Graduate Program in the Department of Cognitive and Neural Systems (CNS) at Boston University

[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 2003 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:


amos at cns.bu.edu


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 advisor 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

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

Gail A. Carpenter
Professor of Cognitive and Neural Systems and Mathematics
Director of Graduate Studies, Department of Cognitive and Neural Systems
Director, CNS Technology Laboratory
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

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

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
Acting Chairman 2002-2003, Department of Cognitive and Neural Systems
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

Bradley Rhodes
Research Associate, Technology Lab, Department of Cognitive and Neural 
Systems
PhD, Cognitive and Neural Systems, Boston University
Motor control, learning, and adaptation, serial order behavior (timing 
in particular), attention and memory

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
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)

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. x 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 Lab was established in July 2001, with a grant from the Air Force 
Office of Scientific Research:  "Information Fusion for Image Analysis: 
  Neural Models and Technology Development." Initial projects have 
focused on multi-level fusion and data mining in a geospatial context, 
in collaboration with the Boston University Center for Remote Sensing. 
This research and development has built on models of opponent-color 
visual processing, boundary contour system (BCS) and texture processing, 
and Adaptive Resonance Theory (ART) pattern learning and recognition, as 
well as other models of associative learning and prediction. Other 
projects include collaborations with the New England Medical Center and 
Boston Medical Center, to develop methods for analysis of large-scale 
medical databases, currently to predict HIV resistance to antiretroviral 
therapy. Associated basic research projects are conducted within the 
joint context of scientific data and technological constraints.

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: inquiries at cns.bu.edu
Web: http://www.cns.bu.edu/
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