Abstract
Little has been done yet to study the synchronization properties of the sources estimated from the MEG/EEG inverse problem, despite the growing interest in the role of phase relations in brain functions. In order to achieve this aim, we propose a novel approach to the MEG/EEG inverse problem based on some regularization using spectral priors: The MEG/EEG raw data are filtered in a frequency band of interest and blurred with some specific “regularization noise” prior to the inversion process. This formalism uses non quadratic regularization and a deterministic optimization algorithm. We proceed to Monte Carlo simulations using the chaotic Rössler oscillators to model the neural generators. Our results demonstate that it is possible to reveal some phase-locking between brain sources with great accuracy following the computation of the inverse problem based on scalp MEG/EEG measurements.
Acknowledgements
The authors wish to thank J.-F. Mangin for the cortical surface segmentation algorithms, M. Le Van Quyen and J. Martinerie for helpful discussions on the chaotic Rössler oscillators and S. Baillet for thoroughful reading.
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David, O., Garnero, L., Varela, F.J. (2001). A New Approach to the MEG/EEG Inverse Problem for the Recovery of Cortical Phase-Synchrony. In: Insana, M.F., Leahy, R.M. (eds) Information Processing in Medical Imaging. IPMI 2001. Lecture Notes in Computer Science, vol 2082. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45729-1_29
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DOI: https://doi.org/10.1007/3-540-45729-1_29
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