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Abstract #3937

Reconstructing the BOLD-fMRI signal at the facial expression processing network from simultaneous EEG-derived predictors 

MARCO SIMOES1, Rodolfo Abreu2, Bruno Direito2, Alexandre Sayal2, Joao Castelhano2, Paulo Carvalho3, and Miguel Castelo-Branco2
1CIBIT, Coimbra Institute for Biomedical Imaging and Translational Research, Faculty of Medicine, University of Coimbra, COIMBRA, Portugal, 2CIBIT, University of Coimbra, Coimbra, Portugal, 3CISUC, University of Coimbra, Coimbra, Portugal

fMRI is the neuroimage modality of choice when considering localized neurofeedback applications. However, the high costs and inflexibility of MRI setups limit their widespread application, motivating their transfer to EEG setups by reconstructing the BOLD-fMRI signal at the target regions using EEG only. Here, we systematically investigated the extent at which the BOLD-fMRI signal at the facial expressions processing network could be reconstructed from simultaneously recorded EEG signals. Features from both scalp and source spaces were extracted and used as predictors in a regression problem using random forests. We improved the accuracy of the state-of-the-art method from 20% to 53%.

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