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.
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.