Graduate School of Informatics /Health Informatics
In partial fulfillment of the requirements for the degree of Master of Science Ahmet Levent Kandemir will defend his thesis.
Title: RESTING STATE BRAIN CONNECTIVITY VIA BICOHERENCE AND COHERENCE
Date: 21th March 2018
Time: 14:00 AM
Thesis Abstract : Bicoherence is normalized version of bispectrum. Bispectrum is known as decomposition of the third moment (skewness) of a signal over frequency, and falls in the category of higher-order spectra. It provides supplementary information to the power spectrum and is proven to be useful in various fields of science such as sonars, biomedical engineering, radars etc. Despite this, the extensive computations required for processing of multidimensional data make bispectrum less practical than other methods in signal processing. In this study, information content of bicoherence will be evaluated. The aim is to find a time saving alternative to multidimensional bicoherence estimation. Alternatives will be compared to well known connectivity metric know as coherence. During study, methods will be applied on Resting State MEG data from Human Brain Connectome Project which can be found online.