Changes for page Neuron

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

From version 35.1
edited by abonard
on 2025/04/10 15:07
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To version 29.1
edited by abonard
on 2025/04/10 15:07
Change comment: There is no comment for this version

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144 144  **Level**: advanced(%%) **Type**: user documentation
145 145  
146 146  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"]] ===
148 148  
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 -=== [[Reaction-Diffusion – Thresholds>>https://neuron.yale.edu/neuron/docs/reaction-diffusion-thresholds||rel=" noopener noreferrer" target="_blank"]] ===
157 -
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.
161 -=== [[Randomness in NEURON models>>https://neuron.yale.edu/neuron/docs/randomness-neuron-models||rel=" noopener noreferrer" target="_blank"]] ===
162 -
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.
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"]] ===
169 -
170 -**Level**: advanced(%%) **Type**: interactive tutorial
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"]] ===
174 -
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.
179 -