Wiki source code of Neuron

Version 121.1 by abonard on 2025/04/10 15:17
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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"]] ===
10
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
17
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
22
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
27
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
32
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
37
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
43
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
48
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
53
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"]] ===
58
59 **Level**: advanced(%%) **Type**: -
60
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
65
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
70
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"]] ===
abonard 76.1 73
abonard 77.1 74 **Level**: advanced(%%) **Type**: interactive tutorial
75
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
80
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
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 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
93
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
98
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
103
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
108
109 Our goal is to implement a new voltage-gated macroscopic current whose properties are described by HH-style equations.
abonard 84.1 110 === [[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 83.1 111
abonard 84.1 112 **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 85.1 115 === [[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 84.1 116
abonard 85.1 117 **Level**: advanced(%%) **Type**: user documentation
118
abonard 86.1 119 === [[Using the Network Builder – Introduction to Network Construction>>https://neuron.yale.edu/neuron/static/docs/netbuild/intro.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 85.1 120
abonard 86.1 121 **Level**: advanced(%%) **Type**: user documentation
122
abonard 87.1 123 === [[Python introduction>>https://neuron.yale.edu/neuron/docs/python-introduction||rel=" noopener noreferrer" target="_blank"]] ===
abonard 86.1 124
abonard 87.1 125 **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 88.1 128 === [[Reaction-Diffusion Example – RxD with MOD files>>https://neuron.yale.edu/neuron/docs/rxd-mod-files||rel=" noopener noreferrer" target="_blank"]] ===
abonard 87.1 129
abonard 88.1 130 **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 89.1 133 === [[Segmenting a simulation of a model network - Introduction>>https://neuron.yale.edu/neuron/docs/segmenting-simulation-model-network||rel=" noopener noreferrer" target="_blank"]] ===
abonard 88.1 134
abonard 89.1 135 **Level**: advanced(%%) **Type**: user documentation
136
abonard 90.1 137 === [[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 89.1 138
abonard 90.1 139 **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 91.1 142 === [[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 90.1 143
abonard 91.1 144 **Level**: advanced(%%) **Type**: user documentation
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146 Implementation example for the restriction of the reaction to part of a region.
abonard 92.1 147 === [[Segmenting a simulation of a model cell - Introduction>>https://neuron.yale.edu/neuron/docs/segmenting-simulation-model-cell||rel=" noopener noreferrer" target="_blank"]] ===
abonard 91.1 148
abonard 92.1 149 **Level**: advanced(%%) **Type**: user documentation
150
abonard 93.1 151 === [[Scripting NEURON basics>>https://neuron.yale.edu/neuron/docs/scripting-neuron-basics||rel=" noopener noreferrer" target="_blank"]] ===
abonard 92.1 152
abonard 93.1 153 **Level**: advanced(%%) **Type**: user documentation
154
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 94.1 156 === [[Reaction-Diffusion – Thresholds>>https://neuron.yale.edu/neuron/docs/reaction-diffusion-thresholds||rel=" noopener noreferrer" target="_blank"]] ===
abonard 93.1 157
abonard 94.1 158 **Level**: advanced(%%) **Type**: interactive tutorial
159
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 95.1 161 === [[Randomness in NEURON models>>https://neuron.yale.edu/neuron/docs/randomness-neuron-models||rel=" noopener noreferrer" target="_blank"]] ===
abonard 94.1 162
abonard 95.1 163 **Level**: advanced(%%) **Type**: user documentation
164
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 96.1 168 === [[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 95.1 169
abonard 96.1 170 **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 97.1 173 === [[Using Import3D – An introduction>>https://neuron.yale.edu/neuron/docs/import3d||rel=" noopener noreferrer" target="_blank"]] ===
abonard 96.1 174
abonard 97.1 175 **Level**: advanced(%%) **Type**: user documentation
176
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 98.1 179 === [[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 97.1 180
abonard 98.1 181 **Level**: advanced(%%) **Type**: user documentation
182
abonard 99.1 183 === [[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 98.1 184
abonard 99.1 185 **Level**: advanced(%%) **Type**: user documentation
186
abonard 100.1 187 === [[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 99.1 188
abonard 100.1 189 **Level**: advanced(%%) **Type**: user documentation
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abonard 101.1 191 === [[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 100.1 192
abonard 101.1 193 **Level**: advanced(%%) **Type**: user documentation
194
abonard 102.1 195 === [[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 101.1 196
abonard 102.1 197 **Level**: advanced(%%) **Type**: user documentation
198
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 103.1 200 === [[Reaction-Diffusion – Hodgkin-Huxley using rxd>>https://neuron.yale.edu/neuron/docs/hodgkin-huxley-using-rxd||rel=" noopener noreferrer" target="_blank"]] ===
abonard 102.1 201
abonard 103.1 202 **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 104.1 205 === [[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 103.1 206
abonard 104.1 207 **Level**: advanced(%%) **Type**: -
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209 Learn how to build an extremely simplified model of a pyramidal cell.
abonard 105.1 210 === [[Ball and Stick model part 2>>https://neuron.yale.edu/neuron/docs/ball-and-stick-model-part-2||rel=" noopener noreferrer" target="_blank"]] ===
abonard 104.1 211
abonard 105.1 212 **Level**: advanced(%%) **Type**: user documentation
213
abonard 106.1 214 === [[Reaction-Diffusion Example – Circadian rhythm>>https://neuron.yale.edu/neuron/docs/example-circadian-rhythm||rel=" noopener noreferrer" target="_blank"]] ===
abonard 105.1 215
abonard 106.1 216 **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 107.1 219 === [[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 106.1 220
abonard 107.1 221 **Level**: advanced(%%) **Type**: user documentation
222
abonard 108.1 223 === [[ModelView: Compact display of parameters for NEURON models.>>https://neuron.yale.edu/neuron/static/papers/mview/modelviewhbp2004.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 107.1 224
abonard 108.1 225 **Level**: advanced(%%) **Type**: user documentation
226
227 This example demonstrates how ModelView can explore a NEURON model.
abonard 109.1 228 === [[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 108.1 229
abonard 109.1 230 **Level**: advanced(%%) **Type**: user documentation
231
abonard 110.1 232 === [[Segmenting a simulation of a model network – 4. Reconstitute and verify the "complete" simulation results>>https://neuron.yale.edu/neuron/docs/4-reconstitute-and-verify-complete-simulation-results-0||rel=" noopener noreferrer" target="_blank"]] ===
abonard 109.1 233
abonard 110.1 234 **Level**: advanced(%%) **Type**: user documentation
235
abonard 111.1 236 === [[Using NEURON's Optimization Tools – Tutorial 1 : Fitting a function to data>>https://neuron.yale.edu/neuron/static/docs/optimiz/func/outline.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 110.1 237
abonard 111.1 238 **Level**: advanced(%%) **Type**: user documentation
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240 We will look into how to bring up a Multiple Run Fitter, load the Experimental Data into the Multiple Run Fitter, specify the function we want to optimize, specify the parameters that will be adjusted, specify the criteria we want the function to satisfy and finally perform the optimization.
abonard 112.1 241 === [[Ball and Stick model part 4>>https://neuron.yale.edu/neuron/docs/ball-and-stick-model-part-4||rel=" noopener noreferrer" target="_blank"]] ===
abonard 111.1 242
abonard 112.1 243 **Level**: advanced(%%) **Type**: user documentation
244
abonard 113.1 245 === [[Reaction-Diffusion>>https://neuron.yale.edu/neuron/docs/reaction-diffusion||rel=" noopener noreferrer" target="_blank"]] ===
abonard 112.1 246
abonard 113.1 247 **Level**: advanced(%%) **Type**: interactive tutorial
248
249 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 114.1 250 === [[Creating a stylized ("stick figure") model cell>>https://neuron.yale.edu/neuron/static/docs/cbtut/stylized/outline.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 113.1 251
abonard 114.1 252 **Level**: advanced(%%) **Type**: user documentation
253
254 Our goal in this tutorial is to build an extremely simplified model of a pyramidal cell using the CellBuilder, a powerful and convenient tool for constructing and managing models of individual neurons. We will be looking into setting up model topology, grouping sections with shared properties into subsets, assigning geometric properties to subsets or individual sections, and specifying a discretization strategy, as well as assigning biophysical properties to subsets or individual sections.
abonard 115.1 255 === [[Randomness in NEURON models– Source code that demonstrates the problem>>https://neuron.yale.edu/neuron/docs/source-code-demonstrates-problem||rel=" noopener noreferrer" target="_blank"]] ===
abonard 114.1 256
abonard 115.1 257 **Level**: advanced(%%) **Type**: user documentation
258
259 The tutorial will show you how to declare important constants (model parameters and simulation parameters), load files that other stuff will depend on, create the model itself (just a collection of cells that spike at random times), specify instrumentation (in this case, recording of spike times), specify simulation control and execute one or more simulations with various model parameters in the source code.
abonard 116.1 260 === [[Using the Channel Builder – Creating a model of stochastic channel gating>>https://neuron.yale.edu/neuron/static/docs/chanlbild/stochastic/outline.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 115.1 261
abonard 116.1 262 **Level**: advanced(%%) **Type**: interactive tutorial
263
264 Given a Channel Builder that implements a deterministic channel specified by a kinetic scheme, we create a new one that implements stochastic gating.
abonard 117.1 265 === [[Randomness in NEURON models - How to generate independent random spike streams>>https://neuron.yale.edu/neuron/docs/how-generate-independent-random-spike-streams||rel=" noopener noreferrer" target="_blank"]] ===
abonard 116.1 266
abonard 117.1 267 **Level**: advanced(%%) **Type**: user documentation
268
269 Learn how to generate random spike streams with the use of NetStim.
abonard 118.1 270 === [[Using Import3D – Reading a morphometric data file and converting it to a NEURON model>>https://neuron.yale.edu/neuron/docs/import3d/read_data||rel=" noopener noreferrer" target="_blank"]] ===
abonard 117.1 271
abonard 118.1 272 **Level**: advanced(%%) **Type**: user documentation
273
274 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 bringing up an Import3d tool, then specifying a file to be read and finally export the data as a NEURON model.
abonard 119.1 275 === [[Reaction-Diffusion – Varying initial concentrations and parameters>>https://neuron.yale.edu/neuron/docs/reaction-diffusion-varying-initial-concentrations-and-parameters||rel=" noopener noreferrer" target="_blank"]] ===
abonard 118.1 276
abonard 119.1 277 **Level**: advanced(%%) **Type**: interactive tutorial
278
279 This tutorial will show you how to manipulate the rxd.Species attribute to see how the choice of initial conditions affects the dynamics.
abonard 120.1 280 === [[Using the CellBuilder – Managing a model cell with complex anatomy>>https://neuron.yale.edu/neuron/static/docs/cbtut/pt3d/outline.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 119.1 281
abonard 120.1 282 **Level**: advanced(%%) **Type**: interactive tutorial
283
284 We use the CellBuilder to specify the spatial grid (nseg) and biophysical properties of a model based on detailed morphometric data.
abonard 121.1 285 === [[Using NEURON's Optimization Tools>>https://neuron.yale.edu/neuron/static/docs/optimiz/main.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 120.1 286
abonard 121.1 287 **Level**: advanced(%%) **Type**: user documentation
288
289 This collection of tutorials shows how to use NEURON's optimization tools. Before working through these tutorials, most readers should probably examine the on-line "Introduction to Optimization" http://neos-guide.org/content/optimization-introduction.
290