activity
20172020
most citedBayesian multi--dipole localization and uncertainty quantification from simultaneous EEG and MEG recordings

2 citations · 2 across the 2 of their papers we have counts for

collaborators

5 papers

math.NA2020

The role of spectral complexity in connectivity estimation

Elisabetta Vallarino, Michele Piana, Alberto Sorrentino +1

The study of functional connectivity from magnetoecenphalographic (MEG) data consists in quantifying the statistical dependencies among time series describing the activity of diffe…

stat.AP2020

Where Bayes tweaks Gauss: Conditionally Gaussian priors for stable multi-dipole estimation

Alessandro Viani, Gianvittorio Luria, Harald Bornfleth +1

We present a very simple yet powerful generalization of a previously described model and algorithm for estimation of multiple dipoles from magneto/electro-encephalographic data. Sp…

math.NA2019

On the two-step estimation of the cross--power spectrum for dynamical inverse problems

Elisabetta Vallarino, Sara Sommariva, Michele Piana +1

We consider the problem of reconstructing the cross--power spectrum of an unobservable multivariate stochatic process from indirect measurements of a second multivariate stochastic…

q-bio.QM2018

Bayesian Multi--Dipole Modeling in the Frequency Domain

Gianvittorio Luria, Dunja Duran, Elisa Visani +6

Background: Magneto- and Electro-encephalography record the electromagnetic field generated by neural currents with high temporal frequency and good spatial resolution, and are the…

q-bio.QM20172 cited

Bayesian multi--dipole localization and uncertainty quantification from simultaneous EEG and MEG recordings

Filippo Rossi, Gianvittorio Luria, Sara Sommariva +1

We deal with estimation of multiple dipoles from combined MEG and EEG time--series. We use a sequential Monte Carlo algorithm to characterize the posterior distribution of the numb…