|제목||[학술세미나] [학과세미나] 12월 19일(목) 특별세미나 안내|
|내용||[학과세미나] 12월 19일(목) 특별세미나 안내
▪제목 : Regularized Aggregation of Statistical Parametric Maps and Graphical Models
▪연사 : Cheolwoo Park (University of Georgia)
▪일시 : 2019년 12월 19일(목) AM 11:00 – 12:00
▪장소 : 25동 405호
Combining statistical parametric maps (SPM) from individual subjects is the goal in some types of group-level analyses of functional magnetic resonance imaging (fMRI) data. Brain maps are usually combined using a simple average across subjects, making them susceptible to subjects with outlying values. Furthermore, t tests are prone to false positives and false negatives when outlying values are observed. We propose a regularized aggregation method for SPMs to find an optimal weight for aggregation, which aids in detecting and mitigating the effect of outlying subjects. We also present a bootstrap-based weighted test using the optimal weights to construct an activation map robust to outlying subjects. We validate the performance of the proposed aggregation method and test using simulated and real data examples. Results show that the regularized aggregation approach can effectively detect outlying subjects, lower their weights, and produce robust SPMs. We also apply the proposed regularized aggregation to the simultaneous estimation of individual and group brain networks based on graphical models.
세미나 안내_191219_Cheolwoo Park.hwp [14.5KB]