= Simulations =
''Author: Francois Tadel''

This tutorial addresses everything that can be called "simulation" in Brainstorm: simulation of simple signals, simulation of full source maps from a few scouts, simulation of MEG/EEG recordings from source maps (real or synthetic). Its goal is to group all the information that was previously spread across multiple tutorials and forum posts, and difficult to access.

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== Simulate signals ==
You have no data in your database. Some process in the '''Simulate''' menu can generate signals and save them as new files in the database. Because you start from nothing, the Process1 list needs to be empty. Click on Run and try the following processes.

=== Simulate generic signals ===
This process allows to define a set of signals with Matlab code and save it in a Brainstorm file. With the text box, you can write a free-form piece of code, which will be evaluated with the function '''eval'''(). This code must at least define the variable '''Data''' [Nsignals x Ntime], based on in the input time vector '''t''' (defined automatically by the process from the number of time points and the sampling frequency). The more rows you add to the Data matrix, the more signals you will have in your file. The example below creates three signals. Another example is available in the tutorial [[https://neuroimage.usc.edu/brainstorm/Tutorials/TimeFrequency#Simulation|Time-frequency]].

{{attachment:simulate_generic.gif}}

=== Simulate PAC signals ===
This process generates synthesized data containing cross-frequency phase-amplitude coupling. It is fully documented in the tutorial [[https://neuroimage.usc.edu/brainstorm/Tutorials/TutPac#Simulate_signals|Phase-amplitude coupling: Method]].

{{attachment:simulate_pac.gif}}

== Generate full source maps from scout signals ==
== Simulate MEG/EEG recordings from real sources ==
After estimating the sources from real MEG/EEG recordings with the minimum norm method, you can simulate recordings from the model. This is done simply by multiplying the source time series with the forward model:

{{{
EEG_sim [Nelec x Ntime] = Forward_model [Nelec x Nsources] * MN_sources [Nsources x Ntime]
}}}
To simulate MEG/EEG recordings from a minimum norm source model: right-click on the source file, then select the menu '''Model evaluation > Simulate recordings'''. This can be useful for evaluating the quality of the model. The process is documented in the tutorial [[https://neuroimage.usc.edu/brainstorm/Tutorials/SourceEstimation#Model_evaluation|Source estimation]].

{{attachment:model_eval_menu.gif}}

{{attachment:model_eval_res.gif}}

== Simulate MEG/EEG recordings from simulated dipoles ==
These examples are based on the introduction tutorials, but can easily be transposed to any study. The inputs you need to provide to the process depend on the type of orientation constrains

=== Constrained ===
=== Unconstrained ===
https://neuroimage.usc.edu/brainstorm/Tutorials/TutVolSource#Volume_scouts

== Additional documentation ==
A great simulation article was published by Prof. Debener's neuropsychology lab in Oldenburg. It uses Brainstorm to evaluate and improve the design of ear-EEG devices. All the Matlab/Brainstorm scripts used in this study are available on [[https://figshare.com/articles/software/Matlab-code_for_simulation_of_dipole_sources/11907801|figshare]], together with some videos illustrating the simulations that were done.

Meiser A, Tadel F, Debener S, Bleichner MG<<BR>>[[https://link.springer.com/article/10.1007/s10548-020-00793-2|The Sensitivity of Ear-EEG: Evaluating the Source-Sensor Relationship Using Forward Modeling]]<<BR>>'''Brain Topography''', Aug 2020

{{attachment:meiser.gif}}