Graduate training at BU CNS Department

[Boston University CNS Department]

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GRADUATE TRAINING IN THE
DEPARTMENT OF COGNITIVE AND NEURAL SYSTEMS (CNS)
AT BOSTON UNIVERSITY
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The Boston University Department of Cognitive and Neural Systems offers comprehensive graduate training 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 brochure may also be viewed on line at:

http://www.cns.bu.edu/brochure/

and application forms at:

http://www.bu.edu/cas/graduate/application. html

Applications for Fall 2002 admission and financial aid are now being accepted for both the MA and PhD degree programs.

To obtain a brochure describing the CNS Program and a set of application materials, write, telephone, or fax:

DEPARTMENT OF COGNITIVE AND NEURAL SYSTEMS
Boston University
677 Beacon Street
Boston, MA 02215

617/353-9481 (phone)
617/353-7755 (fax)

or send via email your full name and mailing address to the attention of Mr. Robin Amos at:

[EMAIL PROTECTED]

                                         
Applications for admission and financial aid should be received by the Graduate School Admissions Office no later than January 15.  Late applications will be considered until May 1; after that date applications will be considered only as special cases.

Applicants are required to submit undergraduate (and, if applicable, graduate) transcripts, three letters of recommendation, and Graduate Record Examination (GRE) scores. The Advanced Test should be in the candidate's area of departmental specialization. GRE scores may be waived for MA candidates and, in exceptional cases, for PhD candidates, but absence of these scores will decrease an applicant's chances for admission and financial aid.

Non-degree students may also enroll in CNS courses on a part-time basis.

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Description of the CNS Department:

The Department of Cognitive and 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. During the past decade, CNS has led the way 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 an academic and a research adviser. 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 do 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 or groups, 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. Students interested in neural network hardware can work with researchers in CNS and at the College of Engineering. Other research resources include the campus-wide Program in Neuroscience, which includes distinguished research groups in cognitive neuroscience, neurophysiology, neuroanatomy, neuropharmacology, and neural modeling across the Charles River Campus and the Medical School; in sensory robotics, biomedical engineering, computer and systems engineering, and neuromuscular research within the College of Engineering; in dynamical systems within the Mathematics Department; in theoretical computer science within the Computer Science Department ; and in biophysics and computational physics within the Physics Department.  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 (computational neuroscience, visual psychophysics, psychoacoustics, speech and language, sensory-motor control, neurobotics, computer vision), 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.

Below are listed departmental faculty, courses and labs.

FACULTY AND STAFF OF THE DEPARTMENT OF COGNITIVE AND NEURAL SYSTEMS
AND CENTER FOR ADAPTIVE SYSTEMS

Jelle Atema
Professor of Biology
Director, Boston University Marine Program (BUMP)
PhD, University of Michigan
Sensory physiology and behavior

Helen Barbas
Professor, Department of Health Sciences, Sargent College
PhD, Physiology/Neurophysiology, McGill University
Organization of the prefrontal cortex, evolution of the neocortex

Jacob Beck
Research Professor of Cognitive and Neural Systems
PhD, Psychology, Cornell University
Visual perception, psychophysics, computational models of vision

Neil Bomberger
Research Associate, CNS Technology Laboratory, Department of Cognitive and Neural Systems
PhD, Cognitive and Neural Systems, Boston University

Daniel H. Bullock
Associate Professor of Cognitive and Neural Systems, and Psychology
PhD, Experimental Psychology, Stanford University
Sensory-motor performance and learning, voluntary control of action, serial order and timing, cognitive development

Val Bykoski
Research Associate, CNS Technology Laboratory, Department of Cognitive and Neural Systems
PhD, Applied Mathematics and Physics, The Russian Academy, Moscow, Russia

Gail A. Carpenter
Professor of Cognitive and Neural Systems and Mathematics
Director of Graduate Studies, Department of Cognitive and Neural Systems
PhD, Mathematics, University of Wisconsin, Madison
Learning and memory, synaptic processes, pattern recognition, remote sensing, medical database analysis, machine learning, differential equations

Michael A. Cohen
Associate Professor of Cognitive and Neural Systems and Computer Science
PhD, Psychology, Harvard University
Speech and language processing, measurement theory, neural modeling, dynamical systems, cardiovascular oscillations physiology and time series

H. Steven Colburn
Professor of Biomedical Engineering
PhD, Electrical Engineering, Massachusetts Institute of Technology
Audition, binaural interaction, auditory virtual environments, signal processing models of hearing

Howard Eichenbaum
Professor of Psychology
PhD, Psychology, University of Michigan
Neurophysiological studies of how the hippocampal system mediates declarative memory

William D. Eldred III
Professor of Biology
PhD, University of Colorado, Health Science Center
Visual neuralbiology

David Fay
Research Associate, Department of Cognitive and Neural Systems
Assistant Director, CNS Technology Laboratory
MA, Cognitive and Neural Systems, Boston University

John C. Fiala
Research Assistant Professor of Biology
PhD, Cognitive and Neural Systems, Boston University
Synaptic plasticity, dendrite anatomy and pathology, motor learning, robotics, neuroinformatics

Jean Berko Gleason
Professor of Psychology
PhD, Harvard University
Psycholinguistics

Sucharita Gopal
Associate Professor of Geography
PhD, University of California at Santa Barbara
Neural networks, computational modeling of behavior, geographical information systems, fuzzy sets, and
spatial cognition

Stephen Grossberg
Wang Professor of Cognitive and Neural Systems
Professor of Mathematics, Psychology, and Biomedical Engineering
Chairman, Department of Cognitive and Neural Systems
Director, Center for Adaptive Systems
PhD, Mathematics, Rockefeller University
Vision, audition, language, learning and memory, reward and motivation, cognition, development,
sensory-motor control, mental disorders, applications

Frank Guenther
Associate Professor of Cognitive and Neural Systems
PhD, Cognitive and Neural Systems, Boston University
MSE, Electrical Engineering, Princeton University
Speech production, speech perception, biological sensory-motor control and functional brain imaging

Catherine L. Harris
Assistant Professor of Psychology
PhD, Cognitive Science and Psychology, University of California at San Diego
Visual word recognition, psycholinguistics, cognitive semantics, second language acquisition,
computational models of cognition

Michael E. Hasselmo
Associate Professor of Psychology
Director of Graduate Studies, Psychology Department
PhD, Experimental Psychology, Oxford University
Computational modeling and experimental testing of neuromodulatory mechanisms involved in encoding,
retrieval and consolidation

Allyn Hubbard
Associate Professor of Electrical and Computer Engineering
PhD, Electrical Engineering, University of Wisconsin
Peripheral auditory system (experimental and modeling), chip design spanning the range from
straightforward digital applications to exotic sub-threshold analog circuits that emulate the
functionality of the visual and auditory periphery, BCS/FCS, the mammalian cochlea in silicon and MEMS,
and drug discovery on silicon

Richard Ivey
Research Associate, CNS Technology Laboratory, Department of Cognitive and Neural Systems
MA, Cognitive and Neural Systems, Boston University

Thomas G. Kincaid
Professor of Electrical, Computer and Systems Engineering, College of Engineering
PhD, Electrical Engineering, Massachusetts Institute of Technology
Signal and image processing, neural networks, non-destructive testing

Mark Kon
Professor of Mathematics
PhD, Massachusetts Institute of Technology
Neural network theory, complexity theory, wavelet theory, mathematical physics

Nancy Kopell
Professor of Mathematics
PhD, Mathematics, University of California at Berkeley
Dynamics of networks of neurons

Jacqueline A. Liederman
Associate Professor of Psychology
PhD, Psychology, University of Rochester
Dynamics of interhemispheric cooperation; prenatal correlates of neurodevelopmental disorders

Ennio Mingolla
Professor of Cognitive and Neural Systems and Psychology
PhD, Psychology, University of Connecticut
Visual perception, mathematical modeling of visual processes

Joseph Perkell
Adjunct Professor of Cognitive and Neural Systems
Senior Research Scientist, Research Lab of Electronics and Department of Brain and Cognitive Sciences,
Massachusetts Institute of Technology
PhD, Massachusetts Institute of Technology
Motor control of speech production

Adam Reeves
Adjunct Professor of Cognitive and Neural Systems
Professor of Psychology, Northeastern University
PhD, Psychology, City University of New York
Psychophysics, cognitive psychology, vision

Michele Rucci
Assistant Professor of Cognitive and Neural Systems
PhD, Scuola Superiore S.-Anna, Pisa, Italy
Vision, sensory-motor control and learning, and computational neuroscience

Elliot Saltzman
Associate Professor of Physical Therapy, Sargent College
Research Scientist, Haskins Laboratories, New Haven, CT
Assistant Professor in Residence, Department of Psychology and Center for the
Ecological Study of Perception and Action, University of Connecticut, Storrs, CT
PhD, Developmental Psychology, University of Minnesota
Modeling and experimental studies of human sensorimotor control and coordination of the limbs and speech
articulators, focusing on issues of timing in skilled activities

Robert Savoy
Adjunct Associate Professor of Cognitive and Neural Systems
Scientist, Rowland Institute for Science
Experimental Psychologist, Massachusetts General Hospital
PhD, Experimental Psychology, Harvard University
Computational neuroscience; visual psychophysics of color, form, and motion perception
Teaching about functional MRI and other brain mapping methods

Eric Schwartz
Professor of Cognitive and Neural Systems; Electrical, Computer and Systems Engineering; and Anatomy and Neurobiology
PhD, High Energy Physics, Columbia University
Computational neuroscience, machine vision, neuroanatomy, neural modeling

Robert Sekuler
Adjunct Professor of Cognitive and Neural Systems
Research Professor of Biomedical Engineering, College of Engineering,
BioMolecular Engineering Research Center
Frances and Louis H. Salvage Professor of Psychology, Brandeis University
Consultant in neurosurgery, Boston Children's Hospital
PhD, Psychology, Brown University
Visual motion, brain imaging, relation of visual perception, memory, and movement

Barbara Shinn-Cunningham
Assistant Professor of Cognitive and Neural Systems and Biomedical Engineering
PhD, Electrical Engineering and Computer Science, Massachusetts Institute of Technology
Psychoacoustics, audition, auditory localization, binaural hearing, sensorimotor adaptation,
mathematical models of human performance

David Somers
Assistant Professor of Psychology
PhD, Cognitive and Neural Systems, Boston University
Functional MRI, psychophysical, and computational investigations of visual perception and attention

Chantal E. Stern
Assistant Professor of Psychology and Program in Neuroscience, Boston University
Assistant in Neuroscience, MGH-NMR Center and Harvard Medical School
PhD, Experimental Psychology, Oxford University
Functional neuroimaging studies (fMRI and MEG) of learning and memory

Malvin C. Teich
Professor of Electrical and Computer Engineering, Biomedical Engineering, and Physics
PhD, Cornell University
Quantum optics and imaging, photonics, wavelets and fractal stochastic processes, biological signal
processing and information transmission

Lucia Vaina
Professor of Biomedical Engineering
Research Professor of Neurology, School of Medicine
PhD, Sorbonne (France); Dres Science, National Politechnique Institute, Toulouse (France)
Computational visual neuroscience, biological and computational learning, functional and structural
neuroimaging

Takeo Watanabe
Associate Professor of Psychology
PhD, Behavioral Sciences, University of Tokyo
Perception of objects and motion and effects of attention on perception using psychophysics and brain
imaging (f-MRI)

Allen Waxman
Research Professor of Cognitive and Neural Systems
Director, CNS Technology Laboratory
Senior Staff Scientist, MIT Lincoln Laboratory
PhD, Astrophysics, University of Chicago
Visual system modeling, multisensor fusion, image mining, parallel computing, and advanced visualization

Jeremy Wolfe
Adjunct Associate Professor of Cognitive and Neural Systems
Associate Professor of Ophthalmology, Harvard Medical School
Psychophysicist, Brigham & Women's Hospital, Surgery Department
Director of Psychophysical Studies, Center for Clinical Cataract Research
PhD, Massachusetts Institute of Technology
Visual attention, pre-attentive and attentive object representation

Curtis Woodcock
Professor of Geography
Chairman, Department of Geography
Director, Geographic Applications, Center for Remote Sensing
PhD, University of California, Santa Barbara
Biophysical remote sensing, particularly of forests and natural vegetation, canopy reflectance models
and their inversion, spatial modeling, and change detection; biogeography; spatial analysis; geographic
information systems; digital image processing

CNS DEPARTMENT COURSE OFFERINGS

CAS CN500  Computational Methods in Cognitive and Neural Systems
CAS CN510  Principles and Methods of Cognitive and Neural Modeling I
CAS CN520  Principles and Methods of Cognitive and Neural Modeling II
CAS CN530  Neural and Computational Models of Vision
CAS CN540  Neural and Computational Models of Adaptive Movement Planning
                        and Control
CAS CN550  Neural and Computational Models of Recognition, Memory and Attention 
CAS CN560  Neural and Computational Models of Speech Perception and Production 
CAS CN570  Neural and Computational Models of Conditioning, Reinforcement,
                        Motivation and Rhythm
CAS CN580  Introduction to Computational Neuroscience 
GRS CN700  Computational and Mathematical Methods in Neural Modeling
GRS CN720  Neural and Computational Models of Planning and Temporal Structure
                        in Behavior 
GRS CN730  Models of Visual Perception 
GRS CN740  Topics in Sensory-Motor Control
GRS CN760  Topics in Speech Perception and Recognition 
GRS CN780  Topics in Computational Neuroscience 
GRS CN810  Topics in Cognitive and Neural Systems: Visual Event Perception
GRS CN811  Topics in Cognitive and Neural Systems: Visual Perception

GRS CN911,912
Research in Neural Networks for Adaptive Pattern Recognition
GRS CN915,916
Research in Neural Networks for Vision and Image Processing
GRS CN921,922
Research in Neural Networks for Speech and Language Processing
GRS CN925,926
Research in Neural Networks for Adaptive Sensory-Motor Planning
and Control
GRS CN931,932
Research in Neural Networks for Conditioning and Reinforcement Learning
GRS CN935,936
Research in Neural Networks for Cognitive Information Processing
GRS CN941,942
Research in Nonlinear Dynamics of Neural Networks
GRS CN945,946
Research in Technological Applications of Neural Networks
GRS CN951,952
Research in Hardware Implementations of Neural Networks

CNS students also take a wide variety of courses in related departments. In addition, students participate in a weekly colloquium series, an informal lecture series, and student-run special interest groups, and attend lectures and meetings throughout the Boston area; and advanced students work in small research groups.

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; and sensory-motor control and robotics. Data analysis and numerical simulations are carried out on a state-of-the-art computer network comprised of Sun workstations, Silicon Graphics workstations, Macintoshes, and PCs.  A PC farm running Linux operating systems is available as a distributed computational environment.  All students have access to X-terminals or UNIX workstation consoles, a selection of color systems and PCs, a network of SGI machines, and standard modeling and mathematical simulation packages such as Mathematica, VisSim, Khoros, and Matlab.

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
The Active Perception Laboratory is dedicated to the investigation of the interactions between perception and behavior. Research focuses on the theoretical and computational analyses of the effects of motor behavior on sensory perception and on 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 will soon 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.

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; a light machine shop; 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 and robotics. The major question being address 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.

Neurobotics Laboratory
The Neurobotics Laboratory utilizes wheeled mobile robots to study potential applications of neural networks in several areas, including adaptive dynamics and kinematics, obstacle avoidance, path planning and navigation, visual object recognition, and conditioning and motivation. The laboratory currently has three Pioneer robots equipped with sonar and visual sensors; one B-14 robot with a moveable camera, sonars, infrared, and bump sensors; and two Khepera miniature robots with infrared proximity detectors. Other platforms may be investigated in the future.

Psychoacoustics Laboratory
The Psychoacoustics Laboratory in the Department of Cognitive and Neural Systems (CNS) is equipped to perform both traditional psychoacoustic experiments as well as experiments using interactive auditory virtual-reality stimuli. The laboratory contains approximately eight PCs (running Windows 98 and/or Linux), used both as workstations for students and to control laboratory equipment and run experiments. The other major equipment in the laboratory includes special-purpose signal processing and sound generating equipment from Tucker-Davis Technologies, electromagnetic head tracking systems, a two-channel spectrum analyzer, and other miscellaneous equipment for producing, measuring, analyzing, and monitoring auditory stimuli. The Psychoacoustics Laboratory consists of three adjacent rooms in the basement of 677 Beacon St. (the home of the CNS Department). One room houses an 8 ft. ´ 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.

Sensory-Motor Control Laboratory
The Sensory-Motor Control Laboratory supports experimental and computational studies of sensory-motor control.  A computer controlled infrared WatSmart system allows measurement of large-scale (e.g. reaching) movements, and a pressure-sensitive graphics tablet allows studies of handwriting and other fine-scale movements.  A second major component is a helmet-mounted, video-based, eye-head tracking system (ISCAN Corp, 1997). 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.  The laboratory is connected to the department's extensive network of Linux and Windows workstations and Linux computational servers.

Speech and Language Laboratory
The Speech 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 Technology Laboratory was established in July 2001, with a five-year $2,500,000 grant from the Air Force Office of Scientific Research (AFOSR), "Information Fusion for Image Analysis:  Neural Models and Technology Development." Initial applied research projects are developing methods for multi-sensor data and information fusion, utilizing multi-spectral and high-resolution stereo imagery from satellites, in conjunction with simulated ELINT (emitter locator intelligence) and GMTI (ground moving target indicator) data and contextual terrain data. Fusion and data mining methods are being developed in a geospatial context, building on models of opponent-color visual processing, boundary contour system (BCS) and texture processing, Adaptive Resonance Theory (ART) pattern learning and recognition, and other models of associative learning and prediction. Multi-modality presentation of fused sensor data and information to human operators is studied in the context of a Common Operating Picture. A related defense application is real-time 3D fusion of low-light visible, thermal infrared, and ladar imagery, for advanced night vision systems incorporating target learning and search. Other research topics include multi-pass search by incorporation of feedback in the classification-to-search pathway for fused image mining, thereby treating classification decisions as context for further search, and multi-spectral MRI and multi-modality medical image fusion. Associated basic research projects are conducted within the joint context of scientific data and technological constraints. The laboratory effort also includes collaborative technology transfer to government laboratories and commercial industry. Under the sponsorship of the National Imagery and Mapping Agency (NIMA), software for multi-sensor image fusion and data mining is being incorporated into the commercial software suite Imagine by ERDAS Corporation. Related efforts aim to create a Matlab toolbox for interactive neural processing of imagery, signals, and patterns, and technology transfer into RSI/Kodak's ENVI software and the geospatial information software ArcGIS from ESRI Corporation.

The Director of the Technology Laboratory, Professor Allen Waxman, and the Assistant Director, David Fay, recently joined the CNS Department after collaborating for twelve years at MIT Lincoln Laboratory. The laboratory continues to grow rapidly, with three research associates, one postdoctoral fellow, and four graduate students, as well as faculty from CNS and the Center for Remote Sensing, currently associated with application, implementation, and basic and applied research projects. Dedicated equipment includes six high-end graphics PCs with dual-headed stereo monitors, two SGI O2 workstations, a Sun UltraSparc 10 workstation, a wall-sized stereo projection display system, a large Cybermation mobile robot, and CCD video cameras with real-time image acquisition and processing using Genesis DSP boards from Matrox. The Technology Laboratory occupies 1000 square feet in the CNS building, including a "dark room" for night vision research and a well-equipped conference room.

Visual Psychophysics Laboratory
The Visual Psychophysics 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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DEPARTMENT OF COGNITIVE AND NEURAL SYSTEMS
GRADUATE TRAINING ANNOUNCEMENT

Boston University
677 Beacon Street
Boston, MA 02215

Phone: 617/353-9481
Fax:   617/353-7755
Email: [EMAIL PROTECTED]
Web: http://www.cns.bu.edu/

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