Neurons forming a network in disassociated cell culture. (Image courtesy of Seung Laboratory
, MIT Department of Brain and Cognitive Sciences.)
This course explores the organization of synaptic connectivity as the basis of neural computation and learning. Perceptrons and dynamical theories of recurrent networks including amplifiers, attractors, and hybrid computation are covered. Additional topics include backpropagation and Hebbian learning, as well as models of perception, motor control, memory, and neural development.
Special software is required to use some of the files in this course: .mat, and .m.
*Some translations represent previous versions of courses.