Wednesday, May 25, 2022 • 9:00–10:30 am (CT) • Light Hall, Room 202
Instructors: Joshua Lukemire and Ying Guo
In this short course, we introduce the Hierarchical INdependent component analysis Toolbox (HINT) (Lukemire et al., 2020). HINT is a GUI-based Matlab toolbox based on a hierarchical ICA framework (Shi and Guo, 2016; Wang and Guo, 2019) for extracting brain networks and modeling and testing covariate effects on networks. The toolbox can be used to generate model-based estimates of brain networks on both the population and individual levels. This short course will cover using HINT for both cross-sectional and longitudinal fMRI studies. Topics covered include preparing the data, specifying the ICA model, estimating parameters, and visualizing results with an emphasis on hypothesis testing for covariate effects.