Courses:

CAS CN500: Computational Methods in Cognitive and Neural Systems Prereq: One year of calculus or consent of instructor. This course introduces students to computer and mathematical techniques, spanning a variety of scientific areas that make use of theoretical and applied computational modeling, such as engineering, mathematics, computer science and computational neuroscience.  Each topic is introduced through practical examples from literature, combining theory and applications.  Topics include basic and advanced computer skills, difference and differential equations, mathematical simulation techniques, statistics, digital signal processing, control theory and image processing.  This course is designed with the flexibility required to account for the varied background of participating students. 4cr., 1st semester.

CAS CN570: Neural and Computational Models of Conditioning, Reinforcement, Motivation and Rhythm Prereq: CN510 or consent of instructor. This course develops neural and computational models of how humans and animals learn to successfully predict environmental events and generate behavioral actions which satisfy internally defined criteria of success or failure.  Reinforcement learning and its homeostatic (drive, arousal, rhythm) and non-homeostatic (reinforcement) modulators are analyzed in depth.  Recognition learning and recall learning networks are joined to the reinforcement learning networks to analyze how these several processes cooperate to generate successful goal-oriented behavior.  Maladaptive behaviors and certain mental disorders are analyzed from a unified theoretical perspective.  Applications to the design of freely moving adaptive robots are noted. 4 cr., 2nd semester.

							Dept. of Cognitive and Neural Systems http://www.cns.bu.edu/users/rucci/
August, 2003