specifying parameterized variation of biophysical properties>>https://neuron.yale.edu/neuron/static/docs/cbtut/parameterized/outline.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 157.1 169
abonard 158.1 170 **Level**: advanced(%%) **Type**: interactive tutorial
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172 How to make one or more biophysical properties vary systematically with position in space.
abonard 159.1 173 === [[Using Import3D – An introduction>>https://neuron.yale.edu/neuron/docs/import3d||rel=" noopener noreferrer" target="_blank"]] ===
abonard 158.1 174
abonard 159.1 175 **Level**: advanced(%%) **Type**: user documentation
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177 Import3D tool can be used to translate common varieties of cellular morphometric data into a CellBuilder that specifies the anatomical properties of a model neuron. This Tutorial will guide you in reading a morphometric data file and converting it to a NEURON model as well as
178 exploring morphometric data and fixing problems.
abonard 160.1 179 === [[Segmenting a simulation of a model network – 1. Implement and test the computational model itself>>https://neuron.yale.edu/neuron/docs/1-implement-and-test-computational-model-itself-0||rel=" noopener noreferrer" target="_blank"]] ===
abonard 159.1 180
abonard 160.1 181 **Level**: advanced(%%) **Type**: user documentation
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abonard 161.1 183 === [[Segmenting a simulation of a model network – 2. Run a "complete" simulation and save its results>>https://neuron.yale.edu/neuron/docs/2-run-complete-simulation-and-save-its-results-0||rel=" noopener noreferrer" target="_blank"]] ===
abonard 160.1 184
abonard 161.1 185 **Level**: advanced(%%) **Type**: user documentation
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abonard 162.1 187 === [[Segmenting a simulation of a model cell – 2. Run a "complete" simulation and save its results>>https://neuron.yale.edu/neuron/docs/2-run-complete-simulation-and-save-its-results||rel=" noopener noreferrer" target="_blank"]] ===
abonard 161.1 188
abonard 162.1 189 **Level**: advanced(%%) **Type**: user documentation
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abonard 163.1 191 === [[Segmenting a simulation of a model cell – 1. Implement and test the computational model itself>>https://neuron.yale.edu/neuron/docs/1-implement-and-test-computational-model-itself||rel=" noopener noreferrer" target="_blank"]] ===
abonard 162.1 192
abonard 163.1 193 **Level**: advanced(%%) **Type**: user documentation
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abonard 164.1 195 === [[Using NEURON's Optimization Tools – Tutorial 2 : Fitting a model to data>>https://neuron.yale.edu/neuron/static/docs/optimiz/model/outline.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 163.1 196
abonard 164.1 197 **Level**: advanced(%%) **Type**: user documentation
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199 We will go over how to create an "unoptimized" model, set up a current clamp experiment on this model, configure a MultipleRunFitter to do a "run fitness" optimization, load the Experimental Data into the iclamp Run Fitness Generator, specify the parameters that will be adjusted and finally perform the optimization.
abonard 165.1 200 === [[Reaction-Diffusion – Hodgkin-Huxley using rxd>>https://neuron.yale.edu/neuron/docs/hodgkin-huxley-using-rxd||rel=" noopener noreferrer" target="_blank"]] ===
abonard 164.1 201
abonard 165.1 202 **Level**: advanced(%%) **Type**: interactive tutorial
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204 In this tutorial you will learn how to set the proper parameters for the Hodgkin–Huxley model in NEURON.
abonard 166.1 205 === [[Using the CellBuilder – Creating a stylised ("stick-figure") model cell>>https://neuron.yale.edu/neuron/static/docs/cbtut/stylized/outline.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 165.1 206
abonard 166.1 207 **Level**: advanced(%%) **Type**: -
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209 Learn how to build an extremely simplified model of a pyramidal cell.
abonard 167.1 210 === [[Ball and Stick model part 2>>https://neuron.yale.edu/neuron/docs/ball-and-stick-model-part-2||rel=" noopener noreferrer" target="_blank"]] ===
abonard 166.1 211
abonard 167.1 212 **Level**: advanced(%%) **Type**: user documentation
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abonard 168.1 214 === [[Reaction-Diffusion Example – Circadian rhythm>>https://neuron.yale.edu/neuron/docs/example-circadian-rhythm||rel=" noopener noreferrer" target="_blank"]] ===
abonard 167.1 215
abonard 168.1 216 **Level**: advanced(%%) **Type**: user documentation
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218 Here we develop a NEURON implementation of the Leloup-Goldbeter model for circadian rhythms in Drosophila. In this example NEURON's h library and its standard run system are being used as well as matplotlib to plot concentrations of circadian proteins over time.
abonard 169.1 219 === [[Segmenting a simulation of a model cell – 3. Run a segmented simulation and save its results>>https://neuron.yale.edu/neuron/docs/3-run-segmented-simulation-and-save-its-results||rel=" noopener noreferrer" target="_blank"]] ===
abonard 168.1 220
abonard 169.1 221 **Level**: advanced(%%) **Type**: user documentation
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abonard 170.1 223 === [[ModelView: Compact display of parameters for NEURON models.>>https://neuron.yale.edu/neuron/static/papers/mview/modelviewhbp2004.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 169.1 224
abonard 170.1 225 **Level**: advanced(%%) **Type**: user documentation
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227 This example demonstrates how ModelView can explore a NEURON model.
abonard 171.1 228 === [[Segmenting a simulation of a model network – 3. Run a segmented simulation and save its results>>https://neuron.yale.edu/neuron/docs/3-run-segmented-simulation-and-save-its-results-0||rel=" noopener noreferrer" target="_blank"]] ===
abonard 170.1 229
abonard 171.1 230 **Level**: advanced(%%) **Type**: user documentation
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