The primary focus of the Laboratory for Neuroinformatics is to develop new computational methods for extracting digital biomarkers for brain disorders from EEG measurements. Our approach to EEG signal analysis is based in complex dynamical systems theory. Entropy measures, recurrence plot and recurrence network analysis, neural synchronization, and tensor data structures all play a role. Machine learning is used to extract information from these measures. Though the methods are theoretical, the goal of this work is highly practical: we seek digital biomarkers that can be implemented and used in clinical settings for early detection, treatment planning, and monitoring of neurological, neurodevelopmental, and mental disorders.
