Processing, Analysis, and Classification for Neuroimaging Data


Junhua Li:

Tutorial Title: Processing, Analysis, and Classification for Neuroimaging Data

Abstract:

This tutorial will briefly present the concept of neuroimaging data processing, analysis, and classification at the beginning. This will be followed by the introduction of EEG and fMRI, which are prevalently utilized to explore brain functions pertaining to particular mental states or psychiatric diseases. After that, I will report a few experiments looking insights into the brain when it is engaging in tasks to be a particular mental state or is under a pathological condition. Methods and results will be shown along with the demonstrations of the experiments as videos. Functional connectivity will be focused in this tutorial. Specifically, I will show how functional connectivity changes with the progression of fatigue, how functional connectivity alters at the different levels of workload, what the different inter-regional organizations are under different walking conditions with and without an exoskeleton. The findings derived from the above studies were used to guide the feature extraction to facilitate the decoding of brain states. In addition, I will also present our proposed methodologies such as dynamic functional connectivity and deep learning model.