Cognitive & Neural Systems

  • CAS CN 510: Principles and Methods of Cognitive and Neural Modeling I
    Undergraduate Prerequisites: CASMA226 (or equivalent; can be taken in parallel); and CASCS108 or CASCS111 or ENGEK127 (or equivalent); and CASNE101 (or equivalent; can be taken in parallel); or consent of instructor.
    Explores psychological, biological, mathematical, and computational foundations of behavioral and brain modeling. Topics include organizational principles, mechanisms, local circuits, network architectures, cooperative and competitive non-linear feedback systems, associative learning systems, and self-organizing code-compression systems. The adaptive resonance theory model unifies many course themes. CAS CN 510 and 520 may be taken concurrently.
  • CAS CN 530: Neural and Computational Models of Vision
    Undergraduate Prerequisites: CAS CN 510; or consent of instructor.
    Graduate Prerequisites: CAS CN 510; or consent of instructor.
    Current models of mammalian visual processes are constrained by experimental and theoretical results from psychology, physiology, computer science, and mathematics. The course evaluates the explanatory adequacy of competing neural and computational models of such processes as edge detection, textural grouping, shape-from-shading, stereopsis, motion detection, and color perception. Students perform computer simulations of some of the examined models.
  • CAS CN 570: Neural and Computational Models of Conditioning, Reinforcement, Motivation, and Rhythm
    Undergraduate Prerequisites: CAS CN 510; or consent of instructor.
    Develops neural and computational models of how humans and animals learn to successfully predict environmental events and generate behavioral actions that satisfy internally defined criteria of success or failure. Reinforcement learning and its homeostatic (drive, arousal, rhythm) and nonhomeostatic (reinforcement) modulators are analyzed in depth. Recognition learning and recall learning networks are joined to the reinforcement learning network 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.
  • GRS CN 699: Teaching College Cognitive and Neural Systems I
    The goals, contents, and methods of instruction in cognitive and neural systems. General teaching-learning issues. Required of all teaching fellows.