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Abstract #3746

Classification of BOLD-fMRI dynamic functional connectivity states based on simultaneous EEG microstates

Rodolfo Abreu1,2, Alberto Leal3, and Patrícia Figueiredo1

1ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Ténico, Universidade de Lisboa, Lisboa, Portugal, 2Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT) and CNC.IBILI, University of Coimbra, Coimbra, Portugal, 3Department of Neurophysiology, Centro Hospitalar Psiquiátrico de Lisboa, Lisboa, Portugal

Dynamic functional connectivity (dFC) states have been identified in BOLD-fMRI data, but their electrophysiological underpinnings remain a matter of debate. The simultaneous acquisition of the EEG has previously allowed the identification of EEG signatures of dFC states. Here, we further investigated whether EEG microstates can be used to classify dFC states. We found that highly accurate classification could be achieved based on the three EEG microstates with the highest global explained variance, in simultaneous EEG-fMRI data acquired from eight epileptic patients. These results further support the electrophysiological underpinnings of fMRI dFC states, highlighting their relationship with EEG-derived microstates.

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