Fusion of electroencephalography and functional magnetic resonance imaging to explore epileptic network activity
Borbála Hunyadi, Wim Van Paesschen, Maarten De Vos, Sabine Van Huffel · 2016
Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are two complementary modalities capturing a mixture of various underlying neural sources. The fusion of these modalities promises the best of both worlds, i.e. a better resolution in time and space, respectively. Assuming that EEG and fMRI observations are generated by the same mixing system in both modalities, their fusion can be achieved by joint blind source separation (BSS). We solve the joint BSS problem using different variants of joint independent component analysis (jointICA) and coupled matrix-tensor factorization (CMTF). We demonstrate that EEG-fMRI fusion provides a detailed spatio-temporal characterization of an EEG-fMRI dataset recorded in epilepsy patients, leading to new insights in epileptic network behaviour.