Statistical and computational methods for discriminating of anatomic changes, mental states and identification of brain connectivity: an integrative approach based on MRI, fMRI and EEG

Abstract

One of the main innovations in human brain mapping is the acquisition of structural and functional magnetic resonance imaging. The extraction and unification of information present in EEG data, structural magnetic resonance imaging (MRI) and functional (fMRI) is of great importance for a deep understanding of cognitive processes, diseases and even clinical applications, such as mapping and characterization of epileptogenic foci. A crucial step for multimodal integration is the development of quantitative methods for the identification of brain connectivity and "decoding" of mental states. To date, the number of scientific studies exploring this issue is negligible, thus, there are no methods available for assessing these aspects especially in multimodal data. The main aim of this project is the development and application of new statistical methodologies and software’s for data analysis and integration of information obtained through MRI, fMRI and electroencephalography (EEG). The approach will be in a non-parametric fashion and exploratory (integrating concepts of support vector machines, neural networks, time series clustering, etc.) in order to avoid the necessity of strong assumptions often assumed by conventional statistical methods, thus obtaining, a method with greater flexibility for use in diseases or complex cognitive processing. Moreover, considering the technological, political and social, this project will promote the integration of Federal University of ABC (UFABC) with other research and technologic centers and in Brazil and also international cooperation, encouraging scientific innovation in the ABC region. (AU)