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79	79	**Level**: advanced(%%) **Type**: user documentation
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	81	+=== [[Using the CellBuilder – Introduction>>https://neuron.yale.edu/neuron/static/docs/cbtut/main.html||rel=" noopener noreferrer" target="_blank"]] ===
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	83	+**Level**: advanced(%%) **Type**: interactive tutorial
	84	+
	85	+The following tutorials show how to use the CellBuilder, a powerful and convenient tool for constructing and managing models of individual neurons. It breaks the job of model specification into a sequence of tasks:
	86	+1. Setting up model topology (branching pattern).
	87	+2. Grouping sections with shared properties into subsets.
	88	+3. Assigning geometric properties (length, diameter) to subsets or individual sections, and specifying a discretization strategy (i.e. how to set nseg).
	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"]] ===
	91	+
	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	+=== [[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	+