Jaemin Shin1,
2, Zhi Yang3, 4, Audrey Duarte5,
Xiaoping P. Hu1
1Department
of Biomedical Engineering, Georgia Tech and Emory University, Atlanta, GA,
United States; 2Center for Advanced Brain Imaging, Georgia Tech
and Georgia State University, Atlanta, GA, United States; 3Institute
of Psychology, Chinese Academy of Sciences, Beijing, China; 4National
Institute of Mental Health, Bethesda, MD, United States; 5School
of Psychology, Georgia Tech, Atlanta, GA, United States
Recently, increased attention has been directed at resting-state functional connectivity. However, physiological fluctuations arising from respiratory and cardiac processes are detrimental in resting-state functional connectivity analysis. The present study aims to characterize the effects of physiological noise correction on the derived resting-state networks (RSNs). After correction, it is observed that the reproducibility of RSNs is increased. In particular, a technique that corrects for long-term physiological noise effects as well as short-term effects resulted in the highest reproducibility.