Title：Parameter-free centralized multi-task learning for characterizing developmental sex differences in resting state functional connectivity
Time and place：April 11, 2018,10:00-12:00 a.m.,RM408 Science Building（理科楼）
Lecturer：Xiaofeng Zhu, professor, Guangxi Normal University
Abstract:
In contrast to most existing studies that typically characterize the developmental sex differences using analysis of variance or equivalently multiple linear regression, we present a parameter-free centralized multi-task learning method to identify sex specific and common resting state functional
connectivity (RSFC) patterns underlying the brain development based on resting state functional MRI (rs-fMRI) data. Specifically, we design a novel multi-task learning model to characterize sex specific and common RSFC patterns in an age prediction framework by regarding the age prediction
for males and females as separate tasks. Moreover, the importance of each task and the balance of these two patterns, respectively, are automatically learned in order to make the multi-task learning robust as well as free of tunable parameters, i.e., parameter-free for short. Our experimental results on synthetic datasets verified the effectiveness of our method with respect to prediction performance, and experimental results on rs-fMRI scans of 1041 subjects (651 males) of the Philadelphia Neurodevelopmental Cohort (PNC) showed that our method could improve the age prediction on average by 5.82% with statistical significance than the best alternative methods under comparison, in addition to characterizing the developmental sex differences in RSFC patterns.
Bio:
Xiaofeng Zhu received his BSc degree from Guangxi Normal University and MSc degree from National University of Singapore. After obtaining his PhD degree from The University of Queensland, Australia, in 2013, he was a post-doc researcher at the University of North Carolina at Chapel Hill, XiAn Jiaotong Univeristy, China, and The University of Pennsylvania. He is currently a full professor at Guangxi Normal University and will be an associate professor at Massey University, New Zealand, in May 2018.
