Computational Neuroscience: Exploring Brain-Environment Interaction with EEG

This course is highly interdisciplinary and data-driven, and provides students with competency in applying neural data science techniques (or more specifically, computational neuroscience techniques) in researching and understanding how the brain interacts with the outside world using electroencephalography (EEG). During the course, we collect EEG data to study the brain's response to a variety of conditions, for example, when engaged in contemplative practices, or when performing geospatial navigational tasks (way finding). Topics such as the use of EEG as biomarkers for neurological disorders and Brain Computer Interface (BCI) will also be explored. The course is interdisciplinary with wide-ranging learning objectives, from designing brain imaging experiments to obtaining EEG data from subjects to data analysis, and communication of findings. Study modes in this course include reading and analysing primary literature, completion of an independent research project that further develops research and computational skills, and articulation of research findings in oral format by giving a class group presentation.