![]() The current focus is on Causality in Data science applications - how do we know how things work if we can not randomize? But we are also very much excited about understanding how the brain does credit assignment. ![]() But as the approaches matured, the focus has more been on discovering ways in which new data sources as well as emerging data analysis can enable awesome possibilities. Early research in the lab focused on computational neuroscience and in particular movement. Kording's (He/Him) is trying to understand how the world and in particular the brain works using data. Then I will review how quasiexperimental techniques may give us causality in some cases where currently popular approaches may not.ĭr. I will give some intuitions on why causality is so hard in practice. I will review ways in which neuroscientists try to infer causality in the world. ![]() Quasiexperimental causality in neuroscience Konrad Kording, Penn Integrated Knowledge Professor, University of Pennsylvania
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