NeuroCore:Quantitative Rigor and Reproducibility in Neuroscience

Catalog description

The quantitative neuroscience core course is designed to be an overview of quantitative approaches used for rigorous and reproducible neuroscience research. This course does not cover statistics in a traditional way, in the sense that it does not provide a comprehensive survey of statistical tests, nor does it dive very deeply into formal mathematical derivations of those tests (information about such things can be found in textbooks and all over the web). Instead, the course focused on teaching students how to apply quantitative approaches to now they think about neuroscience research from beginning to end, including defining clear hypotheses; designing experiments to test those hypotheses; collecting, visualizing, analyzing, and interpreting data in reference to those hypotheses; and keeping effective and transparent records at each stage to ensure rigor and reproducibility. There are two main components to the course. The first component consists of a series of four modules, each of which is designed to use a specific example from neuroscience to illustrate a set of quantitative approaches and tools. The second component consists of group projects that focus on designing and implementing quantitative analyses for existing data sets (e.g., from rotation projects).