From version 51.1
edited by abonard
on 2025/04/10 15:08
on 2025/04/10 15:08
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To version 2.1
edited by jessicamitchell
on 2023/09/11 11:44
on 2023/09/11 11:44
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... ... @@ -1,250 +1,222 @@ 1 +Available tutorials: 1 1 3 +=== [[Construction and Use of Models: Part 1. Elementary tools>>https://neuron.yale.edu/neuron/static/docs/elementarytools/outline.htm||rel=" noopener noreferrer" target="_blank"]] === 2 2 3 - * ((( ==== **[[Beginner>>||anchor = "HBeginner-1"]]** ==== )))5 +//Level: beginner// 4 4 5 -* ((( ==== **[[Advanced >>||anchor = "HAdvanced-1"]]** ==== ))) 7 +A good beginner's tutorial. Introduces some of NEURON's basic GUI tools. 8 +=== [[The hoc programming language>>https://neuron.yale.edu/neuron/static/docs/programming/hoc_slides.pdf||rel=" noopener noreferrer" target="_blank"]] === 6 6 7 - ===**Beginner** ===10 +//Level: beginner// 8 8 9 -=== [[ ANEURON ProgrammingTutorial-partC>>http://web.mit.edu/neuron_v7.4/nrntuthtml/tutorial/tutC.html||rel=" noopener noreferrer" target="_blank"]] ===12 +=== [[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"]] === 10 10 11 - **Level**:beginner(%%) **Type**: userdocumentation14 +//Level: advanced// 12 12 13 -After this tutorial, students will be able to replicate neurons using templates and connect these neurons together. 14 -=== [[A NEURON Programming Tutorial - Part A>>http://web.mit.edu/neuron_v7.4/nrntuthtml/tutorial/tutA.html||rel=" noopener noreferrer" target="_blank"]] === 16 +=== [[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"]] === 15 15 16 - **Level**:beginner(%%) **Type**: userdocumentation18 +//Level: advanced// 17 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 19 -=== [[A NEURON Programming Tutorial - Part B>>http://web.mit.edu/neuron_v7.4/nrntuthtml/tutorial/tutB.html||rel=" noopener noreferrer" target="_blank"]] === 20 +=== [[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"]] === 20 20 21 - **Level**:beginner(%%) **Type**: userdocumentation22 +//Level: advanced// 22 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 24 -=== [[A NEURON Programming Tutorial - Part D>>http://web.mit.edu/neuron_v7.4/nrntuthtml/tutorial/tutE.html||rel=" noopener noreferrer" target="_blank"]] === 24 +=== [[3D/Hybrid Intracellular Tutorial>>https://neuron.yale.edu/neuron/docs/3dhybrid-intracellular-tutorial||rel=" noopener noreferrer" target="_blank"]] === 25 25 26 - **Level**:beginner(%%) **Type**: userdocumentation26 +//Level: advanced// 27 27 28 -After this tutorial, students will be able to add new membrane mechanisms to the simulator and incorporate them in our neurons. 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"]] === 28 +=== [[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"]] === 30 30 31 - **Level**:beginner(%%) **Type**: userdocumentation30 +//Level: advanced// 32 32 33 -A good beginner's tutorial to get an introduction to some of NEURON's basic GUI tools. 34 -=== [[A NEURON Programming Tutorial - Introduction>>https://web.mit.edu/neuron_v7.4/nrntuthtml/index.html||rel=" noopener noreferrer" target="_blank"]] === 32 +=== [[A NEURON Programming Tutorial - Part A>>http://web.mit.edu/neuron_v7.4/nrntuthtml/tutorial/tutA.html||rel=" noopener noreferrer" target="_blank"]] === 35 35 36 - **Level**:beginner(%%) **Type**: userdocumentation34 +//Level: advanced// 37 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. 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"]] === 36 +=== [[A NEURON Programming Tutorial - Part B>>http://web.mit.edu/neuron_v7.4/nrntuthtml/tutorial/tutB.html||rel=" noopener noreferrer" target="_blank"]] === 41 41 42 - **Level**:beginner(%%) **Type**: interactive tutorial38 +//Level: advanced// 43 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. 45 -=== [[The hoc programming language>>https://neuron.yale.edu/neuron/static/docs/programming/hoc_slides.pdf||rel=" noopener noreferrer" target="_blank"]] === 40 +=== [[A NEURON Programming Tutorial - part C>>http://web.mit.edu/neuron_v7.4/nrntuthtml/tutorial/tutC.html||rel=" noopener noreferrer" target="_blank"]] === 46 46 47 - **Level**:beginner(%%) **Type**: slide deck42 +//Level: advanced// 48 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). 50 50 === [[A NEURON Programming Tutorial - Part E>>http://web.mit.edu/neuron_v7.4/nrntuthtml/tutorial/tutE.html||rel=" noopener noreferrer" target="_blank"]] === 51 51 52 - **Level**:beginner(%%) **Type**: userdocumentation46 +//Level: advanced// 53 53 54 -After this tutorial, students will be able to save data from the simulations and methods for increasing simulation speed. 55 -=== **Advanced** === 48 +=== [[Ball and Stick model part 1>>https://neuron.yale.edu/neuron/docs/ball-and-stick-model-part-1||rel=" noopener noreferrer" target="_blank"]] === 56 56 57 - === [[Reaction-Diffusion– Radial Diffusion>>https://neuron.yale.edu/neuron/docs/radial-diffusion||rel=" noopener noreferrer" target="_blank"]] ===50 +//Level: advanced// 58 58 59 - **Level**:advanced(%%)**Type**:-52 +=== [[Ball and Stick model part 2>>https://neuron.yale.edu/neuron/docs/ball-and-stick-model-part-2||rel=" noopener noreferrer" target="_blank"]] === 60 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. 62 -=== [[Reaction-Diffusion Example – Calcium Wave>>https://neuron.yale.edu/neuron/docs/reaction-diffusion-calcium-wave||rel=" noopener noreferrer" target="_blank"]] === 54 +//Level: advanced// 63 63 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. 67 -=== [[Reaction-Diffusion – 3D/Hybrid Intracellular Tutorial>>https://neuron.yale.edu/neuron/docs/3dhybrid-intracellular-tutorial||rel=" noopener noreferrer" target="_blank"]] === 68 - 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. 72 -=== [[Reaction-Diffusion – Initialization strategies>>https://neuron.yale.edu/neuron/docs/initialization-strategies||rel=" noopener noreferrer" target="_blank"]] === 73 - 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? 77 77 === [[Ball and Stick model part 3>>https://neuron.yale.edu/neuron/docs/ball-and-stick-model-part-3||rel=" noopener noreferrer" target="_blank"]] === 78 78 79 - **Level**: advanced(%%) **Type**: user documentation58 +//Level: advanced// 80 80 81 -=== [[ Usingthe CellBuilder– Introduction>>https://neuron.yale.edu/neuron/static/docs/cbtut/main.html||rel=" noopener noreferrer" target="_blank"]] ===60 +=== [[Ball and Stick model part 4>>https://neuron.yale.edu/neuron/docs/ball-and-stick-model-part-4||rel=" noopener noreferrer" target="_blank"]] === 82 82 83 - **Level**: advanced(%%) **Type**: interactive tutorial62 +//Level: advanced// 84 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. 90 -=== [[Using Import3D – Exploring morphometric data and fixing problems>>https://neuron.yale.edu/neuron/docs/import3d/fix_problems||rel=" noopener noreferrer" target="_blank"]] === 64 +=== [[Creating a channel from a kinetic scheme specification>>https://neuron.yale.edu/neuron/static/docs/chanlbild/kinetic/outline.html||rel=" noopener noreferrer" target="_blank"]] === 91 91 92 - **Level**: advanced(%%) **Type**: user documentation66 +//Level: advanced// 93 93 94 - Import3Dtoolcanbeusedtoranslatecommon varietiesfcellularmorphometric data intoa CellBuilder thatspecifiesthe anatomicalpropertiesofamodel neuron. ThisTutorial will guide youthroughhow tofix problemsinyourmorphometricdata.95 -=== [[ RandomnessinNEURONmodels–Thesolution>>https://neuron.yale.edu/neuron/docs/solution||rel=" noopener noreferrer" target="_blank"]] ===68 +Here we will implement a new voltage-gated macroscopic current whose properties are described by a family of chemical reactions. 69 +=== [[Creating a channel from an HH-style specification>>https://neuron.yale.edu/neuron/static/docs/chanlbild/hhstyle/outline.html||rel=" noopener noreferrer" target="_blank"]] === 96 96 97 - **Level**: advanced(%%) **Type**: user documentation71 +//Level: advanced// 98 98 99 - Inthispartftheutorialweillshowyou howtogiveNetStim itsownrandomnumbergenerator.100 -=== [[ Segmentationintro:Dealingwithsimulations thatgenerate alotof data>>https://neuron.yale.edu/neuron/docs/dealing-simulations-generate-lot-data||rel=" noopener noreferrer" target="_blank"]] ===73 +Our goal is to implement a new voltage-gated macroscopic current whose properties are described by HH-style equations. 74 +=== [[Creating a model of stochastic channel gating>>https://neuron.yale.edu/neuron/static/docs/chanlbild/stochastic/outline.html||rel=" noopener noreferrer" target="_blank"]] === 101 101 102 - **Level**: advanced(%%) **Type**: user documentation76 +//Level: advanced// 103 103 104 - Howtodealwithsimulationsthatgenerateaotoftathatmustbesaved?Wewillshowcasedifferentapproaches.105 -=== [[ Using theChannel Builder– Creating achannel from an HH-style specification>>https://neuron.yale.edu/neuron/static/docs/chanlbild/hhstyle/outline.html||rel=" noopener noreferrer" target="_blank"]] ===78 +Given a Channel Builder that implements a deterministic channel specified by a kinetic scheme, we create a new one that implements stochastic gating. 79 +=== [[Creating a stylized ("stick figure") model cell>>https://neuron.yale.edu/neuron/static/docs/cbtut/stylized/outline.html||rel=" noopener noreferrer" target="_blank"]] === 106 106 107 - **Level**: advanced(%%) **Type**: interactive tutorial81 +//Level: advanced// 108 108 109 -Our goal is to i mplementaewvoltage-gatedmacroscopic currentwhosepropertiesaredescribedby HH-styleequations.110 -=== [[ Using theChannel Builder – Creatinga channel fromakineticscheme specification>>https://neuron.yale.edu/neuron/static/docs/chanlbild/kinetic/outline.html||rel=" noopener noreferrer" target="_blank"]] ===83 +Our goal is to build an extremely simplified model of a pyramidal cell. 84 +=== [[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"]] === 111 111 112 - **Level**: advanced(%%) **Type**: interactive tutorial86 +//Level: advanced// 113 113 114 -Here we will implement a new voltage-gated macroscopic current whose properties are described by a family of chemical reactions. 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"]] === 88 +=== [[Example: circadian rhythm>>https://neuron.yale.edu/neuron/docs/example-circadian-rhythm||rel=" noopener noreferrer" target="_blank"]] === 116 116 117 - **Level**: advanced(%%) **Type**: user documentation90 +//Level: advanced// 118 118 119 -=== [[ Using theNetwork Builder–Introduction toNetworkConstruction>>https://neuron.yale.edu/neuron/static/docs/netbuild/intro.html||rel=" noopener noreferrer" target="_blank"]] ===92 +=== [[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"]] === 120 120 121 - **Level**: advanced(%%) **Type**: user documentation94 +//Level: advanced// 122 122 123 -=== [[ Pythonintroduction>>https://neuron.yale.edu/neuron/docs/python-introduction||rel=" noopener noreferrer" target="_blank"]] ===96 +=== [[Exploring morphometric data and fixing problems>>https://neuron.yale.edu/neuron/docs/import3d/fix_problems||rel=" noopener noreferrer" target="_blank"]] === 124 124 125 - **Level**: advanced(%%) **Type**: user documentation98 +//Level: advanced// 126 126 127 -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. 128 -=== [[Reaction-Diffusion Example – RxD with MOD files>>https://neuron.yale.edu/neuron/docs/rxd-mod-files||rel=" noopener noreferrer" target="_blank"]] === 100 +=== [[Extracellular Diffusion>>https://neuron.yale.edu/neuron/docs/extracellular-diffusion||rel=" noopener noreferrer" target="_blank"]] === 129 129 130 - **Level**: advanced(%%) **Type**: user documentation102 +//Level: advanced// 131 131 132 -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). 133 -=== [[Segmenting a simulation of a model network - Introduction>>https://neuron.yale.edu/neuron/docs/segmenting-simulation-model-network||rel=" noopener noreferrer" target="_blank"]] === 104 +=== [[How to generate independent random spike streams>>https://neuron.yale.edu/neuron/docs/how-generate-independent-random-spike-streams||rel=" noopener noreferrer" target="_blank"]] === 134 134 135 - **Level**: advanced(%%) **Type**: user documentation106 +//Level: advanced// 136 136 137 -=== [[ Usingthe Network Builder – Tutorial 1: MakingNetworksof Artificial Neurons>>https://neuron.yale.edu/neuron/static/docs/netbuild/artnet/outline.html||rel=" noopener noreferrer" target="_blank"]] ===108 +=== [[Introduction to Network Construction>>https://neuron.yale.edu/neuron/static/docs/netbuild/intro.html||rel=" noopener noreferrer" target="_blank"]] === 138 138 139 - **Level**: advanced(%%) **Type**: interactive tutorial110 +//Level: advanced// 140 140 141 -Learn how to Artificial Integrate and Fire cell with a synapse that is driven by an afferent burst of spikes. 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"]] === 112 +=== [[Managing a model cell with complex anatomy>>https://neuron.yale.edu/neuron/static/docs/cbtut/pt3d/outline.html||rel=" noopener noreferrer" target="_blank"]] === 143 143 144 - **Level**: advanced(%%) **Type**: user documentation114 +//Level: advanced// 145 145 146 - Implementationexamplefortherestrictionofthereactiontopartofa region.147 -=== [[ Segmenting a simulationofaodelcell - Introduction>>https://neuron.yale.edu/neuron/docs/segmenting-simulation-model-cell||rel=" noopener noreferrer" target="_blank"]] ===116 +We use the CellBuilder to specify the spatial grid (nseg) and biophysical properties of a model based on detailed morphometric data. 117 +=== [[mGluR example>>https://neuron.yale.edu/neuron/docs/mglur-example||rel=" noopener noreferrer" target="_blank"]] === 148 148 149 - **Level**: advanced(%%) **Type**: user documentation119 +//Level: advanced// 150 150 151 -=== [[ ScriptingNEURONbasics>>https://neuron.yale.edu/neuron/docs/scripting-neuron-basics||rel=" noopener noreferrer" target="_blank"]] ===121 +=== [[ModelView: Compact display of parameters for NEURON models.>>https://neuron.yale.edu/neuron/static/papers/mview/modelviewhbp2004.html||rel=" noopener noreferrer" target="_blank"]] === 152 152 153 - **Level**: advanced(%%) **Type**: user documentation123 +//Level: advanced// 154 154 155 -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. 156 -=== [[Reaction-Diffusion – Thresholds>>https://neuron.yale.edu/neuron/docs/reaction-diffusion-thresholds||rel=" noopener noreferrer" target="_blank"]] === 125 +=== [[Python introduction>>https://neuron.yale.edu/neuron/docs/python-introduction||rel=" noopener noreferrer" target="_blank"]] === 157 157 158 - **Level**: advanced(%%) **Type**: interactive tutorial127 +//Level: advanced// 159 159 160 -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. 129 +This page provides a brief introduction to: 130 +Python syntax 131 +Variables 132 +Lists and Dicts 133 +For loops and iterators 134 +Functions 135 +Classes 136 +Importing modules 137 +Writing and reading files with Pickling. 161 161 === [[Randomness in NEURON models>>https://neuron.yale.edu/neuron/docs/randomness-neuron-models||rel=" noopener noreferrer" target="_blank"]] === 162 162 163 - **Level**: advanced(%%) **Type**: user documentation140 +//Level: advanced// 164 164 165 -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. 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"]] === 142 +=== [[Reaction-Diffusion>>https://neuron.yale.edu/neuron/docs/reaction-diffusion||rel=" noopener noreferrer" target="_blank"]] === 169 169 170 - **Level**: advanced(%%) **Type**: interactive tutorial144 +//Level: advanced// 171 171 172 -How to make one or more biophysical properties vary systematically with position in space. 173 -=== [[Using Import3D – An introduction>>https://neuron.yale.edu/neuron/docs/import3d||rel=" noopener noreferrer" target="_blank"]] === 146 +=== [[Reaction-Diffusion: Calcium Wave>>https://neuron.yale.edu/neuron/docs/reaction-diffusion-calcium-wave||rel=" noopener noreferrer" target="_blank"]] === 174 174 175 - **Level**: advanced(%%) **Type**: user documentation148 +//Level: advanced// 176 176 177 -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. 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"]] === 150 +=== [[Reaction-Diffusion: Thresholds>>https://neuron.yale.edu/neuron/docs/reaction-diffusion-thresholds||rel=" noopener noreferrer" target="_blank"]] === 180 180 181 - **Level**: advanced(%%) **Type**: user documentation152 +//Level: advanced// 182 182 183 -=== [[ Segmenting a simulationofamodel network – 2. Run a"complete" simulation andsaveits results>>https://neuron.yale.edu/neuron/docs/2-run-complete-simulation-and-save-its-results-0||rel=" noopener noreferrer" target="_blank"]] ===154 +=== [[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"]] === 184 184 185 - **Level**: advanced(%%) **Type**: user documentation156 +//Level: advanced// 186 186 187 -=== [[ Segmenting asimulationof amodelcell– 2. Runa"complete"simulationandsave itsresults>>https://neuron.yale.edu/neuron/docs/2-run-complete-simulation-and-save-its-results||rel=" noopener noreferrer" target="_blank"]] ===158 +=== [[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"]] === 188 188 189 - **Level**: advanced(%%) **Type**: user documentation160 +//Level: advanced// 190 190 191 -=== [[ Segmentinga simulation of a model cell – 1. Implement and test thecomputationalmodel itself>>https://neuron.yale.edu/neuron/docs/1-implement-and-test-computational-model-itself||rel=" noopener noreferrer" target="_blank"]] ===162 +=== [[RxD with MOD files>>https://neuron.yale.edu/neuron/docs/rxd-mod-files||rel=" noopener noreferrer" target="_blank"]] === 192 192 193 - **Level**: advanced(%%) **Type**: user documentation164 +//Level: advanced// 194 194 195 -=== [[ Using NEURON'sOptimization Tools– Tutorial 2 : Fitting a model to data>>https://neuron.yale.edu/neuron/static/docs/optimiz/model/outline.html||rel=" noopener noreferrer" target="_blank"]] ===166 +=== [[Scripting NEURON basics>>https://neuron.yale.edu/neuron/docs/scripting-neuron-basics||rel=" noopener noreferrer" target="_blank"]] === 196 196 197 - **Level**: advanced(%%) **Type**: user documentation168 +//Level: advanced// 198 198 199 -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. 200 -=== [[Reaction-Diffusion – Hodgkin-Huxley using rxd>>https://neuron.yale.edu/neuron/docs/hodgkin-huxley-using-rxd||rel=" noopener noreferrer" target="_blank"]] === 170 +The objectives of this part of the tutorial are to get familiar with basic operations of NEURON using Python. In this worksheet we will: 171 +Create a passive cell membrane in NEURON. 172 +Create a synaptic stimulus onto the neuron. 173 +Modify parameters of the membrane and stimulus. 174 +Visualize results with bokeh 175 +=== [[Segmenting a simulation of a model cell>>https://neuron.yale.edu/neuron/docs/segmenting-simulation-model-cell||rel=" noopener noreferrer" target="_blank"]] === 201 201 202 - **Level**: advanced(%%) **Type**: interactive tutorial177 +//Level: advanced// 203 203 204 -In this tutorial you will learn how to set the proper parameters for the Hodgkin–Huxley model in NEURON. 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"]] === 179 +=== [[Segmenting a simulation of a model network>>https://neuron.yale.edu/neuron/docs/segmenting-simulation-model-network||rel=" noopener noreferrer" target="_blank"]] === 206 206 207 - **Level**: advanced(%%) **Type**: -181 +//Level: advanced// 208 208 209 -Learn how to build an extremely simplified model of a pyramidal cell. 210 -=== [[Ball and Stick model part 2>>https://neuron.yale.edu/neuron/docs/ball-and-stick-model-part-2||rel=" noopener noreferrer" target="_blank"]] === 183 +=== [[Source code that demonstrates the solution>>https://neuron.yale.edu/neuron/docs/source-code-demonstrates-solution||rel=" noopener noreferrer" target="_blank"]] === 211 211 212 - **Level**: advanced(%%) **Type**: user documentation185 +//Level: advanced// 213 213 214 -=== [[ Reaction-DiffusionExample– Circadianrhythm>>https://neuron.yale.edu/neuron/docs/example-circadian-rhythm||rel=" noopener noreferrer" target="_blank"]] ===187 +=== [[Specifying parameterized variation of biophysical properties>>https://neuron.yale.edu/neuron/static/docs/cbtut/parameterized/outline.html||rel=" noopener noreferrer" target="_blank"]] === 215 215 216 - **Level**: advanced(%%) **Type**: user documentation189 +//Level: advanced// 217 217 218 -H erewedevelopa NEURON implementationof theLeloup-Goldbeter modelfor circadian rhythmsnDrosophila. Inthisexample NEURON'sh libraryand itsstandard run systemre being usedas wellas matplotlibtoplotconcentrationsof circadian proteins over time.219 -=== [[ Segmentingasimulation of a modelcell – 3. Run a segmented simulationand save its results>>https://neuron.yale.edu/neuron/docs/3-run-segmented-simulation-and-save-its-results||rel=" noopener noreferrer" target="_blank"]] ===191 +How to make one or more biophysical properties vary systematically with position in space. 192 +=== [[The solution>>https://neuron.yale.edu/neuron/docs/solution||rel=" noopener noreferrer" target="_blank"]] === 220 220 221 - **Level**: advanced(%%) **Type**: user documentation194 +//Level: advanced// 222 222 223 -=== [[ ModelView:Compactdisplayof parametersforNEURON models.>>https://neuron.yale.edu/neuron/static/papers/mview/modelviewhbp2004.html||rel=" noopener noreferrer" target="_blank"]] ===196 +=== [[Tutorial 1 : Fitting a function to data>>https://neuron.yale.edu/neuron/static/docs/optimiz/func/outline.html||rel=" noopener noreferrer" target="_blank"]] === 224 224 225 - **Level**: advanced(%%) **Type**: user documentation198 +//Level: advanced// 226 226 227 -This example demonstrates how ModelView can explore a NEURON model. 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"]] === 200 +=== [[Tutorial 1: Making Networks of Artificial Neurons>>https://neuron.yale.edu/neuron/static/docs/netbuild/artnet/outline.html||rel=" noopener noreferrer" target="_blank"]] === 229 229 230 - **Level**: advanced(%%) **Type**: user documentation202 +//Level: advanced// 231 231 232 -=== [[ Segmentingasimulationofa modelnetwork– 4. Reconstitute andverify the "complete" simulation results>>https://neuron.yale.edu/neuron/docs/4-reconstitute-and-verify-complete-simulation-results-0||rel=" noopener noreferrer" target="_blank"]] ===204 +=== [[Tutorial 2 : Fitting a model to data>>https://neuron.yale.edu/neuron/static/docs/optimiz/model/outline.html||rel=" noopener noreferrer" target="_blank"]] === 233 233 234 - **Level**: advanced(%%) **Type**: user documentation206 +//Level: advanced// 235 235 236 -=== [[ Using NEURON's OptimizationTools – Tutorial1:Fittinga functionto data>>https://neuron.yale.edu/neuron/static/docs/optimiz/func/outline.html||rel=" noopener noreferrer" target="_blank"]] ===208 +=== [[Tutorial 2: Making Hybrid Nets>>https://neuron.yale.edu/neuron/static/docs/netbuild/hybrid/outline.html||rel=" noopener noreferrer" target="_blank"]] === 237 237 238 - **Level**: advanced(%%) **Type**: user documentation210 +//Level: advanced// 239 239 240 -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. 241 -=== [[Ball and Stick model part 4>>https://neuron.yale.edu/neuron/docs/ball-and-stick-model-part-4||rel=" noopener noreferrer" target="_blank"]] === 212 +=== [[Using Import3D>>https://neuron.yale.edu/neuron/docs/import3d||rel=" noopener noreferrer" target="_blank"]] === 242 242 243 - **Level**: advanced(%%) **Type**: user documentation214 +//Level: advanced// 244 244 245 -=== [[Reaction-Diffusion>>https://neuron.yale.edu/neuron/docs/reaction-diffusion||rel=" noopener noreferrer" target="_blank"]] === 216 +Reading a morphometric data file and converting it to a NEURON model 217 +Exploring morphometric data and fixing problems 218 +=== [[Using NEURON's Optimization Tools>>https://neuron.yale.edu/neuron/static/docs/optimiz/main.html||rel=" noopener noreferrer" target="_blank"]] === 246 246 247 - **Level**: advanced(%%) **Type**: interactive tutorial220 +//Level: advanced// 248 248 249 -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? 250 250