Department of Cognitive & Neural Systems

The following list reflects the 2007/2008 faculty.

Chair Ennio Mingolla

Director of Graduate Studies Barbara Shinn-Cunningham

Faculty

Daniel H. Bullock Professor of Cognitive & Neural Systems and Psychology, College of Arts & Sciences. BA, Reed College; PhD, Stanford University

Yongqiang Cao Research Assistant Professor, Department of Cognitive & Neural Systems, College of Arts & Sciences. BS, Peking University, Beijing (China); MS, University of Technology, Dalian (China); PhD, York University, Toronto (Canada)

Gail A. Carpenter Professor of Cognitive & Neural Systems and Mathematics, College of Arts & Sciences. BA, University of Colorado; MA, PhD, University of Wisconsin, Madison

Michael A. Cohen Associate Professor of Cognitive & Neural Systems and Computer Science, College of Arts & Sciences. SB, Massachusetts Institute of Technology; PhD, Harvard University

Stephen Grossberg Director, Center for Adaptive Systems; Director, Center of Excellence for Learning in Education, Science & Technology (CELEST); Wang Professor of Cognitive & Neural Systems, College of Arts & Sciences; Professor of Mathematics, Psychology, and Biomedical Engineering. BA, Dartmouth College; MS, Stanford University; PhD, Rockefeller University

Frank Guenther Associate Professor of Cognitive & Neural Systems, College of Arts & Sciences. BS, University of Missouri, Columbia; MSE, Princeton University; PhD, Boston University

Ennio Mingolla Chair, Department of Cognitive & Neural Systems; Professor of Cognitive & Neural Systems and Psychology, College of Arts & Sciences. BA, Harvard University; MEd, Boston University; PhD, University of Connecticut

Michele Rucci Assistant Professor of Cognitive & Neural Systems, College of Arts & Sciences. BA, MA, University of Florence, Firenze (Italy); PhD, Scuola Superiore, Pisa (Italy)

Eric Schwartz Professor of Cognitive & Neural Systems, College of Arts & Sciences. Electrical, Computer, and Systems Engineering, College of Engineering. Anatomy and Neurobiology, School of Medicine. AB, Columbia College; MS, PhD, Columbia University

Barbara Shinn-Cunningham Director of Graduate Studies, Department of Cognitive & Neural Systems; Associate Professor of Cognitive & Neural Systems, College of Arts & Sciences; Associate Professor of Biomedical Engineering, College of Engineering. ScB, Brown University; MS, PhD, Massachusetts Institute of Technology

Arash Yazdanbakhsh Research Assistant Professor, Department of Cognitive & Neural Systems, College of Arts & Sciences. MD, Tehran University of Medical Sciences (Iran); PhD, Boston University

Research Staff

Mukund Balasubramanian Research Associate, Department of Cognitive & Neural Systems, College of Arts & Sciences. BA, BS, University of Texas at Austin; PhD, Boston University

Virginia Best Research Associate, Department of Cognitive & Neural Systems, College of Arts & Sciences. BMS, PhD, University of Sydney (Australia)

Arash Fazl Research Associate, Department of Cognitive & Neural Systems, College of Arts & Sciences. MD, Tehran University of Medical Sciences (Iran); PhD, Boston University

Daniel Franklin CELEST Director of Curriculum Development, Department of Cognitive & Neural Systems, College of Arts & Sciences. BA, Williams College; MTS, Harvard University; MBA, Boston University

Satrajit Ghosh Research Fellow, Department of Cognitive & Neural Systems, College of Arts & Sciences. BS, National University of Singapore; PhD, Boston University

Anatoli Gorchetchnikov Research Associate, Department of Cognitive & Neural Systems, College of Arts & Sciences. BS, Belmont University; MS, Middle Tennessee State University; PhD, Boston University

Sadao Hiroya Research Fellow, Department of Cognitive & Neural Systems, College of Arts & Sciences. BS, Tokyo University of Science; ME, PhD, Tokyo Institute of Technology (Japan)

Norbert Kopco Research Associate, Department of Cognitive & Neural Systems, College of Arts & Sciences. MSc (Dipl Ing), Technicka Univerzita, Kosice (Slovakia); PhD, Boston University

Sulochana Naidoo Research Associate, Department of Cognitive & Neural Systems, College of Arts & Sciences. BS, University of Durban-Westville (South Africa); MS, Boston University; PhD, Boston University School of Medicine

Simon Overduin Research Associate, Department of Cognitive & Neural Systems, College of Arts & Sciences. BSc, Wilfrid Laurier University (Canada); PhD, Massachusetts Institute of Technology

Jonathan Polimeni Research Fellow, Department of Cognitive & Neural Systems, College of Arts & Sciences. BS, Johns Hopkins University; PhD, Boston University

Fabrizio Santini Research Associate, Department of Cognitive & Neural Systems, College of Arts & Sciences. MS, University of Rome, La Sapienza, Rome (Italy); PhD, University of Florence (Italy)

Timothy Streeter Research Associate, Department of Speech, Language & Hearing Sciences, Sargent College of Health & Rehabilitation Sciences. BS, MS, University of New Hampshire; MA, Boston University

Massimiliano Versace Assistant Director, CNS Technology Lab for Science & Technology Outreach, Department of Cognitive & Neural Systems, College of Arts & Sciences. BA/MA, University of Trieste (Italy); PhD, Boston University

Tony Vladusich Research Associate, Department of Cognitive & Neural Systems, College of Arts & Sciences. BS, University of Queensland (Australia); PhD, Australian National University

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Affiliated Faculty

Jelle Atema Professor of Biology, College of Arts & Sciences. Candidate, Doctorandus, Rijksuniversiteit te Utrecht (Netherlands); PhD, University of Michigan

Helen Barbas Professor of Health Sciences, Sargent College. BA, Kean College; MS, Kansas State University; PhD, McGill University (Canada)

Catherine Caldwell-Harris Associate Professor of Psychology, College of Arts & Sciences. BA, Harvard University; PhD, University of California, San Diego

H. Steven Colburn Director, Hearing Research Center; Professor of Biomedical Engineering, College of Engineering. SB, SM, PhD, Massachusetts Institute of Technology

Howard Eichenbaum Director, Center for Memory & Brain; Director, Cognitive Neurobiology Laboratory; Director, Center for Neuroscience; University Professor. Professor of Psychology, College of Arts & Sciences. BS, PhD, University of Michigan

William D. Eldred III Professor of Biology, College of Arts & Sciences. BS, PhD, University of Colorado

Jean Berko Gleason Professor Emerita of Psychology, College of Arts & Sciences. AB, Radcliffe College; AM, PhD, Harvard University

Sucharita Gopal Professor of Geography & Environment, College of Arts & Sciences. BA, MSc, BEd, MPhil, Madras University (India); PhD, University of California, Santa Barbara

Michael E. Hasselmo Professor of Psychology, College of Arts & Sciences. AB, Harvard University; PhD, Oxford University (England)

Allyn Hubbard Professor of Electrical & Computer Engineering, College of Engineering. BS, MS, PhD, University of Wisconsin

Dae-Shik Kim Director, Center for Biomedical Imaging. Associate Professor of Anatomy and Neurobiology, School of Medicine. BA/BS, Technical University of Darmstadt (Germany); MA, PhD, Max-Planck-Institute for Brain Research (Germany)

Thomas Kincaid Professor of Electrical, Computer, and Systems Engineering, College of Engineering. BS, Queen’s University (Canada); SM, PhD, Massachusetts Institute of Technology

Mark Kon Professor of Mathematics & Statistics, College of Arts & Sciences. BA, Cornell University; PhD, Massachusetts Institute of Technology

Nancy Kopell Professor of Mathematics & Statistics, College of Arts & Sciences. BA, Cornell University; MA, PhD, University of California, Berkeley

Jacqueline A. Liederman Professor of Psychology, College of Arts & Sciences. BA, City College of New York; PhD, University of Rochester

Margaret Livingstone Adjunct Professor of Cognitive & Neural Systems, College of Arts & Sciences; Professor of Neurobiology, Harvard Medical School. BS, Massachusetts Institute of Technology; PhD, Harvard University

Joseph Perkell Adjunct Professor of Cognitive & Neural Systems, College of Arts & Sciences. Senior Research Scientist, Research Lab of Electronics and Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology. SB, Massachusetts Institute of Technology; DMD, Harvard School of Dental Medicine; PhD, Massachusetts Institute of Technology

Marc Pomplun Adjunct Associate Professor of Cognitive & Neural Systems; Director, Visual Attention Laboratory; Associate Professor of Computer Science, University of Massachusetts Boston. Vordiplom, Diplom, PhD, University of Bielefeld (Germany)

Adam Reeves Adjunct Professor of Cognitive & Neural Systems, College of Arts & Sciences; Professor of Psychology, Northeastern University. BA, PhD, City University of New York

Elliot L. Saltzman Associate Professor of Physical Therapy, Sargent College. AB, Harvard University; PhD, University of Minnesota

Robert Savoy Adjunct Associate Professor of Cognitive & Neural Systems, College of Arts & Sciences; President, HyperVision Incorporated; Assistant in Experimental Psychology, Director of fMRI Education, Instructor, Department of Radiology, Harvard Medical School. BS, MS, Massachusetts Institute of Technology; PhD, Harvard University

Robert Sekuler Adjunct Professor of Cognitive & Neural Systems, College of Arts & Sciences; Professor of Cognitive Neuroscience, Frances and Louis H. Salvage Professor of Psychology, Brandeis University. AB, Brandeis University; MS, PhD, Brown University

David Somers Associate Professor of Psychology, College of Arts & Sciences. BS, Harvey Mudd College; PhD, Boston University

Chantal Stern Director, Brain, Behavior & Cognition Program. Associate Professor of Psychology and Program in Neuroscience, College of Arts & Sciences. BA, McGill University (Canada); DPhil, University of Oxford (England)

Malvin C. Teich Professor of Electrical & Computer Engineering and Biomedical Engineering, College of Engineering. SB, Massachusetts Institute of Technology; MS, Stanford University; PhD, Cornell University

Joe Z. Tsien Professor of Pharmacology, School of Medicine; Professor of Biomedical Engineering, College of Engineering. BS, East China Normal University; PhD, University of Minnesota

Lucia Vaina Professor of Biomedical Engineering, College of Engineering; Research Professor of Neurology, School of Medicine. MS, University of Timisoara (Romania) and Urbino (Italy); PhD, Université Paris I (France); Dres Science, Institut National Polytechnique (France)

Takeo Watanabe Professor of Psychology, College of Arts & Sciences. BA, MA, PhD, University of Tokyo (Japan)

Jeremy Wolfe Adjunct Professor of Cognitive & Neural Systems, College of Arts & Sciences; Professor of Ophthalmology, Harvard Medical School; Psychophysicist, Brigham & Women’s Hospital; Director of Psychophysical Studies, Center for Clinical Cataract Research. AB, Princeton University; PhD, Massachusetts Institute of Technology

Curtis E. Woodcock Professor, Department of Geography & Environment; Director of Geographic Applications, Center for Remote Sensing, College of Arts & Sciences. BA, MA, PhD, University of California, Santa Barbara

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The Department of Cognitive & Neural Systems (CNS)

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. The department’s training and research focus on two broad questions. The first question is: How does the brain control behavior? This is a modern form of the Mind/Body Problem. The second question is: How can technology emulate biological intelligence? This question needs to be answered to develop intelligent technologies that are well suited to human societies. These goals are symbiotic because brains are unparalleled in their ability to intelligently adapt on their own to complex and novel environments. Models of how the brain accomplishes this are developed through systematic empirical, mathematical, and computational analysis in the department. Autonomous adaptation to a changing world is also needed to solve many of the outstanding problems in technology, and the biological models have inspired qualitatively new designs for applications. CNS is a world leader in developing biological models that can quantitatively simulate the dynamics of identified brain cells in identified neural circuits, and the behaviors that they control. This new level of understanding is leading to comparable advances in intelligent technology.

CNS is a graduate department that is devoted to the interdisciplinary training of graduate students. The department awards MA, PhD, and BA/MA degrees. Its students are trained in a broad range of areas concerning computational neuroscience, cognitive science, and neuromorphic systems. The biological training includes 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.

The foundation of this broad training is the unique interdisciplinary curriculum of seventeen interdisciplinary graduate courses that have been developed at CNS. Each of these courses integrates the psychological, neurobiological, mathematical, and computational information needed to theoretically investigate fundamental issues concerning mind and brain processes and the applications of artificial neural networks and hybrid systems to technology. A student’s curriculum is tailored to his or her career goals with academic and research advisors. In addition to taking interdisciplinary courses within CNS, students develop important disciplinary expertise by also taking courses in departments such as biology, computer science, engineering, mathematics, and psychology. In addition to these formal courses, students work individually with one or more research advisors to learn how to carry out advanced interdisciplinary research in their chosen research areas. As a result of this breadth and depth of training, CNS students have succeeded in finding excellent jobs in both academic and technological areas after graduation.

The CNS department interacts with colleagues in several Boston University research centers and with Boston-area scientists collaborating with these centers. The units most closely linked to the department are the Center for Adaptive Systems and the CNS Technology Laboratory. CNS is also part of a major new NSF Center of Excellence for Learning in Education, Science, and Technology (CELEST); see www.cns.bu.edu/CELEST. Students interested in neural network hardware can work with researchers in CNS and at the College of Engineering. In particular, CNS is part of a major ONR MURI Center for Intelligent Biomimetic Image Processing and Classification that includes colleagues who are developing neuromorphic VLSI chips. Other research resources include the campus-wide Program in Neuroscience, which unites cognitive neuroscience, neurophysiology, neuroanatomy, neuropharmacology, and neural modeling across the Charles River Campus and the School of Medicine; in sensory robotics, biomedical engineering, computer and systems engineering, and neuromuscular research within the College of Engineering; in dynamical systems within the Department of Mathematics; in theoretical computer science within the Department of Computer Science; and in biophysics and computational physics within the Department of Physics. Key colleagues in these units hold joint appointments in CNS in order to expedite training and research interactions with CNS core faculty and students.

In addition to its basic research and training program, the department organizes an active colloquium series, various research and seminar series, and international conferences and symposia, to bring distinguished scientists from experimental, theoretical, and technological disciplines to the department.

The department is housed in its own four-story building, which includes ample space for faculty and student offices and laboratories (active perception, auditory neuroscience, computer vision and computational neuroscience, sensory-motor control, speech and language, technology, and visual psychophysics), as well as an auditorium, classroom, seminar rooms, a library, and a faculty-student lounge. The department has a powerful computer network for carrying out large-scale simulations of behavioral and brain models and applications.

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Laboratory and Computer Facilities

The department is funded by fellowships, grants, and contracts from federal agencies and private foundations that support research in life sciences, mathematics, artificial intelligence, and engineering. Facilities include laboratories for experimental research and computational modeling in visual perception; audition, speech, and language processing; sensory-motor control and robotics; and technology transfer. Data analysis and numerical simulations are carried out on a state-of-the-art computer network comprised of Sun workstations, Macintoshes, and both 32-bit and 64-bit PCs. A PC farm running BU’s own version of Linux (BU Linux v4.6 based on Fedora Core 3) is available as a distributed computational environment. All students have department-supplied PCs on their desktops (running either Microsoft Windows XP Pro or BU Linux) allowing them to run their simulations either locally or remotely on one of the department’s workstations. Mathematical simulation and modeling are carried out using standard software packages such as Mathematica or Matlab, as well as SPlus and VisSim.

The department maintains a core collection of books and journals, and has access both to the Boston University libraries and to the many other collections of the Boston Library Consortium.

In addition, several specialized facilities and software are available for use. These include:

Active Perception Laboratory Models of the visual system often examine steady-state levels of neural activity during presentations of visual stimuli. It is difficult, however, to envision how such steady-states could occur under natural viewing conditions, given that the projection of the visual scene on the retina is never stationary. The Active Perception Laboratory is dedicated to the investigation of the interactions between visual perception and behavior. Research focuses on the theoretical and computational analysis of the influences of motor activity on the sampling and representation of visual information, the coupling of models of neuronal systems with robotic systems, and the design of psychophysical experiments with human subjects. The Active Perception Laboratory includes extensive computational facilities that allow the execution of large-scale simulations of neural systems. Additional facilities include instruments for the psychophysical investigation of eye movements during visual analysis, including an accurate and non-invasive eye tracker, and robotic systems for the simulation of different types of behavior. The Active Perception Laboratory hosts “Mr. T,” a humanoid robot with two 6-degrees-of-freedom arms and a head/eye system designed to replicate visual input signals to the human eye.

Auditory Neuroscience Laboratory The Auditory Neuroscience Laboratory in the Department of Cognitive & Neural Systems (CNS) is an experimental and theoretical laboratory focused on auditory perception, particular spatial auditory perception, plasticity, and attention. The laboratory contains numerous PCs used both as workstations for students to model and analyze data and to control laboratory equipment and run experiments. The other major equipment in the laboratory includes special-purpose signal processing and sound generating equipment, electromagnetic head-tracking systems, a two-channel spectrum analyzer, and other miscellaneous equipment for producing, measuring, analyzing, and monitoring auditory stimuli. The Auditory Neuroscience Laboratory consists of three adjacent rooms in the basement of 677 Beacon Street (the home of the CNS department). One room houses an 8 ft. by 8 ft. single-walled sound-treated booth as well as space for students. The second room is primarily used as student workspace for developing and debugging experiments. The third space houses a robotic arm, capable of automatically positioning a small acoustic speaker anywhere on the surface of a sphere of adjustable radius, allowing automatic measurement of the signals reaching the ears of a listener for a sound source from different positions in space, including the effects of room reverberation.

Computer Vision & Computational Neuroscience Laboratory The Computer Vision & Computational Neuroscience Laboratory is comprised of an electronics workshop, including a surface-mount workstation, PCD fabrication tools, and an Alterra EPLD design system; an active vision laboratory including actuators and video hardware; and systems for computer-aided neuroanatomy and application of computer graphics and image processing to brain sections and MRI images. The laboratory supports research in the areas of neural modeling, computational neuroscience, computer vision, robotics, and fMRI imaging. The major question being addressed is the nature of representation of the visual world in the brain, in terms of observable neural architectures such as topographic mapping and columnar architecture. The application of novel architectures for image processing for computer vision and robotics is also a major topic of interest. Recent work in this area has included the design and patenting of novel actuators for robotic active vision systems, the design of real-time algorithms for use in mobile robotic applications, and the design and construction of miniature autonomous vehicles using space-variant active vision design principles. Recently one such vehicle has successfully driven itself on the streets of Boston. Applications of fMRI imaging to measuring the topographic structure of human primary and extra-striate visual cortex are a current focus of research.

Sensory-Motor Control Laboratory The Sensory-Motor Control Laboratory supports experimental studies of sensory-motor behavior and computational studies of neural circuits that enable learned voluntary action. Equipment includes a computer-controlled, helmet-mounted, video-based, eye-head tracking system. The latter’s camera samples eye position at 240Hz and also allows reconstruction of what subjects are attending to as they freely scan a scene under normal lighting. Thus the system affords a wide range of visuo-motor studies. To facilitate computational studies, the laboratory is connected to the Department’s and University’s extensive network of Linux and Windows workstations and Linux computational servers.

Speech & Language Laboratory The Speech & Language Laboratory includes facilities for analog-to-digital and digital-to-analog software conversion. Ariel equipment allows reliable synthesis and playback of speech waveforms. An Entropic signal-processing package provides facilities for detailed analysis, filtering, spectral construction, and formant tracking of the speech waveform. Various large databases, such as TIMIT and TIdigits, are available for testing algorithms of speech recognition. The laboratory also contains a network of Windows-based PC computers equipped with software for the analysis of functional magnetic resonance imaging (fMRI) data, including region-of-interest (ROI) based analyses involving software for the parcellation of cortical and subcortical brain regions in structural MRI images.

Technology Laboratory The Technology Laboratory fosters the development of neural network models derived from basic scientific research, and facilitates the transition of the resulting technologies to software and applications. The Lab was established in 2001, with a grant from the Air Force Office of Scientific Research: “Information Fusion for Image Analysis: Neural Models and Technology Development.” Current projects include multi-level fusion and data mining in a geospatial context, in collaboration with the Boston University Center for Remote Sensing; and medical image analysis, in collaboration with the Center for Biomedical Imaging at the Boston University Medical Center. This research and development effort builds on models of opponent-color visual processing, contour and texture processing, and Adaptive Resonance Theory (ART) pattern learning and recognition, as well as other models of vision, associative learning, and prediction. Additional projects include collaborations with the Harvard Medical School, to develop methods for analysis of large-scale medical databases, currently to predict HIV resistance to antiretroviral therapy; and with HRL (formerly Hughes Research Laboratories), to develop robotic platforms. Associated basic research projects are conducted within the joint context of scientific data and technological constraints. Emerging neural network technologies are embedded in the CNS Image Processing Toolkit and the CNS Neural Classifier Toolkit. Software, articles, and educational materials are available through the CELEST Technology website, a growing resource for the NSF Center for Excellence for Learning in Education, Science, and Technology.

Visual Psychophysics Laboratory The Visual Psychophysics Laboratory includes a group of faculty and graduate students that conducts psychophysical and computational modeling studies of many aspects of visual perception, including motion perception, shape-from-texture, contour extraction, and visual navigation. See: http://cns.bu.edu/vislab. The laboratory occupies an 800-square-foot suite, including three dedicated rooms for data collection, and houses a variety of computer-controlled display platforms, including Macintosh, Windows, and Linux workstations. Ancillary resources for visual psychophysics include a computer-controlled video camera, stereo viewing devices, a photometer, and a variety of display-generation, data-collection, and data-analysis software.

Affiliated Laboratories Affiliated CAS/CNS faculty members have additional laboratories ranging from visual and auditory psychophysics and neurophysiology, anatomy, and neuropsychology to engineering and chip design. These facilities are used in the context of faculty/student collaborations.

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Admissions

Prospective applicants are urged to write directly to the department at the following address: Department of Cognitive & Neural Systems, 677 Beacon Street, Boston University, Boston, MA 02215; 617-353-9481; fax: 617-353-7755; e-mail: inquiries@cns.bu.edu. A copy of the program brochure will be sent to the applicant.

To obtain application materials, write to the Admissions Office, Graduate School of Arts & Sciences, Boston University, 705 Commonwealth Avenue, Boston, MA 02215; 617-353-2696. Applications should be received by the Graduate School admissions office no later than January 15. Late applications will be considered until April 15; after that date applications will be considered only as special cases. Under certain circumstances, January admission may be possible, with an application deadline of October 15.

Applicants are required to submit undergraduate (and, if applicable, graduate) transcripts, three letters of recommendation, and Graduate Record Examination (GRE) scores. GRE scores may be waived for MA candidates and, in exceptional cases, for PhD candidates, but absence of these scores may decrease an applicant’s chances for admission and financial aid.

Completed applications are to be mailed to the Graduate School admissions office.

MA in Cognitive & Neural Systems

Course Requirements MA students are required to complete eight semester courses (32 credits), at least six of which must be from the CNS curriculum. The remaining courses may be selected, with approval of the student’s faculty advisor, from other CNS courses and from courses offered by the departments of biology, physiology, medicine, computer science, engineering, mathematics, statistics, physics, and psychology.

MA Comprehensive Examination The MA examination is offered each year in January and in May. A student must have passed at least four 500-level courses in the CNS curriculum to take the MA examination.

PhD in Cognitive & Neural Systems

Course Requirements PhD students are required to complete at least 16 semester courses (64 credits) as follows: at least ten courses chosen from the CNS department’s curriculum, of which at least two must be 700- or 800-level courses, with the remaining courses chosen to form a coherent area of expertise. The latter courses will be selected in consultation with the student’s faculty advisor.

Students who enter the PhD program with a master’s degree in biology, physiology, medicine, computer science, engineering, mathematics, statistics, physics, or psychology are required to take eight courses (32 credits) chosen from the CNS department’s curriculum, at least two of which must be 700- or 800-level courses, and to fulfill all other program requirements.

PhD Qualifying Examinations Students are required to pass a qualifying examination on the CNS curriculum. The examination is offered each year in January and in May. A student must have passed eight courses in the CNS curriculum to take the PhD qualifying examination.

Dissertation Requirements Before finalizing dissertation plans, students are required to submit a written prospectus. A dissertation and final oral examination must be completed in accordance with the general requirements for the PhD as outlined in the Admission; Policies and Procedures section of this website.

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 majors 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 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, Room 112, 705 Commonwealth Avenue, Boston, MA 02215.

Requirements Students must complete all requirements for the BA in Biology 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.

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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 majors 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 CNS course. The application should include a letter from the student’s Computer Science Department advisor. Application forms for admission to the BA/MA program may be obtained from the Graduate School of Arts & Sciences Office, Room 112, 705 Commonwealth Avenue, Boston, MA 02215.

Requirements Students are required to complete all requirements for the BA in Computer Science 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.

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 majors in mathematics to begin working toward an MA in Cognitive & Neural Systems while still completing the BA requirements in the Department of Mathematics.

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 CNS course. The application should include a letter from the student’s Mathematics Department advisor. Application forms for admission to the BA/MA program may be obtained from the Graduate School of Arts & Sciences Office, Room 112, 705 Commonwealth Avenue, Boston, MA 02215.

Requirements Students are required to complete all requirements for the BA in Mathematics 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.

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 majors in psychology to begin working toward an MA in Cognitive & Neural Systems while still completing the 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 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 Psychology advisor. Application forms for admission to the BA/MA program may be obtained from the Graduate School of Arts & Sciences Office, Room 112, 705 Commonwealth Avenue, Boston, MA 02215.

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 and 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.

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Course Offerings

CAS CN 500 Computational Methods in cognitive and Neural Systems

CAS CN 510 Principles and Methods of Cognitive and Neural Modeling I

CAS CN 520 Principles and Methods of Cognitive and Neural Modeling II

CAS CN 530 Neural and Computational Models of Vision

CAS CN 540 Neural and Computational Models of Adaptive Movement Planning and Control

CAS CN 550 Neural and Computational Models of Recognition, Memory, and Attention

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CAS CN 560 Neural and Computational Models of Speech Perception and Production

CAS CN 570 Neural and Computational Models of Conditioning, Reinforcement, Motivation, and Rhythm

CAS CN 580 Introduction to Computational Neuroscience

GRS CN 699 Teaching College Cognitive & Neural Systems I

GRS CN 700 Computational and Mathematical Methods in Neural Modeling

GRS CN 710 Advanced Topics in Neural Modeling

GRS CN 720 Neural and Computational Models of Planning and Temporal Structure in Behavior

GRS CN 730 Models of Visual Perception

GRS CN 740 Topics in Sensory Motor Control

GRS CN 760 Topics in Speech Perception and Recognition

GRS CN 780 Topics in Computational Neuroscience

GRS CN 810 Topics in Cognitive & Neural Systems: Visual Event Perception

GRS CN 811 Topics in Cognitive & Neural Systems: Visual Perception

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Research in Cognitive & Neural Systems

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12 January 2009
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