Assessing the relevance of fMRI-based prior in the EEG inverse problem: a bayesian model comparison approach
| العنوان: | Assessing the relevance of fMRI-based prior in the EEG inverse problem: a bayesian model comparison approach |
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| المؤلفون: | Jean Daunizeau, Jérémie Mattout, Jean-Marc Lina, Diego Clonda, H. Benali, B. Goulard, M. Pelegrini-Issac, Christophe Grova, Guillaume Marrelec |
| المساهمون: | Laboratoire d'Imagerie Biomédicale (LIB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS) |
| المصدر: | IEEE Transactions on Signal Processing IEEE Transactions on Signal Processing, Institute of Electrical and Electronics Engineers, 2005, 53 (9), pp.3461-3472. ⟨10.1109/TSP.2005.853220⟩ |
| بيانات النشر: | HAL CCSD, 2005. |
| سنة النشر: | 2005 |
| مصطلحات موضوعية: | Computer science, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Bayesian probability, Inference, Bayesian inference, Machine learning, computer.software_genre, 050105 experimental psychology, 03 medical and health sciences, 0302 clinical medicine, Functional neuroimaging, Prior probability, medicine, 0501 psychology and cognitive sciences, Electrical and Electronic Engineering, ComputingMilieux_MISCELLANEOUS, medicine.diagnostic_test, business.industry, [SCCO.NEUR]Cognitive science/Neuroscience, 05 social sciences, Bayes factor, Human brain, Magnetoencephalography, Inverse problem, Functional imaging, medicine.anatomical_structure, Signal Processing, Artificial intelligence, Functional magnetic resonance imaging, business, computer, 030217 neurology & neurosurgery |
| الوصف: | Characterizing the cortical activity from electro- and magneto-encephalography (EEG/MEG) data requires solving an ill-posed inverse problem that does not admit a unique solution. As a consequence, the use of functional neuroimaging, for instance, functional Magnetic Resonance Imaging (fMRI), constitutes an appealing way of constraining the solution. However, the match between bioelectric and metabolic activities is desirable but not assured. Therefore, the introduction of spatial priors derived from other functional modalities in the EEG/MEG inverse problem should be considered with caution. In this paper, we propose a Bayesian characterization of the relevance of fMRI-derived prior information regarding the EEG/MEG data. This is done by quantifying the adequacy of this prior to the data, compared with that obtained using an noninformative prior instead. This quantitative comparison, using the so-called Bayes factor, allows us to decide whether the informative prior should (or not) be included in the inverse solution. We validate our approach using extensive simulations, where fMRI-derived priors are built as perturbed versions of the simulated EEG sources. Moreover, we show how this inference framework can be generalized to optimize the way we should incorporate the informative prior. |
| اللغة: | English |
| تدمد: | 1053-587X |
| DOI: | 10.1109/TSP.2005.853220⟩ |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ac2dc7266f83919b7b4ba5ab35bd9f71 https://hal.archives-ouvertes.fr/hal-03163997 |
| Rights: | CLOSED |
| رقم الانضمام: | edsair.doi.dedup.....ac2dc7266f83919b7b4ba5ab35bd9f71 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 1053587X |
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| DOI: | 10.1109/TSP.2005.853220⟩ |