AISB convention 2017

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Harold Cohen

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Computerised Minds. ...

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Connection Science

All individual members of The Society for the Study of Artificial Intelligence and Simulation of Behaviour have a personal subscription to the Taylor Francis journal Connection Science as part of their membership. How to Acce...



AISB opportunities Bulletin Item



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. CNS is a world leader in computational neuroscience, connectionist cognitive science, and biologically-inspired technology. It has developed a unique interdisciplinary curriculum of seventeen graduate courses with which to train its graduate students. CNS research activities include the major new NSF Center of Excellence for Learning in Education, Science, and Technology (CELEST;

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;

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

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

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


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 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
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 Classification
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 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, 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 systems

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, 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; & 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
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 University
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 transmission

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 brain-machine-interface

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 neuroinformatics

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 & Womens 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


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 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 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.


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 BUs 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 departments 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 latters 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 Departments and Universitys 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 (, a growing resource for the NSF Center for Excellence for Learning in Education, Science, and Technology (

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:  The laboratory occupies an 800-square-foot suite, including three dedicated rooms for data collection, and houses a variety of computer-controlled display platforms, including Macintosh, Windows and Linux workstations. Ancillary resources for visual psychophysics include a computer-controlled video camera, stereo viewing devices, a photometer, and a variety of display-generation, data-collection, and data-analysis software.

Affiliated 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.