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76	76	This tutorial will teach you how to build an arbor.recipe., an arbor.context and
77	77	create an arbor.simulation. The running the simulation and visualising the results.
	78	+=== [[Spike Timing-dependent Plasticity Curve>>https://docs.arbor-sim.org/en/stable/tutorial/calcium_stdp_curve.html||rel=" noopener noreferrer" target="_blank"]] ===
78	78
	80	+**Level**: advanced(%%) **Type**: user documentation
	81	+
	82	+We will focus on implementing a stochastic differential equation (SDE) in Arbor’s NMODL dialect and examine the mechanism code in the Arbor repository.
	83	+=== [[Two cells connected via a gap junction>>https://docs.arbor-sim.org/en/stable/tutorial/network_two_cells_gap_junctions.html||rel=" noopener noreferrer" target="_blank"]] ===
	84	+
	85	+**Level**: advanced(%%) **Type**: user documentation
	86	+
	87	+You will be able to learn how to create a simulation recipe for two cells.
	88	+How to place probes, run the simulation and extract the results.
	89	+Finally you will able to add a gap junction connection.
	90	+=== [[Brunel network>>https://docs.arbor-sim.org/en/latest/tutorial/brunel.html||rel=" noopener noreferrer" target="_blank"]] ===
	91	+
	92	+**Level**: advanced(%%) **Type**: user documentation
	93	+
	94	+In this tutorial we will follow the description of the ring network to build our recipe. Finally you will be able to build the network, run the simulation, and record the spikes. If interested you can go on to learn how to visualise the raster plot of the entire network and a few selected cells, and the peristimulus time histogram (PSTH) of the entire network.
	95	+=== [[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"]] ===
	96	+
	97	+**Level**: advanced(%%) **Type**: interactive tutorial
	98	+
	99	+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.
	100	+=== [[Extracellular signals (LFPykit)>>https://docs.arbor-sim.org/en/stable/tutorial/probe_lfpykit.html||rel=" noopener noreferrer" target="_blank"]] ===
	101	+
	102	+**Level**: advanced(%%) **Type**: user documentation
	103	+
	104	+This tutorial will show you how to record transmembrane currents using arbor.cable_probe_total_current_cell and how to record stimulus currents using arbor.cable_probe_stimulus_current_cell. Later we will be using the arbor.place_pwlin API to map recorded transmembrane currents to extracellular potentials by deriving Arbor specific classes from LFPykit’s lfpykit.LineSourcePotential and lfpykit.CellGeometry.
	105	+=== [[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"]] ===
	106	+
	107	+**Level**: advanced(%%) **Type**: interactive tutorial
	108	+
	109	+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.
	110	+