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282	282	**Level**: advanced(%%) **Type**: interactive tutorial
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284	284	We use the CellBuilder to specify the spatial grid (nseg) and biophysical properties of a model based on detailed morphometric data.
	285	+=== [[Using NEURON's Optimization Tools>>https://neuron.yale.edu/neuron/static/docs/optimiz/main.html||rel=" noopener noreferrer" target="_blank"]] ===
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	287	+**Level**: advanced(%%) **Type**: user documentation
	288	+
	289	+This collection of tutorials shows how to use NEURON's optimization tools. Before working through these tutorials, most readers should probably examine the on-line "Introduction to Optimization" http://neos-guide.org/content/optimization-introduction.
	290	+=== [[Ball and Stick model part 1>>https://neuron.yale.edu/neuron/docs/ball-and-stick-model-part-1||rel=" noopener noreferrer" target="_blank"]] ===
	291	+
	292	+**Level**: advanced(%%) **Type**: user documentation
	293	+
	294	+=== [[Reaction-Diffusion – Extracellular Diffusion>>https://neuron.yale.edu/neuron/docs/extracellular-diffusion||rel=" noopener noreferrer" target="_blank"]] ===
	295	+
	296	+**Level**: advanced(%%) **Type**: interactive tutorial
	297	+
	298	+We have expanded the capabilities the NEURON reaction diffusion module to support a macroscopic model of the extracellular space. Here is brief a tutorial that provides an overview of the python interface.
	299	+=== [[Segmenting a simulation of a model cell – 4. Reconstitute and verify the "complete" simulation results>>https://neuron.yale.edu/neuron/docs/4-reconstitute-and-verify-complete-simulation-results||rel=" noopener noreferrer" target="_blank"]] ===
	300	+
	301	+**Level**: advanced(%%) **Type**: user documentation
	302	+
	303	+=== [[Using the Network Builder – Tutorial 2: Making Hybrid Nets>>https://neuron.yale.edu/neuron/static/docs/netbuild/hybrid/outline.html||rel=" noopener noreferrer" target="_blank"]] ===
	304	+
	305	+**Level**: advanced(%%) **Type**: interactive tutorial
	306	+
	307	+In this tutorial you will learn how to define the types of cells, create each cell in the network and connect the cells (this includes specifying parameters such as delays and weights) . We'll use a pair of biophysical models for M and R, and a NetStim artificial neuron will provide the excitatory drive to M.
	308	+In the end we will run a simulation and plot the input and output spike trains.
	309	+=== [[Reaction-Diffusion Example – mGluR example>>https://neuron.yale.edu/neuron/docs/mglur-example||rel=" noopener noreferrer" target="_blank"]] ===
	310	+
	311	+**Level**: advanced(%%) **Type**: user documentation
	312	+
	313	+This examples, will show how to use rxd to handle the kinetics of a mGLUR.
	314	+