DocumentCode :
722855
Title :
Exploratory analysis of time-varying functional connectivity in a visual task
Author :
Jingjun Wong ; Zhiguo Zhang
Author_Institution :
Inst. of Psychiatry, Dept. of Neuroimaging, King´s Coll. London, London, UK
fYear :
2015
fDate :
12-14 June 2015
Firstpage :
1
Lastpage :
5
Abstract :
Functional magnetic resonance imaging (fMRI) has become a common tool in investigating brain activities on human subjects. Although each region of the brain was thought to be independent and responsible only for particular tasks and specialized functions, recent studies have shown that different regions of the brain interact with each other in performing specific tasks or even during the resting state. However, the temporal variations in functional connectivity have been largely overlooked by most studies. This study aims to explore time-varying properties of functional connectivity through comparing results from different correlation and regression analysis methods on a sample set of fMRI data acquired from a visual task. The results clearly show that functional connectivity in the visual task is transient, which suggests that simply assuming a sustained connectivity change during task period might not be sufficient to capture dynamic functional connectivity changes induced by tasks.
Keywords :
biomedical MRI; medical image processing; brain activities; brain interact; exploratory analysis; fMRI data; functional magnetic resonance imaging; human subjects; temporal variations; time-varying functional connectivity; time-varying properties; visual task; Correlation; Correlation coefficient; Kalman filters; Magnetic resonance imaging; Noise; Smoothing methods; Visualization; Kalman filtering; functional connectivity; functional magnetic resonance imaging; time-varying signal processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA), 2015 IEEE International Conference on
Conference_Location :
Shenzhen
Type :
conf
DOI :
10.1109/CIVEMSA.2015.7158633
Filename :
7158633
Link To Document :
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