Speaker: Ben Fulcher
Title: Visualizing and understanding complex neural time series.
Bio: Ben Fulcher is a Senior Lecturer in Physics at The University of Sydney where he leads the Dynamics and Neural Systems Group. After his Bachelor and Masters in Physics at The University of Sydney, he did a PhD in time-series analysis and complex systems at Oxford University, and then worked with whole-brain gene-expression and neuroimaging data during his postdoctoral fellowship at Monash University. His current research uses time-series analysis, statistical learning, and physical brain modeling to quantify patterns and understand brain function in terms of underlying physical mechanisms.
Tutorial Description: Time series are measured across diverse applications in neuroscience, be it from calcium imaging, EEG, MEG, or fMRI experiments. To analyze the structure in such time series, we can select from a library of sophisticated modern methods that have been developed by diverse scientists solving problems in areas from mathematics, geoscience, economics, and astrophysics. From this rich diversity of scientific methods, how do we pick the right methods to pull out the patterns we care about in our neuroscience data? In this tutorial, I will introduce a suite of analysis and visualization tools that we have built to help users find interpretable patterns in their time-series data. I will demonstrate how interactive visualizations can very quickly pull out meaningful understanding from a dataset, using our tools hctsa (Matlab), catch22 (R, python, Julia), and a range of new online tools (including CompEngine).