Wiki source code of Neuron

Version 83.1 by abonard on 2025/04/10 15:16
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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 74.1 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 66.1 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 66.1 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 67.1 19 === [[A NEURON Programming Tutorial - Part B>>http://web.mit.edu/neuron_v7.4/nrntuthtml/tutorial/tutB.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 66.1 20
abonard 67.1 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 68.1 24 === [[A NEURON Programming Tutorial - Part D>>http://web.mit.edu/neuron_v7.4/nrntuthtml/tutorial/tutE.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 67.1 25
abonard 68.1 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 69.1 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 68.1 30
abonard 69.1 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 70.1 34 === [[A NEURON Programming Tutorial - Introduction>>https://web.mit.edu/neuron_v7.4/nrntuthtml/index.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 69.1 35
abonard 70.1 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 71.1 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 70.1 41
abonard 71.1 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 72.1 45 === [[The hoc programming language>>https://neuron.yale.edu/neuron/static/docs/programming/hoc_slides.pdf||rel=" noopener noreferrer" target="_blank"]] ===
abonard 71.1 46
abonard 72.1 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 73.1 50 === [[A NEURON Programming Tutorial - Part E>>http://web.mit.edu/neuron_v7.4/nrntuthtml/tutorial/tutE.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 72.1 51
abonard 73.1 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 74.1 55 === **Advanced** ===
abonard 73.1 56
abonard 74.1 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 75.1 62 === [[Reaction-Diffusion Example – Calcium Wave>>https://neuron.yale.edu/neuron/docs/reaction-diffusion-calcium-wave||rel=" noopener noreferrer" target="_blank"]] ===
abonard 74.1 63
abonard 75.1 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 76.1 67 === [[Reaction-Diffusion – 3D/Hybrid Intracellular Tutorial>>https://neuron.yale.edu/neuron/docs/3dhybrid-intracellular-tutorial||rel=" noopener noreferrer" target="_blank"]] ===
abonard 75.1 68
abonard 76.1 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 77.1 72 === [[Reaction-Diffusion – Initialization strategies>>https://neuron.yale.edu/neuron/docs/initialization-strategies||rel=" noopener noreferrer" target="_blank"]] ===
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abonard 77.1 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 78.1 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 77.1 78
abonard 78.1 79 **Level**: advanced(%%) **Type**: user documentation
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abonard 79.1 81 === [[Using the CellBuilder – Introduction>>https://neuron.yale.edu/neuron/static/docs/cbtut/main.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 78.1 82
abonard 79.1 83 **Level**: advanced(%%) **Type**: interactive tutorial
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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 80.1 90 === [[Using Import3D – Exploring morphometric data and fixing problems>>https://neuron.yale.edu/neuron/docs/import3d/fix_problems||rel=" noopener noreferrer" target="_blank"]] ===
abonard 79.1 91
abonard 80.1 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 81.1 95 === [[Randomness in NEURON models– The solution>>https://neuron.yale.edu/neuron/docs/solution||rel=" noopener noreferrer" target="_blank"]] ===
abonard 80.1 96
abonard 81.1 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 82.1 100 === [[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 81.1 101
abonard 82.1 102 **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 83.1 105 === [[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 82.1 106
abonard 83.1 107 **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.
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