| ... | ... | @@ -87,4 +87,42 @@ | 
              
                    | 87 | 87 | 2. Grouping sections with shared properties into subsets. | 
              
                    | 88 | 88 | 3. Assigning geometric properties (length, diameter) to subsets or individual sections, and specifying a discretization strategy (i.e. how to set nseg). | 
              
                    | 89 | 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"]] === | 
              
                    | 90 | 90 |  | 
              
                    |  | 92 | +**Level**: advanced(%%)  **Type**: user documentation | 
              
                    |  | 93 | + | 
              
                    |  | 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"]] === | 
              
                    |  | 96 | + | 
              
                    |  | 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 | + |