APPPHYS 293:
Theoretical Neuroscience (PSYCH 242)
Survey of advances in the theory of neural networks, mainly (but not solely) focused on results of relevance to theoretical neuroscience.Synthesizing a variety of recent advances that potentially constitute the outlines of a theory for understanding when a given neural network architecture will work well on various classes of modern recognition and classification tasks, both from a representational expressivity and a learning efficiency point of view. Discussion of results in the neurallyplausible approximation of back propagation, theory of spiking neural networks, the relationship between network and task dimensionality, and network state coarsegraining. Exploration of estimation theory for various typical methods of mapping neural network models to neuroscience data, surveying and analyzing recent approaches from both sensory and motor areas in a variety of species. Prerequisites: calculus, linear algebra, and basic probability theory, or consent of instructor.
Terms: Spr

Units: 3

Grading: Letter or Credit/No Credit