Speaker Biography
Moritz Grosse-Wentrup is Professor for Data Science at the Ludwig-Maximilians-Universität München and group leader at the Max Planck Institute for Intelligent Systems, Tübingen. After obtaining his Dr.-Ing. degree at Technische Universität München, he was a postdoc with Bernhard Schölkopf at the Max Planck Institute for Biological Cybernetics. He has been the recipient of the 2011 Annual BCI Research Award and the 2016 IEEE Brain Initiative Best Paper Award. He serves as the steering committee chair for the International Workshop on Pattern Recognition in Neuroimaging (PRNI) and as an area chair for the Neural Information Processing Systems (NIPS) conference. He is a founding member of the EURASIP-SAT on Biomedical Image and Signal Analysis. His research focuses on machine learning for brain decoding and neural engineering, with applications in brain-computer interfacing for communication and rehabilitation.
Talk Abstract
Explaining how neuronal activity gives rise to cognition is a fundamental problem in cognitive neuroscience. It is presently unclear, however, what conditions a theory should satisfy in order to be generally accepted as bridging the explanatory gap between the neuronal and the cognitive level. In this talk, I argue that such a theory should satisfy three conditions: First, it should provide a causal model that operates on the neuronal level. Second, it should provide a causal model that operates on the cognitive level. And third, it should give a causally consistent mapping between these two models, i.e., a mapping that allows us to reason interchangeably about the effects of experimental manipulations on both levels. I state sufficient conditions for a mapping to be causally consistent, and outline how a theory that fulfils all three conditions might be constructed in practice.