Dynamic Connectivity in fMRI: Methods & Applications

This lecture by the instructor provides a comprehensive overview of dynamic functional connectivity methods in fMRI analysis. Starting with activation-based and static connectivity analysis, the lecture delves into the concept of non-stationary connectivity, highlighting the importance of identifying multiple brain states. The application of these methods in understanding brain disorders like schizophrenia and bipolar disorder is discussed, emphasizing the potential for distinguishing clinical groups. Various advanced techniques such as frame-wise analysis, temporal modeling, and dynamic graph analysis are explored, showcasing their utility in uncovering temporal relationships between brain states. The lecture concludes with insights on the contributions of dynamic connectivity in studying cognitive and psychiatric phenomena, cautioning about the challenges of hypothesis testing and result interpretation in this field.