Current Problems in Applied Mathematics: Mathematical
Methods and Models in Visual Neuroscience
Instructor: D. Graham
Fall Term 2010
Meeting Time: Monday
and Thursday, 4pm – 5:30pm (03A block)
Room: Kemeny 244
TENTATIVE
SYLLABUS (Last YearŐs Syllabus: 2009)
(older syllabus: 2008)
Description
This course is designed to introduce
graduate students and advanced undergraduates from a variety of disciplines to
mathematical methods used to measure and model neural mechanisms underlying the
function of the human visual system. The course will focus primarily on neural
coding strategies in the early visual system (retina, thalamus, primary visual
cortex). General topics will include receptive fields, information-theoretic
approaches, efficient coding theory, and nonlinearities. Higher-level cortical
representations and object recognition strategies will also be discussed.
Prerequisites: No background in
neurobiology is expected, though experience with differential equations, linear
algebra, computer programming and basic biology will be very useful.
Evaluation: Students will be
evaluated based on problem sets (mostly Matlab-based), a quiz, and a final
project/presentation.
Useful links
http://www.handprint.com/HP/WCL/color.html
-- An excellent site describing the retina in fantastic detail.
http://faculty.washington.edu/chudler/neuroroot.html
-- A site that gives the Greek or Latin root of many common brain terms.
http://white.stanford.edu/Useful_Numbers.php
-- Useful numbers in vision science.
http://www.jove.com/index/details.stp?ID=771
-- See how retinal recordings are actually made.
http://www.cis.hut.fi/projects/ica/imageica/
-- A good, transparent ICA package
http://libguides.dartmouth.edu/math
-- Helpful page for math resources available through Baker Library
http://www.med.harvard.edu/AANLIB/cases/caseM/case.html
http://www.brainconnection.com/topics/?main=anat/vision-anat
http://brainmaps.org/index.php
http://www.brainexplorer.org/brain_atlas/Brainatlas_index.shtml