CNS Department cns at cns.bu.edu
Mon Sep 25 14:04:49 EST 2006


The Boston University Department of Cognitive and Neural Systems  
(CNS) 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.

Applications for Fall 2007 admission and financial aid are now being  
accepted for PhD, MA, and BA/MA degree programs.

For program details, please see the CNS Brochure at:

Paper applications may be downloaded from:

Online applications may be submitted via:

Alternatively, you may request materials via email by sending your  
full name and mailing address to amos at cns.bu.edu;

or write, telephone, or fax:

Mr. Robin Amos
Department of Cognitive and Neural Systems
Boston University
677 Beacon Street
Boston, MA 02215
617/353-9481 (phone)
617/353-7755 (fax)

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, a personal  
statement, and Graduate Record Examination (GRE) general test scores.

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



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.  
Also 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. 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.


Jelle Atema
Professor of Biology
Director, Boston University Marine Program (BUMP)
PhD, University of Michigan
Sensory biology, chemical signals, animal behavior, receptor  
physiology, behavioral ecology, chemical ecology, computational  
models, robotics

Helen Barbas
Professor, Department of Health Sciences, Sargent College
PhD, Physiology/Neurophysiology, McGill University, Canada
Organization of the prefrontal cortex, investigation of pathways that  
transmit signals to prefrontal cortices from structures associated  
with sensory, cognitive, mnemonic and emotional processes

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

Yongqiang Cao
Senior Research Associate, Department of Cognitive and Neural Systems
Ph.D., Applied Mathematics, York University, United Kingdom
Brain modeling and biologically inspired computing; 3D vision,  
pattern recognition and large scale data mining

Gail A. Carpenter
Professor of Cognitive and Neural Systems and Mathematics
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  

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
Chairman, Department of Psychology
Director, Center for Memory and Brain
Director, Cognitive Neurobiology Laboratory
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 neurobiology and neurochemical signal transduction in the retina

Daniel Franklin
CELEST Director of Curriculum Development, Cognitive and Neural Systems
PhD, Cognitive and Neural Systems, Boston University (pending)
MBA, Statistics and Organizational Design, Boston University
Learning and memory, development, education; deliver new and enhanced  
curriculum modules for use by teachers with students of all ages

Jean Berko Gleason
Professor Emereitus of Psychology
PhD, Harvard University

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

Anatoli Gorchetchnikov
Research Associate, Department of Cognitive and Neural Systems
PhD, Cognitive and Neural Systems, Boston University
Theoretical modeling of spatial navigation in humans and animals with  
the emphasis on the hippocampal function, create printed educational  
materials on natural and artificial learning mechanisms

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
Director, Center of Excellence for Learning in Education, Science,  
and Technology
Director, Center for Intelligent Biomimetic Image Processing and  
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, Graduate Studies, Department of Psychology
Director, Computational Neurophysiology Laboratory
PhD, Experimental Psychology, Oxford University, United Kingdom
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

Dae-Shik Kim
Associate Professor of Anatomy and Neurobiology
Director, Center for Biomedical Imaging (CBI)
PhD, Neurophysiology, Max-Planck Institute for Brain Research
Functional and connectivity mapping of the human visual cortex

Thomas G. Kincaid
Professor of Electrical, Computer and Systems Engineering, College of  
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, functional analysis, mathematical physics,  
partial differential equations

Norbert Kopco
Research Associate, Department of Cognitive and Neural Systems
PhD, Cognitive and Neural Systems, Boston University
Lecturer, Department of Cybernetics and AI, Technical, University of  
Kosice, Slovakia
Spatial auditory perception; behavioral studies and modeling of  
speech and non-speech perception in complex environments, auditory  
localization, plasticity, attention, and crossmodal factors in  
spatial hearing

Nancy Kopell
Professor of Mathematics
PhD, Mathematics, University of California at Berkeley
Dynamics of networks of neurons, applied mathematics and dynamical  

Jacqueline A. Liederman
Professor of Psychology
Director, Brain, Behavior and Cognition Program
PhD, Psychology, University of Rochester
Developmental neuropsychology, neuropsychology, physiological  
psychology, 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

Geoffrey Stuart Morrison
Research Fellow, Department of Cognitive and Neural Systems
PhD, Linguistics, University of Alberta, Canada
Modeling of first and second language speech perception learning

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, MIT Research Lab of Electronics, Speech  
Communication Group
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,  
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  

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

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;  
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; & Anatomy and Neurobiology
PhD, High Energy Physics, Columbia University
Computational neuroscience, machine vision, neuroanatomy, neural  

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  
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  
Director of Graduate Studies, Department of Cognitive and Neural Systems
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
Associate 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  
Associate Professor of Radiology, Harvard Medical School
Director, Cognitive Neuroimaging Laboratory
PhD, Experimental Psychology, Oxford University, United Kingdom
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  

Joseph Z. Tsien
Professor of Pharmacology and Biomedical Engineering
Director, Center for Systems Neurobiology
PhD, Molecular Biology, University of Minnesota
Neural mechanisms of learning, memory and concepts; neural codes and  

Lucia Vaina
Professor of Biomedical Engineering
Research Professor of Neurology, School of Medicine
PhD, Sorbonne Dres Science, National Politechnique Institute,  
Toulouse, France
Computational visual neuroscience; theoretical engineering and  

Takeo Watanabe
Associate Professor of Psychology
Director, Vision Sciences Laboratory
PhD, Behavioral Sciences, University of Tokyo, Japan
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
Professor of Ophthalmology, Harvard Medical School
Psychophysicist, Brigham & Women’s Hospital, Surgery Department
Director of Psychophysical Studies, Center for Clinical Cataract  
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


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  
CAS CN560 Neural and Computational Models of Speech Perception and  
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 CN710 Advanced Topics in Neural Modeling: Comparative Analysis of  
Learning Systems
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  
GRS CN811 Topics in Cognitive and Neural Systems: Visual Perception

GRS CN911, 912 Research in Neural Networks for Adaptive Pattern  
GRS CN915, 916 Research in Neural Networks for Vision and Image  
GRS CN921, 922 Research in Neural Networks for Speech and Language  
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  
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.


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 network comprised of Sun  
workstations, Macintoshes, and both 32-bit and 64-bit PCs. A PC farm  
running BU’s own version of Linux (BU Linux v4.6 based on Fedora Core  
3) is available as a distributed computational environment. All  
students have department supplied PCs on their desktops (running  
either Microsoft Windows XP Pro or BU Linux) allowing them to run  
their simulations either locally or remotely on one of the  
department’s workstations. Mathematical simulation and modeling are  
carried out using standard software packages such as Mathematica or  
Matlab, as well as SPlus and VisSim. The department also 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:

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

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

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

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

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.

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

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

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.

Department of Cognitive and Neural Systems
Boston University
677 Beacon Street
Boston, MA 02215
Phone: 617/353-9481
Fax:     617/353-7755
Email: amos at cns.bu.edu
Web:   http://cns.bu.edu/


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