Gamechangers: Conceptual breakthroughs in neuroscience
Fall 2015, 2014 | 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 2016, 2015, 2014 | Syllabus
For: Early gradual students and seniors (with permission).

The goal of this class is to train students in key quantitative methods that are commonly used by brain scientists (neuroscientists, psychologists, cognitive scientists) to analyze data. It is designed to serve students who do not have a strong quantitative background. This is not a “statistics” class. Rather, serves as a guide to powerful  quantitative techniques along with some exposure to their underlying math. Topics covered will include dimensionality reduction, information theory, frequency domain analyses, curve fitting, optimization, and clustering, and will be applied to "brain activity" datasets (obtained with electroophysiology, imaging, and to some extent, fMRI). Emphasis will be on gaining a conceptual understanding of techniques and their practical application, rather than on proofs. In order to develop expertise in the techniques and their use, students will work on problme sets, take short quizzes, and critique journal articles. Knowledge of MATLAB is a plus, but not necessary, as we will go over MATLAB basics as part of the class.

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 "brain science" 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 frameworks.