Orateur
Description
We present a theoretical and numerical framework for performing source lo-
calisation and cortical mapping using EEG data with various source models.
This framework is built on the idea that the problems of source localisation and
cortical mapping are different aspects of the same inverse problem rather than
independent inverse problems. This approach promises to improve numerical ac-
curacy and to provide context to the numerical results obtained both for source
localisation and cortical mapping. We provide theoretical results which allow
the sources to be modelled as vector-fields from a wide range of functional and
distributional spaces. The study of the various source models in motivated by a
need to take advantage of advances in medical imaging such as diffusion MRI.
This opens the possibility to restrict the support of the sources to anatomical
structures of the brain that we now have access to thanks to these advances.
We present numerical results to demonstrate the proposed alternating minimi-
sation algorithm for solving the source location and cortical mapping problems
simultaneously. Such an alternating minimisation procedure provides practical
advantages especially in computer memory usage.
