T133. The effective brain connectome: An inverse problem

Abstract

We give a general overview of recent developments in the study of Brain Connectivity. The essential task is to estimate the “Effective Brain Connectome” (EBC). This is the set of all direct interactions between neural masses. However, these interactions have to be estimated. We propose a formal definition of the EBC as a hypergraph defined on a multidimensional tensor. The simplest version of EBC is defined on a 3-dimensional tensor, with signatures for emitter regions, receiver regions and time delays, taking values for a Wiener-Akaike-Granger-Schweder influence measure. In the more complex case the dimensionality may take into consideration cortical layer, neurotransmitters etc. The support of the hypergraph is defined by the structural connectome. The actual challenge is to estimate the EBC from incomplete, noisy, multimodal neuroimaging data, especially from EEG and fMRI time series. Recognition of the mathematical structure of the underlying model allows the use of new tensor based methods for model inversion and data fusion. These are illustrated with resting state EEG/fMRI data. Finally, open problems in EBC studies are identifies and discussed.