The SESAMEEG package: a probabilistic tool for source localization and uncertainty quantification in M/EEG.

Source localization from M/EEG data is a fundamental step in many analysis pipelines, including those aiming at clinical applications such as the pre-surgical evaluation in epilepsy. Among the many available source localization algorithms, SESAME (SEquential SemiAnalytic Montecarlo Estimator) is a Bayesian method that distinguishes itself for several good reasons: it is highly accurate in localizing focal sources with comparably little sensitivity to input parameters; it allows the quantification of the uncertainty of the reconstructed source(s); it accepts user-defined high- and low-probability search regions in input; it can localize the generators of neural oscillations in the frequency domain. Both a Python and a MATLAB implementation of SESAME are available as open-source packages under the name of SESAMEEG and are well integrated with the main software packages used by the M/EEG community; moreover, the algorithm is part of the commercial software BESA Research (from version 7.

Electroclinical Features of Epilepsy in Kleefstra Syndrome.

Background: Kleefstra syndrome (KS) or 9q34.3 microdeletion syndrome (OMIM #610253) is a rare genetic condition featuring intellectual disability, hypotonia, and dysmorphic facial features. Autism spectrum disorder, severe language impairment, and sleep disorders have also been described.

On the role of REM sleep microstructure in suppressing interictal spikes in Electrical Status Epilepticus during Sleep.

Objective: Non-Rapid Eye Movement (NREM) sleep promotes the spread and propagation of Interictal Epileptiform Discharges (IEDs), while IEDs are suppressed during REM. Recently, it has been shown that the inhibitory effect on epileptic activity is mostly exerted by the phasic REM (PREM) microstate. This study aims at assessing if this holds true even in the extreme condition of IEDs activation during sleep represented by Electrical Status Epilepticus during Sleep (ESES).

Focal status and acute encephalopathy in a 13-year-old boy with de novo DNM1L mutation: Video-polygraphic pattern and clues for differential diagnosis.

Background: Pathogenic variants in the dynamin 1 like gene are related to abnormal mitochondrial dynamics and distributions and are associated to variable clinical phenotypes. A few patients harboring the p.Arg403Cys missense variant appears to be different from the classical, more severe phenotypes, showing sudden onset of drug resistant seizures after a previously normal or slightly delayed development.

Towards the Automatic Localization of the Irritative Zone Through Magnetic Source Imaging.

The present work aims at validating a Bayesian multi-dipole modeling algorithm (SESAME) in the clinical scenario consisting of localizing the generators of single interictal epileptiform discharges from resting state magnetoencephalographic recordings. We use the results of Equivalent Current Dipole fitting, performed by an expert user, as a benchmark, and compare the results of SESAME with those of two widely used source localization methods, RAP-MUSIC and wMNE. In addition, we investigate the relation between post-surgical outcome and concordance of the surgical plan with the cerebral lobes singled out by the methods.

Bayesian multi-dipole modelling in the frequency domain.

Background: Magneto- and Electro-encephalography record the electromagnetic field generated by neural currents with high temporal frequency and good spatial resolution, and are therefore well suited for source localization in the time and in the frequency domain. In particular, localization of the generators of neural oscillations is very important in the study of cognitive processes in the healthy and in the pathological brain.

New Method: We introduce the use of a Bayesian multi-dipole localization method in the frequency domain.