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Computational
Neuroimaging
(Psych and
Neurobio 204A)
This course is designed for graduate students with an interest
in the methods and techniques of functional magnetic resonance imaging (fMRI)
and diffusion tensor imaging and fiber tracking (DTI-FT).
A theme of the course will be to specify the ideas at a
sufficiently precise level so that we can express them as quantitative
simulations. Whenever possible and practical, these will be designed,
developed and tested in Matlab. (A
broad goal for the instructor is to develop a quantitative simulation that
relates neural circuit properties and energy consumption models to the fMRI
signal. What this means will be
clarified in the first two weeks of the class.)
Students will begin making presentations based on the
readings in the 4th week of the class.
I recommend the book Functional Magnetic
Resonance Imaging (Huettel, Song and McCarthy) as an excellent textbook for
all neuroimaging students.
Weeks 1-3
o The MR signal. Electrical signals in the brain and
energy consumption. The physiological basis of the BOLD signal. How do these
issues influence the interpretation of fMRI as we seek to understand brain
computations?
Readings: Logothetis
and Wandell (Ann Rev Physiol).
Bullock (PNAS). Heeger and
Ress (Nature Neuroscience Reviews), Hornak online book:The Basics of
MRI.
Weeks 4-5
o The design and interpretation of fMRI experiments.
Subtraction principle. Block designs, event-related designs.
Stimulus-referred designs. Statistical and computational methods.
Visualization methods (flattening, inflated brains, slices).
Readings: Wandell (Annual
Review Psych), Huettel et
al., book chapters; Fischl reading; Wandell reading
Weeks 6-7
o Diffusion tensor imaging and fiber-tracking
methods. Visualization methods. Validation.
Readings:
Basser, Caitani Conturo, Hagman, Mori, Westin readings
Weeks 8-10
o Five important papers using fMRI and DTI. Important means (a) scientifically
influential, or (b) clinical applications.
Readings: Chosen by class
members during the quarter.
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