Exploring the Visual System with Functional Digital Twins and Inception Loops
Speaker: Prof. Fabian Sinz
Affiliation: University of Göttingen, Institute of Computer Science
Deep nonlinear system identification models have set new standards in modeling the responses oflarge–scale populations of neurons to natural stimuli, yielding models that can accurately predict theresponse of thousands of neurons to arbitrary stimuli and can account for how behavior modulatesresponses of visual neuron. This allows us to treat the model as a functional digital twin of the neuralpopulation and probe neurons in ways that would not be feasible experimentally. With that, we can derive new hypotheses about the neural populations in silico and consequently verify them in vivo, ina paradigm we call inception loops. In this talk, I will give an overview over the models, andshowcaseseveral examples how they can be used to derive novel insights for the visual system in mice andmonkeys. We believe that the combination of large–scale recordings under natural stimulation anddeep data–driven modeling is a paradigm shift in systems neuroscience towards understanding computations in sensory system on complex ecological stimuli.
Prof. Dr. Heinz Beck Institute of Experimental Epileptology and Cognition Research Life and Brain Center University of Bonn Medical Center Sigmund-Freud Str. 25 53127 Bonn
Contact:
Prof. Dr. Heinz Beck Institute of Experimental Epileptology and Cognition Research Life and Brain Center University of Bonn Medical Center Sigmund-Freud Str. 25 53127 Bonn
Contact:
Prof. Dr. Heinz Beck Institute of Experimental Epileptology and Cognition Research Life and Brain Center University of Bonn Medical Center Sigmund-Freud Str. 25 53127 Bonn