DYNAMIC FUNCTIONAL CONNECTIVITY BASED CLASSIFICATION OF PARTICIPANTS FROM FUNCTIONAL MRI DATA

4^th International Conference on Medical Informatics & Telehealth

October 6-7, 2016 | London, UK

Unal Zak Sakoglu

Texas University, USA

Posters & Accepted Abstracts: J Health Med Informat

Abstract :

A dynamic sliding-window-based method, named dynamic functional connectivity (DFC), which assesses temporal dynamics of functional connectivity among different brain networks, was recently developed and it has gained attention (Sakoglu et al, MAGMA Journal, 2010). DFC provides more information than the static FC method and DFC-based features can lead to better classification of brain diseases or conditions when compared with static FC-based features. The method can be applied to FMRI time courses of a voxel or a region-of-interest, as well as it can be combined with powerful data-driven techniques such as independent component analysis (ICA). In this talk, analysis and classification results from FMRI data on addiction, based on DFC features, will be presented.

Biography :

Email: Unal.Sakoglu@tamuc.edu