%0 Journal Article
	%A Chia-Feng Lu and  Yuh-Jen Wang and  Yu-Te Wu and  Sui-Hing Yan
	%D 2014
	%J International Journal of Biomedical and Biological Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 95, 2014
	%T Relations of Progression in Cognitive Decline with Initial EEG Resting-State Functional Network in Mild Cognitive Impairment
	%U https://publications.waset.org/pdf/9999741
	%V 95
	%X This study aimed at investigating whether the
functional brain networks constructed using the initial EEG (obtained
when patients first visited hospital) can be correlated with the
progression of cognitive decline calculated as the changes of
mini-mental state examination (MMSE) scores between the latest and
initial examinations. We integrated the time–frequency cross mutual
information (TFCMI) method to estimate the EEG functional
connectivity between cortical regions, and the network analysis based
on graph theory to investigate the organization of functional networks
in aMCI. Our finding suggested that higher integrated functional
network with sufficient connection strengths, dense connection
between local regions, and high network efficiency in processing
information at the initial stage may result in a better prognosis of the
subsequent cognitive functions for aMCI. In conclusion, the functional
connectivity can be a useful biomarker to assist in prediction of
cognitive declines in aMCI.

	%P 791 - 797