Wiki source code of Neuron

Version 263.1 by abonard on 2025/06/13 16:09
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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 260.1 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 252.1 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 252.1 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 253.1 19 === [[A NEURON Programming Tutorial - Part B>>http://web.mit.edu/neuron_v7.4/nrntuthtml/tutorial/tutB.html||rel=" noopener noreferrer" target="_blank"]] ===
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abonard 253.1 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 254.1 24 === [[A NEURON Programming Tutorial - Part D>>http://web.mit.edu/neuron_v7.4/nrntuthtml/tutorial/tutE.html||rel=" noopener noreferrer" target="_blank"]] ===
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abonard 254.1 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 255.1 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"]] ===
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abonard 255.1 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 256.1 34 === [[A NEURON Programming Tutorial - Introduction>>https://web.mit.edu/neuron_v7.4/nrntuthtml/index.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 255.1 35
abonard 256.1 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 257.1 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 256.1 41
abonard 257.1 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 258.1 45 === [[The hoc programming language>>https://neuron.yale.edu/neuron/static/docs/programming/hoc_slides.pdf||rel=" noopener noreferrer" target="_blank"]] ===
abonard 257.1 46
abonard 258.1 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 259.1 50 === [[A NEURON Programming Tutorial - Part E>>http://web.mit.edu/neuron_v7.4/nrntuthtml/tutorial/tutE.html||rel=" noopener noreferrer" target="_blank"]] ===
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abonard 259.1 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 260.1 55 === **Advanced** ===
abonard 259.1 56
abonard 260.1 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 261.1 62 === [[Reaction-Diffusion Example – Calcium Wave>>https://neuron.yale.edu/neuron/docs/reaction-diffusion-calcium-wave||rel=" noopener noreferrer" target="_blank"]] ===
abonard 260.1 63
abonard 261.1 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 262.1 67 === [[Reaction-Diffusion – 3D/Hybrid Intracellular Tutorial>>https://neuron.yale.edu/neuron/docs/3dhybrid-intracellular-tutorial||rel=" noopener noreferrer" target="_blank"]] ===
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abonard 262.1 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 263.1 72 === [[Reaction-Diffusion – Initialization strategies>>https://neuron.yale.edu/neuron/docs/initialization-strategies||rel=" noopener noreferrer" target="_blank"]] ===
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abonard 263.1 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?
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