Principal Investigators //


Yuhui Du, PhD

Research Scientist

Yuhui Du

Dr. Du is interested in how to estimate brain functional networks using multi-subjects’ fMRI data. She developed a data-driven group information guided independent component analysis (GIG-ICA) to estimate subject-specific brain networks while still preserving correspondence of networks across different subjects. GIG-ICA estimates functional networks using a multiple-objective optimization algorithm that simultaneously optimizes the independence of individual networks of each subject as well as the correspondence between group-level network and subject-specific network. GIG-ICA has been successfully applied to investigate network features for distinguishing different mental disorders. Dr. Du is also interested in analysis of dynamic functional network. She developed a decomposition-based method to extract connectivity states from time-varying functional connectivity patterns and found potential biomarkers for schizophrenia, psychotic bipolar disorder and schizoaffective disorder. In addition, Dr. Du worked on classifying different mental disorders using supervised and semi-supervised classification methods, aiming to achieve a biologically meaningful nosology and benefit individual diagnosis.

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