A neural field model for spatio-temporal brain activity using a morphological model of cortical connectivity
© Trong et al; licensee BioMed Central Ltd. 2009
Published: 13 July 2009
Electroencephalography and magnetoencephalography (EEG and MEG) are brain signals with high temporal resolutions and are believed to reflect neural mass action. For modeling the neuronal structures, which are responsible for the generation of EEG/MEG, one can use so-called neural mass models, like the one of Jansen and Rit . In such models, a brain area (e.g. a cortical column) is modeled by two or three neural masses subsuming similar cells, which are characterized by a single input-output relationship. It turns out that this type of model is too simple to reproduce the entire richness of typical EEG spectra. We therefore propose to use neural field models , which take into account the spatial dimension of active brain areas and describe the use of realistic local connectivity information in these models.
We propose a new formalism to model neural fields and describe the incorporation of precise local connectivity information into these models. Our model is capable of producing output with very EEG-like time courses and spectra. Our results might constitute an important step on the road towards a universal model for neuronal mass action.
This article is published under license to BioMed Central Ltd.