Dynamical MEG source modeling with multi‐target Bayesian filtering A Sorrentino, L Parkkonen, A Pascarella, C Campi, M Piana Human brain mapping 30 (6), 1911-1921, 2009 | 63 | 2009 |
Simultaneous human intracerebral stimulation and HD-EEG, ground-truth for source localization methods E Mikulan, S Russo, S Parmigiani, S Sarasso, FM Zauli, A Rubino, ... Scientific data 7 (1), 127, 2020 | 51* | 2020 |
Forward simulation and inverse dipole localization with the lowest order Raviart—Thomas elements for electroencephalography S Pursiainen, A Sorrentino, C Campi, M Piana Inverse Problems 27 (4), 045003, 2011 | 44 | 2011 |
A Rao–Blackwellized particle filter for magnetoencephalography C Campi, A Pascarella, A Sorrentino, M Piana Inverse Problems 24 (2), 025023, 2008 | 43 | 2008 |
Sequential Monte Carlo samplers for semi-linear inverse problems and application to magnetoencephalography S Sommariva, A Sorrentino Inverse Problems 30 (11), 114020, 2014 | 36 | 2014 |
Bayesian multi-dipole modelling of a single topography in MEG by adaptive sequential Monte Carlo samplers A Sorrentino, G Luria, R Aramini Inverse Problems 30 (4), 045010, 2014 | 30 | 2014 |
A Simplex Method for the Calibration of a MEG Device V Vivaldi, S Sommariva, A Sorrentino Communications in Applied and Industrial Mathematics 10, 35-46, 2019 | 29 | 2019 |
Dynamic filtering of static dipoles in magnetoencephalography A Sorrentino, AM Johansen, JAD Aston, TE Nichols, WS Kendall The annals of applied statistics, 955-988, 2013 | 27 | 2013 |
Highly automated dipole estimation (HADES) C Campi, A Pascarella, A Sorrentino, M Piana Computational intelligence and neuroscience 2011 (1), 982185, 2011 | 27 | 2011 |
Particle filters: a new method for reconstructing multiple current dipoles from MEG data A Sorrentino, L Parkkonen, M Piana International congress series 1300, 173-176, 2007 | 26 | 2007 |
A comparative study of the robustness of frequency-domain connectivity measures to finite data length S Sommariva, A Sorrentino, M Piana, V Pizzella, L Marzetti Brain topography 32, 675-695, 2019 | 21 | 2019 |
Modulation of brain and behavioural responses to cognitive visual stimuli with varying signal-to-noise ratios A Sorrentino, L Parkkonen, M Piana, AM Massone, L Narici, S Carozzo, ... Clinical Neurophysiology 117 (5), 1098-1105, 2006 | 18 | 2006 |
A Bayesian parametric approach to the retrieval of the atmospheric number size distribution from lidar data A Sorrentino, A Sannino, N Spinelli, M Piana, A Boselli, V Tontodonato, ... Atmospheric Measurement Techniques 15 (1), 149-164, 2022 | 13 | 2022 |
Inverse Modeling for MEG/EEG data A Sorrentino, M Piana Mathematical and Theoretical Neuroscience: Cell, Network and Data Analysis …, 2017 | 13 | 2017 |
Statistical approaches to the inverse problem A Pascarella, A Sorrentino Magnetoencephalography, 93-112, 2011 | 13 | 2011 |
Particle filtering, beamforming and multiple signal classification for the analysis of magnetoencephalography time series: a comparison of algorithms A Pascarella, A Sorrentino, C Campi, M Piana Inverse Problems and Imaging 4 (1), 169-170, 2010 | 13 | 2010 |
Identification of multiple hard X-ray sources in solar flares: a Bayesian analysis of the 2002 February 20 event F Sciacchitano, A Sorrentino, AG Emslie, AM Massone, M Piana The Astrophysical Journal 862 (1), 68, 2018 | 12 | 2018 |
Expectation maximization and the retrieval of the atmospheric extinction coefficients by inversion of Raman lidar data S Garbarino, A Sorrentino, AM Massone, A Sannino, A Boselli, X Wang, ... Optics Express 24 (19), 21497-21511, 2016 | 12 | 2016 |
Bayesian smoothing of dipoles in magneto-/electroencephalography V Vivaldi, A Sorrentino Inverse Problems 32 (4), 045007, 2016 | 11 | 2016 |
An in–vivo validation of ESI methods with focal sources A Pascarella, E Mikulan, F Sciacchitano, S Sarasso, A Rubino, I Sartori, ... NeuroImage 277, 120219, 2023 | 10 | 2023 |