An introduction to computational modeling of neural systems and neural data analysis techniques for students majoring in neuroscience. Topics include models of the individual neuron, neural encoding and decoding of sensory information, information processing by neural networks, models of memory formation, time-frequency analysis of neural signals, and image processing techniques. Laboratory included. Not open to students with credit for PHYS 330. Prerequisite: NEUR 250 AND one of CS 110, MATH 105 , MATH 110 , MATH 230 , or PSYC 210 ; OR permission of instructor. Corequisite: NEUR 323 L . Group II Natural Science