Gamechangers: Conceptual breakthroughs in neuroscience
Fall semesters | Syllabus
For: Freshmen.

This introductory class will highlight some key findings in neuroscience over the past century and a half that have revolutionized our understanding of how the brain works. The goal is to convey both the essence of, and the excitement surrounding, neuroscientific breakthroughs that caused paradigm-shifts. We will also look at recent neuroscience-related headlines in popular media and unpack them from a scientific perspective. Topics covered will include “Is the brain just one big lump of tissue?”, “Telephones in the brain?”, “The frog with upside-down vision”, “Brains vs. hard-drives”, “Monkey see=monkey do neurons”, Epigenetics, “Changing the brain’s wiring diagram”, “Do ants have GPS?”, the science behind the movie ‘Memento’, “Implanting false memories into brains”, “My brain sees you, but I don’t” etc. For each big question, we will first examine the thinking that previously existed, and then explore the shift in thinking.
Evaluation: Students will be evaluated based on readings, on the synthesis of ideas and critical thinking (writing pieces), on discussions in class, and on written quizzes.

Quantitative methods for the brain sciences
Spring semesters | Syllabus
For: Early graduate students and upper-level undergraduates (with permission).

The goal of this class is to train students in the methods that are commonly used in analyzing “brain data”. It is designed to serve students who do not have a strong quantitative background. Therefore, rather than being a “Math” or a “Stats” class, this class is more of a guide to frequently used quantitative methods. Emphasis will be on gaining a conceptual understanding of techniques, and their use. We will focus on the analysis of brain activity data (from electrophysiology and imaging, and to some extent, fMRI). We will look at how to summarize data (normalization, comparisons, etc), how to extract the process underlying a data set (curve fitting), data visualization, etc. In order to develop expertise in the techniques and their use, you will be asked, as part of your homework assignments, to take frequent, short quizzes, to solve problem sets/critique journal articles. Knowledge of MATLAB and IMAGEJ is a plus, but not necessary, as we will go over the basics as part of the class. If time permits, we will take quick detours into labs (the “trenches”) for a first hand look at neuroscientific data as they are being generated.
Course benefits
By the end of the course, you can expect to: 1. Be able to apply appropriate mathematical and statistical techniques to, and draw valid conclusions from, typical (neuroscientific) datasets.
2. Be able to justify and explain the use of analyses (this will help with writing methods sections in your own papers); be able to view quantitative methods used in publications with a critical eye.
3. Be exposed to “meta” skills: use of MATLAB, and organization of new information into a personally meaningful framework.