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153	153	**Level**: advanced(%%) **Type**: user documentation
154	154
155	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"]] ===
156	156
	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	+=== [[Using NEURON's Optimization Tools – Tutorial 2 : Fitting a model to data>>https://neuron.yale.edu/neuron/static/docs/optimiz/model/outline.html||rel=" noopener noreferrer" target="_blank"]] ===
	196	+
	197	+**Level**: advanced(%%) **Type**: user documentation
	198	+
	199	+We will go over how to create an "unoptimized" model, set up a current clamp experiment on this model, configure a MultipleRunFitter to do a "run fitness" optimization, load the Experimental Data into the iclamp Run Fitness Generator, specify the parameters that will be adjusted and finally perform the optimization.
	200	+=== [[Reaction-Diffusion – Hodgkin-Huxley using rxd>>https://neuron.yale.edu/neuron/docs/hodgkin-huxley-using-rxd||rel=" noopener noreferrer" target="_blank"]] ===
	201	+
	202	+**Level**: advanced(%%) **Type**: interactive tutorial
	203	+
	204	+In this tutorial you will learn how to set the proper parameters for the Hodgkin–Huxley model in NEURON.
	205	+=== [[Using the CellBuilder – Creating a stylised ("stick-figure") model cell>>https://neuron.yale.edu/neuron/static/docs/cbtut/stylized/outline.html||rel=" noopener noreferrer" target="_blank"]] ===
	206	+
	207	+**Level**: advanced(%%) **Type**: -
	208	+
	209	+Learn how to build an extremely simplified model of a pyramidal cell.
	210	+=== [[Ball and Stick model part 2>>https://neuron.yale.edu/neuron/docs/ball-and-stick-model-part-2||rel=" noopener noreferrer" target="_blank"]] ===
	211	+
	212	+**Level**: advanced(%%) **Type**: user documentation
	213	+
	214	+=== [[Reaction-Diffusion Example – Circadian rhythm>>https://neuron.yale.edu/neuron/docs/example-circadian-rhythm||rel=" noopener noreferrer" target="_blank"]] ===
	215	+
	216	+**Level**: advanced(%%) **Type**: user documentation
	217	+
	218	+Here we develop a NEURON implementation of the Leloup-Goldbeter model for circadian rhythms in Drosophila. In this example NEURON's h library and its standard run system are being used as well as matplotlib to plot concentrations of circadian proteins over time.
	219	+=== [[Segmenting a simulation of a model cell – 3. Run a segmented simulation and save its results>>https://neuron.yale.edu/neuron/docs/3-run-segmented-simulation-and-save-its-results||rel=" noopener noreferrer" target="_blank"]] ===
	220	+
	221	+**Level**: advanced(%%) **Type**: user documentation
	222	+
	223	+=== [[ModelView: Compact display of parameters for NEURON models.>>https://neuron.yale.edu/neuron/static/papers/mview/modelviewhbp2004.html||rel=" noopener noreferrer" target="_blank"]] ===
	224	+
	225	+**Level**: advanced(%%) **Type**: user documentation
	226	+
	227	+This example demonstrates how ModelView can explore a NEURON model.
	228	+=== [[Segmenting a simulation of a model network – 3. Run a segmented simulation and save its results>>https://neuron.yale.edu/neuron/docs/3-run-segmented-simulation-and-save-its-results-0||rel=" noopener noreferrer" target="_blank"]] ===
	229	+
	230	+**Level**: advanced(%%) **Type**: user documentation
	231	+
	232	+=== [[Segmenting a simulation of a model network – 4. Reconstitute and verify the "complete" simulation results>>https://neuron.yale.edu/neuron/docs/4-reconstitute-and-verify-complete-simulation-results-0||rel=" noopener noreferrer" target="_blank"]] ===
	233	+
	234	+**Level**: advanced(%%) **Type**: user documentation
	235	+
	236	+=== [[Using NEURON's Optimization Tools – Tutorial 1 : Fitting a function to data>>https://neuron.yale.edu/neuron/static/docs/optimiz/func/outline.html||rel=" noopener noreferrer" target="_blank"]] ===
	237	+
	238	+**Level**: advanced(%%) **Type**: user documentation
	239	+
	240	+We will look into how to bring up a Multiple Run Fitter, load the Experimental Data into the Multiple Run Fitter, specify the function we want to optimize, specify the parameters that will be adjusted, specify the criteria we want the function to satisfy and finally perform the optimization.
	241	+=== [[Ball and Stick model part 4>>https://neuron.yale.edu/neuron/docs/ball-and-stick-model-part-4||rel=" noopener noreferrer" target="_blank"]] ===
	242	+
	243	+**Level**: advanced(%%) **Type**: user documentation
	244	+
	245	+