ABSTRACT The PhD Program in Neuroscience at Harvard University has been a leader in the development of innovative curricula for training in research rigor, beginning with the creation, in June 2011, of the course "Quantitative Methods for Biologists," led by Drs. Michael Springer and Richard Born. Since this time, we have continued to develop curricula in this area, including specific instruction in research rigor and reproducibility from a statistical perspective in the course "Thinking about data," taught by Dr. Born. We propose to extend and enhance these efforts by developing teaching materials that will address "missing pieces" in neuroscience curricula to reinforce research rigor: 1) identifying and eliminating sources of bias in experimental design and analysis, 2) distinguishing experimental failures from biological answers; 3) investigating the details and assumptions of analyses and 4) making coded analyses reproducible. Our pedagogical approach will emphasize active learning and embedding concepts within a specific neuroscience context to enhance student engagement, learning, and retention. All units will feature interviews with diverse scientists to highlight the importance of the topic and tutorials of varying difficulty focused on specific neuroscience examples. These tutorials will consist of short animated videos to introduce key ideas, interactive visualizations, discussion questions, real data when appropriate, and optional coding exercises, and will be available in various levels of difficulty and assumed expertise. All units will include a “learner resources page” with summary notes, a glossary, and pointers to further resources on the topic, as well as an instructor resources page with sample lesson plans, assessment question banks, and downloadable content.