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2	2
3	3	* ((( ==== **[[Beginner >>||anchor = "HBeginner-1"]]** ==== )))
4	4
5		-* ((( ==== **[[Intermediate >>||anchor = "HIntermediate-1"]]** ==== )))
6		-
7		-* ((( ==== **[[Advanced >>||anchor = "HAdvanced-1"]]** ==== )))
8		-
9	9	=== **Beginner** ===
10	10
11	11	=== [[Creating a simple cell optimisation>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/simplecell/simplecell.ipynb||rel=" noopener noreferrer" target="_blank"]] ===
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18	18	**Level**: beginner(%%) **Type**: interactive tutorial
19	19
20	20	This notebook will explain how to optimise a model using the covariance matrix adaptation (CMA) optimisation strategy. BluePyOpt includes two flavors of CMA: a single objective one and a hybrid single/multi objective one.
21		-=== [[Optimising synaptic parameters>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/expsyn/ExpSyn.ipynb||rel=" noopener noreferrer" target="_blank"]] ===
22	22
23		-**Level**: beginner(%%) **Type**: interactive tutorial
24		-
25		-This notebook shows how the parameters of a NEURON point process (in this case a synapse), can be optimised using BluePyOpt.
26		-=== **Intermediate** ===
27		-
28		-=== [[Creating an optimisation with meta parameters>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/metaparameters/metaparameters.ipynb||rel=" noopener noreferrer" target="_blank"]] ===
29		-
30		-**Level**: intermediate(%%) **Type**: interactive tutorial
31		-
32		-This notebook will explain how to set up an optimisation that uses metaparameters (parameters that control other parameters)
33		-=== [[Setup of a cell model with multi electrode simulation for local field potential recording>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/l5pc_lfpy/L5PC_LFPy.ipynb||rel=" noopener noreferrer" target="_blank"]] ===
34		-
35		-**Level**: intermediate(%%) **Type**: interactive tutorial
36		-
37		-This notebook will demonstrate how to instantiate a cell model and evaluator that include local field potential (LFP) computation and its recording using a simulated multi electrode array (MEA).
38		-=== [[Exporting a cell in the neuroml format and running it>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/neuroml/neuroml.ipynb||rel=" noopener noreferrer" target="_blank"]] ===
39		-
40		-**Level**: intermediate(%%) **Type**: interactive tutorial
41		-
42		-In this tutorial we will go over how to export a cell to neuroml, create a LEMS simulation able to run the neuroml cell and then how to run the simulation.
43		-=== [[Tsodyks-Markram model of short-term synaptic plasticity>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/tsodyksmarkramstp/tsodyksmarkramstp.ipynb||rel=" noopener noreferrer" target="_blank"]] ===
44		-
45		-**Level**: intermediate(%%) **Type**: interactive tutorial
46		-
47		-In this notebook we demonstrate how to fit the parameters of the Tsodyks-Markram model to a given in vitro somatic recording. The in vitro trace used here shows a typical L5TTPC-L5TTPC depressing connection, kindly provided by Rodrigo Perin (EPFL).
48		-=== [[Optimization of burst and tonic firing in thalamo-cortical neurons>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/thalamocortical-cell/thalamocortical-cell_opt.ipynb||rel=" noopener noreferrer" target="_blank"]] ===
49		-
50		-**Level**: intermediate(%%) **Type**: interactive tutorial
51		-
52		-In this tutorial we will go over how to set up the cell model and the cell evaluator, run an optimisation and how to analyse optimisation results.
53		-=== **Advanced** ===
54		-
55		-=== [[Optimisation of a Neocortical Layer 5 Pyramidal Cell>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/l5pc/L5PC.ipynb||rel=" noopener noreferrer" target="_blank"]] ===
56		-
57		-**Level**: advanced(%%) **Type**: interactive tutorial
58		-
59		-This notebook shows you how to optimise the maximal conductance of Neocortical Layer 5 Pyramidal Cell as used in Markram et al. 2015.
60		-=== [[Optimisation of a Neocortical Layer 5 Pyramidal Cell in Arbor>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/l5pc/L5PC_arbor.ipynb||rel=" noopener noreferrer" target="_blank"]] ===
61		-
62		-**Level**: advanced(%%) **Type**: interactive tutorial
63		-
64		-This notebook shows you how to optimise the maximal conductance of Neocortical Layer 5 Pyramidal Cell as used in Markram et al. 2015 using Arbor as the simulator.
65		-=== [[Simulating optimized cell models in Arbor and cross-validation with Neuron>>https://github.com/BlueBrain/BluePyOpt/blob/master/examples/l5pc/l5pc_validate_neuron_arbor.ipynb||rel=" noopener noreferrer" target="_blank"]] ===
66		-
67		-**Level**: advanced(%%) **Type**: interactive tutorial
68		-
69		-This notebook demonstrates how to run a simulation of a simple single compartmental cell with fixed/optimized parameters in Arbor. We follow the standard BluePyOpt flow of setting up an electrophysiological experiment and export the cell model to a mixed JSON/ACC-format. We then cross-validate voltage traces obtained with Arbor with those from a Neuron simulation.
70		-