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Abstract #3385

Optimizing EEG source reconstruction with concurrent fMRI-derived spatial priors

Rodolfo Abreu1, Júlia F. Soares1, Sónia Batista2,3, Lívia Sousa2,3, Miguel Castelo-Branco1,3, and João Valente Duarte1,3
1Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute for Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal, 2Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal, 3Faculty of Medicine, University of Coimbra, Coimbra, Portugal

There is no consensus regarding the optimal EEG source reconstruction algorithm, nor a systematic comparison between sets of fMRI-derived spatial priors to be included in the inversion models. We compared four inversion algorithms, each with three sets of fMRI-derived spatial priors consisting of task activation maps, resting-state networks and, for the first time, dynamic functional connectivity states. We found that combining a beamformer with these priors improves the reconstruction quality, especially in terms of the overlap with task-related brain regions of interest and RSN templates. Our results may guide more informatively the selection of the optimal EEG source reconstruction approach.

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