CNS Graduate Programs Announcement

[Carol Jefferson]

PLEASE POST

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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 2005 admission and financial aid are now being
accepted for PhD, MA, and BA/MA degree programs.

To obtain a brochure describing CNS programs 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) general test scores. 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. 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 producing 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
<http://www.cns.bu.edu/CELEST>http://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, computational neuroscience, visual
psychophysics, speech and language, sensory-motor control, neurobotics,
computer vision, and technology), 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.

FACULTY AND RESEARCH 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

Virginia Best
Research Associate, Department of Cognitive and Neural Systems
PhD, Physiology, University of Sydney, Australia
Auditory processing in humans, with a focus on spatial hearing, spatial
attention and speech perception

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
PhD, Mathematics, University of Wisconsin, Madison
Learning and memory, vision, synaptic processes, pattern recognition,
remote sensing, medical database analysis, machine learning, differential
equations, neural network technology transfer

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

Allyn Hubbard
Professor of Electrical and Computer Engineering
PhD, Electrical Engineering, University of Wisconsin
VLSI circuit design: digital, analog, subthreshold analog, biCMOS, CMOS;
information processing in neurons, neural net chips, synthetic aperture
radar (SAR) processing chips, sonar processing chips; auditory models and
experiments

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

Siegfried Martens
Research Associate, Department of Cognitive and Neural Systems
PhD, Cognitive and Neural Systems, Boston University
Learning models, pattern recognition, visualization, remote sensing, sensor
fusion

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

Alfonso Nieto Castanon
Research Associate, Department of Cognitive and Neural Systems
PhD, Cognitive and Neural Systems, Boston University
Speech, statistics, signal processing, computational neuroscience

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

Marc Pomplun
Adjunct Assistant Professor of Cognitive and Neural Systems
Assistant Professor of Computer Science, University of Massachusetts, Boston
PhD, Computer Science, University of Bielefeld, Germany
Eye movements, visual attention, modeling of cognitive processes,
human-computer interaction

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

Kevin Reilly
Research Associate, Department of Cognitive and Neural Systems
PhD, Speech and Hearing Science, University of Washington, Seattle
Speech production, sensory-motor control and learning, computational
neuroscience

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
Senior Scientist, Haskins Laboratories, New Haven, 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

Fabrizio Santini
Research Associate, Department of Cognitive and Neural Systems
PhD, Computer Science, University of Florence, Italy
Neuromorphic robotics, vision, neuroprocessors and large neural system
simulations

Robert Savoy
Adjunct Associate Professor of Cognitive and Neural Systems
Assistant in Experimental Psychology; Director, fMRI Education; Instructor
Department of Radiology, Massachusetts General Hospital
President, HyperVision Incorporated, Lexington, MA
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
Associate 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
Associate Professor of Psychology and Program in Neuroscience, Boston
University
Associate Professor of Radiology, Harvard Medical School
Assistant in Neuroscience, MGH-Martinos Center, Massachusetts General Hospital
PhD, Experimental Psychology, Oxford University
Functional neuroimaging studies (fMRI and MEG) of learning and memory

Timothy Streeter
Research Associate, Department of Cognitive and Neural Systems
MS, Physics, University of New Hampshire
MA, Cognitive and Neural Systems, Boston University
Spatial auditory perception, perceptual adaptation

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 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
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 CN750  Comparative Analysis of Learning Systems (new course)
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; 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, 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, 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.

Auditory Neuroscience Laboratory
The Auditory Neuroscience 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 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. 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.

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 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.

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://cns.bu.edu/
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