Understanding causality is central to neuroscience, both in how the action of one neuron affects another, as well as in medical approaches that aim to produce causal effects. For this project, Dr. Konrad Kording and his team will develop a set of computational techniques that will allow neuroscientists to quantify how neurons causally influence one another. To do so, they will utilize approaches popular in econometrics, wherein the observation of variables that approximate random system perturbations will allow for the discovery of causal relations. The interdisciplinary team will apply these techniques to problems in neuroscience through a combination of machine learning and engineering, paving the way for important advances toward understanding and quantifying causality in both basic and clinical applications.