Abstract #1818
Characterizing temporal variations of functional connectivity in resting-state
Zening Fu 1 , Xin Di 2 , Shing Chow Chan 1 , Yeung Sam Hung 1 , Bharat B. Biswal 2 , and Zhiguo Zhang 1
1
Department of Electrical and Electronic
Engineering, The University of Hong Kong, Hong Kong,
Hong Kong, China,
2
Department
of Biomedical Engineering, New Jersey Institute of
Technology, Newark, New Jersey, United States
The temporal variation in functional connectivity (FC)
may convey important information about the integration
and coordination of human brain. Recently,
sliding-window analysis is a dominant approach to
characterize temporal dynamics of FC, but there is still
lacking an effective method to select the window size
adaptively to cater for FC dynamics with different
degrees of non-stationarity. In this work, we introduce
a data-driven variable window selection method for
estimating the time-varying correlation coefficient and
apply it to investigate temporal variability of FC in
resting-state fMRI. The results demonstrate that
between-network FC exhibits a significantly larger
temporal variation than within-network FC.
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