The course application deadline is *March 30*.

The course covers a range of topics in computational neuroscience
including neuronal biophysics, neural coding & information processing,
circuit dynamics, learning & memory, motor control, and cognitive
processing & disease. In addition, numerous tutorials and problem sets
will cover a broad range of computational and mathematical modeling
methods. The course strongly emphasizes the collaboration between
theory and experiment in solving neuroscience problems, and lectures
will be given by a mixture of theorists and experimentalists. The
final weeks of the course are primarily reserved for work on
projects that students design in collaboration with the resident
faculty. Further information can be found on the MCN website:
http://www.mbl.edu/mcn/

2022 Course Directors:
Stephen Baccus, Stanford University
Xiao Jing Wang, New York University

2022 Faculty:

Larry Abbott, Columbia University

Tim Behrens, Univ. College London

Emery Brown, MIT

Randy Buckner, Harvard University

Anne Churchland, UCLA

Claudia Clopath, Imp. College London

Albert Compte, IDIBAPS

Shaul Druckmann, Stanford University

Uri Eden, Boston University

Bard Ermentrout, U. of Pittsburgh

Adrienne Fairhall, U. of Washington

Michale Fee, MIT

James Fitzgerald, Janelia Res., HHMI

Loren Frank, UCSF

Stefano Fusi, Columbia University

Surya Ganguli, Stanford University

Paul Glimcher, New York University

Mark Goldman, UC Davis

Nancy Kopell, Boston University

Eve Marder, Brandeis University

Yiota Poirazi, IMBB-FORTH

David Redish, U. Minnesota

Terry Sejnowski, Salk Institute

Reza Shadmehr, Johns Hopkins Univ.

Sara Solla, Northwestern University

Haim Sompolinsky, Hebrew University

Nelson Spruston, Janelia Res., HHMI

Josh Tenenbaum, MIT

Nao Uchida, Harvard University

Greg Wayne, DeepMind