Wiki source code of Neuron

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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 198.1 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 190.1 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 190.1 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 191.1 19 === [[A NEURON Programming Tutorial - Part B>>http://web.mit.edu/neuron_v7.4/nrntuthtml/tutorial/tutB.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 190.1 20
abonard 191.1 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 192.1 24 === [[A NEURON Programming Tutorial - Part D>>http://web.mit.edu/neuron_v7.4/nrntuthtml/tutorial/tutE.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 191.1 25
abonard 192.1 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 193.1 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 192.1 30
abonard 193.1 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 194.1 34 === [[A NEURON Programming Tutorial - Introduction>>https://web.mit.edu/neuron_v7.4/nrntuthtml/index.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 193.1 35
abonard 194.1 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 195.1 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 194.1 41
abonard 195.1 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 196.1 45 === [[The hoc programming language>>https://neuron.yale.edu/neuron/static/docs/programming/hoc_slides.pdf||rel=" noopener noreferrer" target="_blank"]] ===
abonard 195.1 46
abonard 196.1 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 197.1 50 === [[A NEURON Programming Tutorial - Part E>>http://web.mit.edu/neuron_v7.4/nrntuthtml/tutorial/tutE.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 196.1 51
abonard 197.1 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 198.1 55 === **Advanced** ===
abonard 197.1 56
abonard 198.1 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 199.1 62 === [[Reaction-Diffusion Example – Calcium Wave>>https://neuron.yale.edu/neuron/docs/reaction-diffusion-calcium-wave||rel=" noopener noreferrer" target="_blank"]] ===
abonard 198.1 63
abonard 199.1 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 200.1 67 === [[Reaction-Diffusion – 3D/Hybrid Intracellular Tutorial>>https://neuron.yale.edu/neuron/docs/3dhybrid-intracellular-tutorial||rel=" noopener noreferrer" target="_blank"]] ===
abonard 199.1 68
abonard 200.1 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 201.1 72 === [[Reaction-Diffusion – Initialization strategies>>https://neuron.yale.edu/neuron/docs/initialization-strategies||rel=" noopener noreferrer" target="_blank"]] ===
abonard 200.1 73
abonard 201.1 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 202.1 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 201.1 78
abonard 202.1 79 **Level**: advanced(%%) **Type**: user documentation
80
abonard 203.1 81 === [[Using the CellBuilder – Introduction>>https://neuron.yale.edu/neuron/static/docs/cbtut/main.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 202.1 82
abonard 203.1 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 204.1 90 === [[Using Import3D – Exploring morphometric data and fixing problems>>https://neuron.yale.edu/neuron/docs/import3d/fix_problems||rel=" noopener noreferrer" target="_blank"]] ===
abonard 203.1 91
abonard 204.1 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 205.1 95 === [[Randomness in NEURON models– The solution>>https://neuron.yale.edu/neuron/docs/solution||rel=" noopener noreferrer" target="_blank"]] ===
abonard 204.1 96
abonard 205.1 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 206.1 100 === [[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 205.1 101
abonard 206.1 102 **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 207.1 105 === [[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 206.1 106
abonard 207.1 107 **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 208.1 110 === [[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 207.1 111
abonard 208.1 112 **Level**: advanced(%%) **Type**: interactive tutorial
113
114 Here we will implement a new voltage-gated macroscopic current whose properties are described by a family of chemical reactions.
abonard 209.1 115 === [[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 208.1 116
abonard 209.1 117 **Level**: advanced(%%) **Type**: user documentation
118
abonard 210.1 119 === [[Using the Network Builder – Introduction to Network Construction>>https://neuron.yale.edu/neuron/static/docs/netbuild/intro.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 209.1 120
abonard 210.1 121 **Level**: advanced(%%) **Type**: user documentation
122
abonard 211.1 123 === [[Python introduction>>https://neuron.yale.edu/neuron/docs/python-introduction||rel=" noopener noreferrer" target="_blank"]] ===
abonard 210.1 124
abonard 211.1 125 **Level**: advanced(%%) **Type**: user documentation
126
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 212.1 128 === [[Reaction-Diffusion Example – RxD with MOD files>>https://neuron.yale.edu/neuron/docs/rxd-mod-files||rel=" noopener noreferrer" target="_blank"]] ===
abonard 211.1 129
abonard 212.1 130 **Level**: advanced(%%) **Type**: user documentation
131
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 213.1 133 === [[Segmenting a simulation of a model network - Introduction>>https://neuron.yale.edu/neuron/docs/segmenting-simulation-model-network||rel=" noopener noreferrer" target="_blank"]] ===
abonard 212.1 134
abonard 213.1 135 **Level**: advanced(%%) **Type**: user documentation
136
abonard 214.1 137 === [[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 213.1 138
abonard 214.1 139 **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 215.1 142 === [[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 214.1 143
abonard 215.1 144 **Level**: advanced(%%) **Type**: user documentation
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146 Implementation example for the restriction of the reaction to part of a region.
abonard 216.1 147 === [[Segmenting a simulation of a model cell - Introduction>>https://neuron.yale.edu/neuron/docs/segmenting-simulation-model-cell||rel=" noopener noreferrer" target="_blank"]] ===
abonard 215.1 148
abonard 216.1 149 **Level**: advanced(%%) **Type**: user documentation
150
abonard 217.1 151 === [[Scripting NEURON basics>>https://neuron.yale.edu/neuron/docs/scripting-neuron-basics||rel=" noopener noreferrer" target="_blank"]] ===
abonard 216.1 152
abonard 217.1 153 **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 218.1 156 === [[Reaction-Diffusion – Thresholds>>https://neuron.yale.edu/neuron/docs/reaction-diffusion-thresholds||rel=" noopener noreferrer" target="_blank"]] ===
abonard 217.1 157
abonard 218.1 158 **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 219.1 161 === [[Randomness in NEURON models>>https://neuron.yale.edu/neuron/docs/randomness-neuron-models||rel=" noopener noreferrer" target="_blank"]] ===
abonard 218.1 162
abonard 219.1 163 **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 220.1 168 === [[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 219.1 169
abonard 220.1 170 **Level**: advanced(%%) **Type**: interactive tutorial
171
172 How to make one or more biophysical properties vary systematically with position in space.
abonard 221.1 173 === [[Using Import3D – An introduction>>https://neuron.yale.edu/neuron/docs/import3d||rel=" noopener noreferrer" target="_blank"]] ===
abonard 220.1 174
abonard 221.1 175 **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 222.1 179 === [[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 221.1 180
abonard 222.1 181 **Level**: advanced(%%) **Type**: user documentation
182
abonard 223.1 183 === [[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 222.1 184
abonard 223.1 185 **Level**: advanced(%%) **Type**: user documentation
186
abonard 224.1 187 === [[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 223.1 188
abonard 224.1 189 **Level**: advanced(%%) **Type**: user documentation
190
abonard 225.1 191 === [[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 224.1 192
abonard 225.1 193 **Level**: advanced(%%) **Type**: user documentation
194
abonard 226.1 195 === [[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 225.1 196
abonard 226.1 197 **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 227.1 200 === [[Reaction-Diffusion – Hodgkin-Huxley using rxd>>https://neuron.yale.edu/neuron/docs/hodgkin-huxley-using-rxd||rel=" noopener noreferrer" target="_blank"]] ===
abonard 226.1 201
abonard 227.1 202 **Level**: advanced(%%) **Type**: interactive tutorial
203
204 In this tutorial you will learn how to set the proper parameters for the Hodgkin–Huxley model in NEURON.
abonard 228.1 205 === [[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 227.1 206
abonard 228.1 207 **Level**: advanced(%%) **Type**: -
208
209 Learn how to build an extremely simplified model of a pyramidal cell.
abonard 229.1 210 === [[Ball and Stick model part 2>>https://neuron.yale.edu/neuron/docs/ball-and-stick-model-part-2||rel=" noopener noreferrer" target="_blank"]] ===
abonard 228.1 211
abonard 229.1 212 **Level**: advanced(%%) **Type**: user documentation
213
abonard 230.1 214 === [[Reaction-Diffusion Example – Circadian rhythm>>https://neuron.yale.edu/neuron/docs/example-circadian-rhythm||rel=" noopener noreferrer" target="_blank"]] ===
abonard 229.1 215
abonard 230.1 216 **Level**: advanced(%%) **Type**: user documentation
217
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 231.1 219 === [[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 230.1 220
abonard 231.1 221 **Level**: advanced(%%) **Type**: user documentation
222
abonard 232.1 223 === [[ModelView: Compact display of parameters for NEURON models.>>https://neuron.yale.edu/neuron/static/papers/mview/modelviewhbp2004.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 231.1 224
abonard 232.1 225 **Level**: advanced(%%) **Type**: user documentation
226
227 This example demonstrates how ModelView can explore a NEURON model.
abonard 233.1 228 === [[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 232.1 229
abonard 233.1 230 **Level**: advanced(%%) **Type**: user documentation
231
abonard 234.1 232 === [[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 233.1 233
abonard 234.1 234 **Level**: advanced(%%) **Type**: user documentation
235
abonard 235.1 236 === [[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 234.1 237
abonard 235.1 238 **Level**: advanced(%%) **Type**: user documentation
239
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 236.1 241 === [[Ball and Stick model part 4>>https://neuron.yale.edu/neuron/docs/ball-and-stick-model-part-4||rel=" noopener noreferrer" target="_blank"]] ===
abonard 235.1 242
abonard 236.1 243 **Level**: advanced(%%) **Type**: user documentation
244
abonard 237.1 245 === [[Reaction-Diffusion>>https://neuron.yale.edu/neuron/docs/reaction-diffusion||rel=" noopener noreferrer" target="_blank"]] ===
abonard 236.1 246
abonard 237.1 247 **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 238.1 250 === [[Creating a stylized ("stick figure") model cell>>https://neuron.yale.edu/neuron/static/docs/cbtut/stylized/outline.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 237.1 251
abonard 238.1 252 **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 239.1 255 === [[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 238.1 256
abonard 239.1 257 **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 240.1 260 === [[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 239.1 261
abonard 240.1 262 **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 241.1 265 === [[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 240.1 266
abonard 241.1 267 **Level**: advanced(%%) **Type**: user documentation
268
269 Learn how to generate random spike streams with the use of NetStim.
abonard 242.1 270 === [[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 241.1 271
abonard 242.1 272 **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 243.1 275 === [[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 242.1 276
abonard 243.1 277 **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 244.1 280 === [[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 243.1 281
abonard 244.1 282 **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 245.1 285 === [[Using NEURON's Optimization Tools>>https://neuron.yale.edu/neuron/static/docs/optimiz/main.html||rel=" noopener noreferrer" target="_blank"]] ===
abonard 244.1 286
abonard 245.1 287 **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.
abonard 246.1 290 === [[Ball and Stick model part 1>>https://neuron.yale.edu/neuron/docs/ball-and-stick-model-part-1||rel=" noopener noreferrer" target="_blank"]] ===
abonard 245.1 291
abonard 246.1 292 **Level**: advanced(%%) **Type**: user documentation
293
abonard 247.1 294 === [[Reaction-Diffusion – Extracellular Diffusion>>https://neuron.yale.edu/neuron/docs/extracellular-diffusion||rel=" noopener noreferrer" target="_blank"]] ===
abonard 246.1 295
abonard 247.1 296 **Level**: advanced(%%) **Type**: interactive tutorial
297
298 We have expanded the capabilities the NEURON reaction diffusion module to support a macroscopic model of the extracellular space. Here is brief a tutorial that provides an overview of the python interface.
abonard 248.1 299 === [[Segmenting a simulation of a model cell – 4. Reconstitute and verify the "complete" simulation results>>https://neuron.yale.edu/neuron/docs/4-reconstitute-and-verify-complete-simulation-results||rel=" noopener noreferrer" target="_blank"]] ===
abonard 247.1 300
abonard 248.1 301 **Level**: advanced(%%) **Type**: user documentation
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abonard 249.1 303 === [[Using the Network Builder – Tutorial 2: Making Hybrid Nets>>https://neuron.yale.edu/neuron/static/docs/netbuild/hybrid/outline.html||rel=" noopener noreferrer" target="_blank"]] ===
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abonard 249.1 305 **Level**: advanced(%%) **Type**: interactive tutorial
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307 In this tutorial you will learn how to define the types of cells, create each cell in the network and connect the cells (this includes specifying parameters such as delays and weights) . We'll use a pair of biophysical models for M and R, and a NetStim artificial neuron will provide the excitatory drive to M.
308 In the end we will run a simulation and plot the input and output spike trains.
abonard 250.1 309 === [[Reaction-Diffusion Example – mGluR example>>https://neuron.yale.edu/neuron/docs/mglur-example||rel=" noopener noreferrer" target="_blank"]] ===
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abonard 250.1 311 **Level**: advanced(%%) **Type**: user documentation
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313 This examples, will show how to use rxd to handle the kinetics of a mGLUR.
314