Changes for page Neuron

Last modified by abonard on 2025/04/10 15:17

From version 80.1
edited by abonard
on 2025/04/10 15:16
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To version 93.1
edited by abonard
on 2025/04/10 15:16
Change comment: There is no comment for this version

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92 92  **Level**: advanced(%%) **Type**: user documentation
93 93  
94 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.
95 +=== [[Randomness in NEURON models– The solution>>https://neuron.yale.edu/neuron/docs/solution||rel=" noopener noreferrer" target="_blank"]] ===
95 95  
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.
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"]] ===
101 +
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.
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"]] ===
106 +
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.
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"]] ===
111 +
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.
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"]] ===
116 +
117 +**Level**: advanced(%%) **Type**: user documentation
118 +
119 +=== [[Using the Network Builder – Introduction to Network Construction>>https://neuron.yale.edu/neuron/static/docs/netbuild/intro.html||rel=" noopener noreferrer" target="_blank"]] ===
120 +
121 +**Level**: advanced(%%) **Type**: user documentation
122 +
123 +=== [[Python introduction>>https://neuron.yale.edu/neuron/docs/python-introduction||rel=" noopener noreferrer" target="_blank"]] ===
124 +
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.
128 +=== [[Reaction-Diffusion Example – RxD with MOD files>>https://neuron.yale.edu/neuron/docs/rxd-mod-files||rel=" noopener noreferrer" target="_blank"]] ===
129 +
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).
133 +=== [[Segmenting a simulation of a model network - Introduction>>https://neuron.yale.edu/neuron/docs/segmenting-simulation-model-network||rel=" noopener noreferrer" target="_blank"]] ===
134 +
135 +**Level**: advanced(%%) **Type**: user documentation
136 +
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"]] ===
138 +
139 +**Level**: advanced(%%) **Type**: interactive tutorial
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"]] ===
143 +
144 +**Level**: advanced(%%) **Type**: user documentation
145 +
146 +Implementation example for the restriction of the reaction to part of a region.
147 +=== [[Segmenting a simulation of a model cell - Introduction>>https://neuron.yale.edu/neuron/docs/segmenting-simulation-model-cell||rel=" noopener noreferrer" target="_blank"]] ===
148 +
149 +**Level**: advanced(%%) **Type**: user documentation
150 +
151 +=== [[Scripting NEURON basics>>https://neuron.yale.edu/neuron/docs/scripting-neuron-basics||rel=" noopener noreferrer" target="_blank"]] ===
152 +
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.
156 +