| ... | ... | @@ -107,4 +107,89 @@ | 
              
                    | 107 | 107 | **Level**: advanced(%%)  **Type**: interactive tutorial | 
              
                    | 108 | 108 |  | 
              
                    | 109 | 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"]] === | 
              
                    | 110 | 110 |  | 
              
                    |  | 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 | +=== [[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 | +=== [[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"]] === | 
              
                    |  | 180 | + | 
              
                    |  | 181 | +**Level**: advanced(%%)  **Type**: user documentation | 
              
                    |  | 182 | + | 
              
                    |  | 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"]] === | 
              
                    |  | 184 | + | 
              
                    |  | 185 | +**Level**: advanced(%%)  **Type**: user documentation | 
              
                    |  | 186 | + | 
              
                    |  | 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"]] === | 
              
                    |  | 188 | + | 
              
                    |  | 189 | +**Level**: advanced(%%)  **Type**: user documentation | 
              
                    |  | 190 | + | 
              
                    |  | 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"]] === | 
              
                    |  | 192 | + | 
              
                    |  | 193 | +**Level**: advanced(%%)  **Type**: user documentation | 
              
                    |  | 194 | + | 
              
                    |  | 195 | + |