A multimodal framework for integrating biological spectral characteristics and MEG/EEG in brain-source imaging

This paper presents a multimodal framework that considers the spatio-temporal-spectral characteristics of biophysics provided by electrocorticographic (ECoG) and magnetoencephalography (MEG)/electroencephalography (EEG). In this framework, three strategies are proposed to integrate biological characteristics into MEG/EEG source imaging, the coefficient constraint (CoCo) gives a conservative estimate; the exponent constraint (ExCo) yields a polarized resolution; the hybrid constraint (HyCo) dynamically balances the reliance on CoCo and ExCo, based on the quality of the MEG/EEG data, and takes full advantages of both, providing the framework with heuristic ability. Our contribution is a framework with the potential to use biological characteristics information when doing source imaging.