Advanced algorithm for integrated EEG-fMRI data processing.

By combining multiple modalities in a multimodal recording setting one expects to better reveal the complex spatiotemporal interactions between different brain regions and better interpret the underlying neurophysiology. Here, we focus on EEG and fMRI. To fully exploit their strengths, appropriate mathematical frameworks are needed. In this project we extend tensor data structure technology and dipole source localization methodologies by fully exploiting the better spatial information of fMRI into EEG analysis. The challenge is to exploit the spatial localization together with the anatomical and functional properties of the brain activity, as extracted from fMRI data analysis (e.g. using Statistical Parametric Mapping or ICA) into EEG analysis. This should improve the extraction of the relevant EEG events of interest (e.g. epileptic seizure, ERP) and the consequent localization of the corresponding EEG sources generating the brain activity. The project is split into 3 work packages with own objectives. WP1. Extract the EEG source signal(s) of interest by extending tensor data structure technologies in 3 ways: (1) Tensor decompositions: design computationally efficient and numerically robust algorithms, (2) Simultaneous matrix/tensor decompositions: choice of structure and development of algorithms and (3) Constrained tensor decompositions: choice of constraints and development of algorithms WP2. Localize the EEG source(s) of interest by extending multiple/dipole source localization technology in 2 ways: (1) Creating advanced head models, (2) solving the inverse problem using a priori information. WP3. Combine the results of WP1 and WP2 to iteratively refine EEG source extraction and localization.

Keywords:Dipole source localisation, Tensor decomposition, EEG, Functional magnetic resonance

Disciplines:Applied mathematics in specific fields, Computer architecture and networks, Distributed computing, Information sciences, Information systems, Programming languages, Scientific computing, Theoretical computer science, Visual computing, Other information and computing sciences, Modelling, Biological system engineering, Signal processing, Multimedia processing