TY - JOUR A2 - Baillet, Sylvain AU - Campi, C. AU - Pascarella, A. AU - Sorrentino, A. AU - Piana, M. PY - 2011 DA - 2011/03/06 TI - Highly Automated Dipole EStimation (HADES) SP - 982185 VL - 2011 AB - Automatic estimation of current dipoles from biomagnetic data isstill a problematic task. This is due not only to the ill-posedness ofthe inverse problem but also to two intrinsic difficulties introduced bythe dipolar model: the unknown number of sources and the nonlinearrelationship between the source locations and the data. Recently, wehave developed a new Bayesian approach, particle filtering, based ondynamical tracking of the dipole constellation. Contrary to manydipole-based methods, particle filtering does not assume stationarityof the source configuration: the number of dipoles and their positionsare estimated and updated dynamically during the course of the MEGsequence. We have now developed a Matlab-based graphical user interface,which allows nonexpert users to do automatic dipole estimationfrom MEG data with particle filtering. In the present paper, we describethe main features of the software and show the analysis of botha synthetic data set and an experimental dataset. SN - 1687-5265 UR - https://doi.org/10.1155/2011/982185 DO - 10.1155/2011/982185 JF - Computational Intelligence and Neuroscience PB - Hindawi Publishing Corporation KW - ER -