In Knösche, T. R. & Haueisen, J., editors, *EEG/MEG Source Reconstruction: Textbook for Electro-and Magnetoencephalography*, pages 229–354. Springer International Publishing, Cham, 2022.

Paper doi abstract bibtex

Paper doi abstract bibtex

This chapter treats the solution of the neuroelectromagnetic inverse problem (NIP), that is, the reconstruction of the primary current density underlying EEG/MEG measurements, given a particular source model (► Chap. 4) and forward model (► Chap. 5). We will present a theoretical framework of the problem, centered on Bayes’ theorem. Different approaches to the NIP will be classified according to their underlying source model as well as the applied priors and described in greater detail. Specifically, you will learn about focal source reconstruction (i.e., dipole fit methods), distributed source reconstruction (i.e., minimum norm methods), spatial filters and scanning methods, and dynamic source reconstruction.

@incollection{knosche_inverse_2022, address = {Cham}, title = {Inverse {Methods}}, isbn = {978-3-030-74918-7}, url = {https://doi.org/10.1007/978-3-030-74918-7_6}, abstract = {This chapter treats the solution of the neuroelectromagnetic inverse problem (NIP), that is, the reconstruction of the primary current density underlying EEG/MEG measurements, given a particular source model (► Chap. 4) and forward model (► Chap. 5). We will present a theoretical framework of the problem, centered on Bayes’ theorem. Different approaches to the NIP will be classified according to their underlying source model as well as the applied priors and described in greater detail. Specifically, you will learn about focal source reconstruction (i.e., dipole fit methods), distributed source reconstruction (i.e., minimum norm methods), spatial filters and scanning methods, and dynamic source reconstruction.}, language = {en}, urldate = {2022-11-03}, booktitle = {{EEG}/{MEG} {Source} {Reconstruction}: {Textbook} for {Electro}-and {Magnetoencephalography}}, publisher = {Springer International Publishing}, author = {Knösche, Thomas R. and Haueisen, Jens}, editor = {Knösche, Thomas R. and Haueisen, Jens}, year = {2022}, doi = {10.1007/978-3-030-74918-7_6}, pages = {229--354}, }

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