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                    | 102 | 102 | **Level**: advanced(%%)  **Type**: user documentation | 
              
                    | 103 | 103 |  | 
              
                    | 104 | 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 | 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 |  | - |