Academic Software Toolboxes for the Analysis of MEG Data

Sylvain Baillet (1) , Richard Leahy (2) , François Tadel (2) , John C. Mosher (3) , Arnaud Delorme (4, 5) , Scott Makeig (5) , Robert Oostenveld (6) , Matti Hämäläinen (7) , Sarang S. Dalal (8) , J. Zumer (9) , Maureen Clerc (10) , Carsten Wolters (11) , Stefan J. Kiebel (12) , Ole Jensen (6)

1 Department of Neurology [Milwaukee]
2 USC - University of Southern California
3 Cleveland Clinic
4 CERCO - Centre de recherche cerveau et cognition
5 Swartz Center for Computational Neuroscience
6 Donders Institute for Brain, Cognition and Behaviour
7 Athinoula A. Martinos Center for Biomedical Imaging
8 Dynamique Cérébrale et Cognition
9 School of Physics and Astronomy [Nottingham]
10 ATHENA - Computational Imaging of the Central Nervous System
11 Institute for Biomagnetism and Biosignal Analysis
12 IMPNSC - Max Planck Institute for Human Cognitive and Brain Sciences [Leipzig]

Free MEG and EEG data analysis software packages springing from academic research are now widely used in published work. These toolboxes and applications are typically developed by or in close contact with researchers addressing cognitive or clinical neuroscience questions. Thus they often contain the latest methodological developments from the research community. It is therefore vital to educate MEG researchers and make them aware of the new possibilities offered by these toolboxes. The aim of this paper is to illustrate the characteristics and advantages of the various toolboxes to users and developers alike. We present each toolbox with their key features and target audience.

Mots clés: MEG; source analysis; data analysis; imaging; mapping; connectivity; forward modeling

Domaines: Informatique

Sylvain Baillet, Richard Leahy, François Tadel, John C. Mosher, Arnaud Delorme, et al.. Academic Software Toolboxes for the Analysis of MEG Data. Biomag 2010, S. Supek, May 2010, Dubrovnik, Croatia. pp.101-104. ⟨inria-00497071⟩