College of Arts & Sciences
Cognitive & Neural Systems
BA/MA in Biology and Cognitive and Neural SystemsBA/MA in Computer Science and Cognitive and Neural Systems
BA/MA in Mathematics and Cognitive and Neural Systems
BA/MA in Psychology and Cognitive and Neural Systems
Courses
Chair Ennio Mingolla
Director of Graduate and Undergraduate Studies Barbara Shinn-Cunningham
Professors Bullock, Carpenter, Grossberg, Guenther, Mingolla, Schwartz
Associate Professors Cohen, Shinn-Cunningham
Research Assistant Professors Cao, Gorchetchnikov, Yazdanbakhsh
Adjunct Professors Livingstone, Logothetis, Perkell, Reeves, Sekuler, Wolfe
Adjunct Associate Professors Pomplun, Savoy
Adjunct Research Associate Professor Srinivasa
The Department of Cognitive & Neural Systems (CNS) provides advanced training and research experience for graduate students and qualified undergraduates interested in the neural and computational principles, mechanisms, and architectures that underlie human and animal behavior, and the application of neural network architectures to the solution of technological problems. Students are trained in a broad range of areas concerning computational neuroscience, cognitive science, and neural systems, including study of the brain mechanisms of vision and visual object recognition; audition, speech, and language understanding; recognition learning, categorization, and long-term memory; cognitive information processing; self-organization and development, navigation, planning, and spatial orientation; cooperative and competitive network dynamics and short-term memory; reinforcement and motivation; attention; adaptive sensory-motor planning, control, and robotics; biological rhythms; consciousness; mental disorders; and the mathematical and computational methods needed to support advanced modeling research and applications. Technological training includes methods and applications in image processing, multiple types of signal processing, adaptive pattern recognition and prediction, information fusion, and intelligent control and robotics.
For additional information about the Department of Cognitive & Neural Systems, see the Graduate School of Arts & Sciences Bulletin. To receive a brochure, contact the CNS Office, 677 Beacon Street, Room 201, Boston, MA 02215; e-mail: ramos@cns.bu.edu; Website: Department of Cognitive & Neural Systems.
BA/MA in Biology and Cognitive & Neural Systems
The BA/MA in Biology and Cognitive & Neural Systems is an interdepartmental program in the College of Arts & Sciences and the Graduate School of Arts & Sciences. The program allows undergraduate concentrators in biology to begin working toward an MA in Cognitive & Neural Systems while still completing the Department of Biology BA requirements.
Admission to the BA/MA Program College of Arts & Sciences students currently in or entering the junior year are eligible to apply for admission. Students must apply before March 1 of their junior year and must meet a GPA requirement of at least 3.0 through the end of their junior year. Students admitted to the BA/MA program will typically have completed at least one 500-level or above CNS course. In order to be admitted into the BA/MA program, students must have completed at least Calculus I and II (MA 123 and 124, or equivalent) and Linear Algebra (MA 242).
The application should include a letter from the student’s Department of Biology advisor. Application forms for admission to the BA/MA program may be obtained from the Graduate School of Arts & Sciences Office, 705 Commonwealth Avenue, Suite 112.
Requirements Students must complete all requirements for the BA in Biology, as specified in the Undergraduate Programs Bulletin, and all requirements for the MA in Cognitive & Neural Systems, as specified in the Graduate School of Arts & Sciences Bulletin. In particular, 32 courses (128 credits) are required for the BA, and 8 courses (32 credits) are required for the MA degree. In total, 40 courses (160 credits) are required. Students receive the BA and MA degrees simultaneously. Graduation applications must be submitted for both the BA and MA portions of the degree. For more information, please see Special Courses and Programs under College of Arts & Sciences on this site or contact Professor Frank Guenther (guenther@bu.edu) in the Department of Cognitive & Neural Systems.
BA/MA in Computer Science and Cognitive & Neural Systems
The BA/MA in Computer Science and Cognitive & Neural Systems is an interdepartmental program in the College of Arts & Sciences and the Graduate School of Arts & Sciences. The program allows undergraduate concentrators in computer science to begin working toward an MA in Cognitive & Neural Systems while still completing the Department of Computer Science BA requirements.
Admission to the BA/MA Program College of Arts & Sciences students currently in or entering the junior year are eligible to apply for admission. Students must apply before March 1 of their junior year and must meet a GPA requirement of at least 3.0 through the end of their junior year. Students admitted to the BA/MA program will typically have completed at least one 500-level or above CNS course. In order to be admitted into the BA/MA program, students must have completed at least Calculus I and II (MA 123 and 124, or equivalent) and Linear Algebra (MA 242).
The application should include a letter from the student’s Department of Computer Science advisor. Application forms for admission to the BA/MA program may be obtained from the Graduate School of Arts & Sciences Office, 705 Commonwealth Avenue, Suite 112.
Requirements Students must complete all requirements for the BA in Computer Science, as specified in the Undergraduate Programs Bulletin and all requirements for the MA in Cognitive & Neural Systems, as specified in the Graduate School of Arts & Sciences Bulletin. In particular, 32 courses (128 credits) are required for the BA and 8 courses (32 credits) are required for the MA degree. In total, 40 courses (160 credits) are required. Students receive the BA and MA degrees simultaneously. Graduation applications must be submitted for both the BA and MA portions of the degree. For more information, please see Special Courses and Programs under College of Arts & Sciences on this site or contact Professor Frank Guenther (guenther@bu.edu) in the Department of Cognitive & Neural Systems.
BA/MA in Mathematics and Cognitive & Neural Systems
The BA/MA in Mathematics and Cognitive & Neural Systems is an interdepartmental program in the College of Arts & Sciences and the Graduate School of Arts & Sciences. The program allows undergraduate concentrators in mathematics to begin working toward an MA in Cognitive & Neural Systems while still completing the Department of Mathematics BA requirements.
Admission to the BA/MA Program College of Arts & Sciences students currently in or entering the junior year are eligible to apply for admission. Students must apply before March 1 of their junior year and must meet a GPA requirement of at least 3.0 through the end of their junior year. Students admitted to the BA/MA program will typically have completed at least one 500-level or above CNS course. In order to be admitted into the BA/MA program, students must have completed at least Calculus I and II (MA 123 and 124, or equivalent) and Linear Algebra (MA 242).
The application should include a letter from the student’s Department of Mathematics advisor. Application forms for admission to the BA/MA program may be obtained from the Graduate School of Arts & Sciences Office, 705 Commonwealth Avenue, Suite 112.
Requirements Students must complete all requirements for the BA in Mathematics as specified in the Undergraduate Programs Bulletin, and all requirements for the MA in Cognitive & Neural Systems, as specified in the Graduate School of Arts & Sciences Bulletin. In particular, 32 courses (128 credits) are required for the BA and eight courses (32 credits) are required for the MA degree. In total, 40 courses (160 credits) are required. Students receive the BA and MA degrees simultaneously. Graduation applications must be submitted for both the BA and MA portions of the degree. For more information, please see Special Courses and Programs under College of Arts & Sciences on this site or contact Professor Frank Guenther (guenther@bu.edu) in the Department of Cognitive & Neural Systems.
BA/MA in Psychology and Cognitive & Neural Systems
The BA/MA in Psychology and Cognitive & Neural Systems is an interdepartmental program in the College of Arts & Sciences and the Graduate School of Arts & Sciences. The program allows undergraduate concentrators in psychology to begin working toward an MA in Cognitive & Neural Systems while still completing Department of Psychology BA requirements.
Admission to the BA/MA Program College of Arts & Sciences students currently in or entering the junior year are eligible to apply for admission. Students must apply before March 1 of their junior year and must meet a GPA requirement of at least 3.0 through the end of their junior year. Students admitted to the BA/MA program will typically have completed at least one 500-level or above CNS course. In order to be admitted into the BA/MA program, students must have completed at least Calculus I and II (CAS MA 123 and 124, or equivalent) and Linear Algebra (CAS MA 242).
The application should include a letter from the student’s Department of Psychology advisor. Application forms for admission to the BA/MA program may be obtained from the Graduate School of Arts & Sciences Office, 705 Commonwealth Avenue, Room 112.
Requirements Students must complete all requirements for the BA in Psychology as specified in the Undergraduate Programs Bulletin, plus all requirements for the MA in Cognitive & Neural Systems, as specified in the Graduate School of Arts & Sciences Bulletin. In particular, 32 courses (128 credits) are required for the BA and 8 courses (32 credits) are required for the MA degree. In total, 40 courses (160 credits) are required. Students receive the BA and MA degrees simultaneously. Graduation applications must be submitted for both the BA and MA portions of the degree. For more information, please see Special Courses and Programs under College of Arts & Sciences or contact Professor Frank Guenther (guenther@bu.edu) in the Department of Cognitive & Neural Systems.
Courses
CAS CN 210 Introduction to Computational Models of Brain and Behavior
Prereq: CAS MA 123 and MA 124 and sophomore standing, or consent of instructor. Introduction to important concepts in cognitive neuroscience and computational modeling of biological neural systems. Combines a systems-level overview of brain function with an introduction to modeling of brain and behavior using neural networks. Also offered as CAS NE 204. Guenther. 4 cr, 2nd sem.
CAS CN 330 Introduction to Computational Models of Vision
Prereq: CAS MA 123 and CAS MA 124, and either CAS CN 210 or CAS NE 204, and sophomore standing, or consent of instructor. Explores the psychological, biological, mathematical, and computational foundations of visual perception. Mathematically specified neural and computational models elucidate the structure and dynamics of the mammalian visual system. Also offered as CAS NE 330. Mingolla. 4 cr, 2nd sem.
CAS CN 340 Introduction to Computational Models of Movement Planning and Control
Not offered 2009/2010
CAS CN 350 Introduction to Computational Models of Learning
Not offered 2009/2010
CAS CN 360 Computational Models of Hearing
Not offered 2009/2010
CAS CN 500 Computational Methods in Cognitive and Neural Systems
Prereq: one year of calculus or consent of instructor. Introduction to mathematical methods and computer simulation for modeling cognitive and neural systems. Topics include computer simulation methods, control theory, difference and differential equations, digital signal processing, image processing, optimization, and statistics. Readings from current literature emphasize theory and applications relevant to the study of cognitive and neural systems. 4 cr.
CAS CN 510 Principles and Methods of Cognitive and Neural Modeling I
Prereq: one year of calculus and 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. Meets with STH TX 810. 4 cr.
CAS CN 520 Principles and Methods of Cognitive and Neural Modeling II
Prereq: one semester of linear algebra and consent of instructor. Analyzes three main traditions in models of learning: unsupervised (self-organized) learning, supervised learning (learning with a teacher), and reinforcement learning. Architectures studied include adaptive filters, back propagation, competitive learning, self-organizing feature maps, gradient descent procedures, Boltzmann machines, simulated annealing, neocognitron, and gated dipoles. 4 cr.
CAS CN 530 Neural and Computational Models of Vision
Prereq: 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. 4 cr.
CAS CN 540 Neural and Computational Models of Adaptive Movement Planning and Control
Prereq: CAS CN 510 or consent of instructor. Neural models of eye, arm, hand, orofacial, and leg movements are presented and compared to reveal general organizational principles and specialized neural circuit designs for motor learning and performance. Issues include: trajectory formation, synchronization of synergists, variable velocity control, adaptive gain control, map formation, load compensation, serial order, and inflow versus outflow as sources of sensory-motor information. 4 cr.
CAS CN 550 Neural and Computational Models of Recognition, Memory, and Attention
Prereq: CAS CN 510 or consent of instructor. Develops neural network models of how internal representations of sensory events and cognitive hypotheses are learned and remembered, and how such internal representations enable recognition and recall of these events to occur. Various neural pattern recognition models are analyzed. Special emphasis is placed on stable self-organization of pattern recognition and recall codes in unpredictable and noisy environments–notably by adaptive resonance theory models—and on how such codes direct attention toward predictively relevant combinations of features, while attenuating irrelevant background cues. Experimental data and theoretical predictions from cognitive psychology, neuropsychology, and neurophysiology of normal and abnormal individuals are analyzed. 4 cr.
CAS CN 560 Neural and Computational Models of Speech Perception and Production
Prereq: CAS CN 510 or consent of instructor. Develops neural network models of speech perception and production processes. Emphasis is placed on the role of learning and on the specialized neural designs that have evolved for purposes of speech communication. Practical, including industrial, applications of neural networks for speech processing are also reviewed. Meets with ENG BE 509. 4 cr.
CAS CN 570 Neural and Computational Models of Conditioning, Reinforcement, Motivation, and Rhythm
Prereq: 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. 4 cr.
CAS CN 580 Introduction to Computational Neuroscience
Prereq: senior standing in a mathematics or natural science department or consent of instructor. This introductory-level course focuses on building a background in neuroscience, but with emphasis on computational approaches. Topics include basic biophysics of ion channels, Hodgkin-Huxley theory, use of stimulators such as NEURON and GENESIS, recent applications of the compartmental modeling technique, and a survey of neuronal architectures of the retina, cerebellum, basal ganglia, and neocortex. 4 cr.
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One Silber Way
Boston, MA 02215
16 October 2009
Boston University
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