Recorded 30 August 2022. Erik Bollt of Clarkson University Math/ECE presents "Identifying Interactions in Complex Networked Dynamical Systems through Causation Entropy" at IPAM's Reconstructing Network Dynamics from Data: Applications to Neuroscience and Beyond. Abstract: Inferring the coupling structure of complex systems from time series data is a challenging problem in applied science across many disciplines. Reliable and true coupling structure inference requires us to distinguish between both direct and indirect influences between the components within the system. In this work, we present our data-driven information theoretic approach called optimal causation entropy (oCSE) to identify the information flow associated with the actual coupling structure. We will include discussion of examples such as the functional brain network as inferred by fMRI. We will contrast this oCSE network from the popular correlation based brain inference, and dynamical roles these both play in healthy function. Learn more online at: http://www.ipam.ucla.edu/programs/workshops/reconstructing-network-dynamics-from-data-applications-to-neuroscience-and-beyond/?tab=overview