Abstracts

Mapping brain networks in epilepsy: insights from novel EEG, fMRI and morphometric MRI methods

Abstract number : IW.05
Submission category :
Year : 2010
Submission ID : 12963
Source : www.aesnet.org
Presentation date : 12/3/2010 12:00:00 AM
Published date : Dec 2, 2010, 06:00 AM

Authors :
Andrea Bernasconi and William Gaillard

Summary: The human brain is anatomically and functionally organized into complex networks allowing both segregation and integration of information. During the last decade, multidisciplinary research in neuroimaging has provided methods capable of exploring in vivo and non-invasively both structural and functional connectivity at the macroscopic level. These methods are of particular interest to epilepsy since large-scale brain networks connectivity is responsible not only for high cognitive processes, but also for the clinical manifestations of this condition. Studying networks is also crucial to understand consequences of the epileptic process, and its relationship to brain morphology and function. This workshop will assemble a panel of experts that have proposed novel frameworks based on EEG, functional and structural MRI to assess quantitatively brain connectivity. It will provide participants with: the principles of recent EEG and MRI methods to analyze brain networks; a comprehensive review of data on in vivo mapping of temporo-limbic and cognitive networks; a multidisciplinary discussion on the pathophysiology of epileptogenic networks remodeling, with emphasis on temporal lobe epilepsy. Novel methods that have provided independent evidence for altered connectivity in epilepsy will be discussed: analysis of spatial properties of EEG signal and resting state fMRI analyzing temporal correlations of BOLD signals (Dr M. Guye, University of Marseille, France); fMRI activation studies mapping functional networks associated with memory and language (Dr M Berl, George Washington University School of Medicine, USA); analysis of structural connectivity using MRI-based morphometric correlational data (N. Bernasconi, Montreal Neurological Institute, McGill University, Canada).