SESAMEEG

This is a MATLAB implementation of the Bayesian multi–dipole localization method SESAME [1] (SEquential Semi-Analytic Montecarlo Estimator) for the automatic estimation of brain source currents from MEEG data, either in the time domain and in the frequency domain [2].

A mathematical description of the algorithm is available in the documentation.

The algorithm takes in input a sourcespace, a leadfield and a data time series, and outputs a posterior probability map for source locations, the estimated number of dipoles, their locations and their amplitudes.

script_run_SESAME contains an example script that launches the algorithm inverse_SESAME() contains the Monte Carlo algorithm inverse_SESAME_viewer() contains code for visualizing the output.

Bug reports

Use the github issue tracker to report bugs.

Authors of the code

Alberto Sorrentino <sorrentino@dima.unige.it>

Alessandro Viani <viani@dima.unige.it>

Gianvittorio Luria <luria@dima.unige.it>,

Sara Sommariva <sommariva@dima.unige.it>,

Cite our work

If you use this code in your project, please consider citing our work:

[1]

19. Sommariva and A. Sorrentino, Sequential Monte Carlo samplers for semi-linear inverse problems and application to Magnetoencephalography. Inverse Problems, 30 114020 (2014).

[2]

7. Luria et al., Bayesian multi-dipole modelling in the frequency domain. J. Neurosci. Meth., 312 (2019) 27–36.