Caltech's CNS Program

[Christof Koch]

This is a short description of our CNS program. Deadline for application
is end of January.

Christof

*******************************************************
                      CALIFORNIA INSTITUTE OF TECHNOLOGY
  *******************************************************

  Computation and Neural Systems Program

        This interdepartmental program awards a Ph.D. in Computation
        and Neural Systems. No Master is awarded.
        Current enrollment:  28 doctoral, 18 postdoctoral

  Financial support:
        Complete support for tuition and stipend from graduate
        research assistantships, graduate teaching assistantships,
        NIH training grant, and private sources.

  Contact:

        J. Hopfield, Ph.D., Program Head, 160-30
                (818) 356-2808

        J. Bower, Ph.D., Chairman of Admissions, Biology Div.,
                216-76, (818) 356-6817
                jbower at smaug.cns.caltech.edu

        All at California Institute of Technology, Pasadena, CA 91125

        Caltech's graduate program in Computation and Neural Systems
 presently involves 16 faculty in the Division of Biology, Engineering
 and Applied Science, and Physics.  This interdisciplinary program
 is centered on computation approaches to the study of biological and
 artificial information processing systems.  A multidisciplinary
 curriculum offers training in four general areas:  neurobiology;
 computer science and collective computation; physical computational
 devices; and mathematics and modeling.  Students need to take courses
 in each of these areas in addition to an experimental laboratory course in
 neurobiology. The breadth of training is enhanced by close interactions
 among students and faculty from all  parts of the program.  A central
 focus is provided by weekly seminars, informal lunch talks, and a
 computer simulation laboratory open to  students. Students are assigned
 to a research laboratory upon arrival, but have the option of rotating
 through several laboratories before  choosing a thesis advisor.

        Research interests of the faculty include the collective properties
 and computational capacities of complex artificial and biological
 networks, analog VLSI devices, optical devices, and highly parallel
 digital computers.  Neurobiological simulation approaches include
 modeling at the systems level (e.g., olfactory cortex, cerebellar cortex,
 and visual and auditory cortices) and at the cellular level (e.g.,  biophysical

and developmental mechanisms).  Computational approaches to artificial
systems span a wide range, from studies of associative memory and
 analog networks for sensory processing to graphical image representation
 and the theory of computation.  Interested students are  encouraged to
 combine theoretical or modeling approaches with physiological or
 anatomical research on biological systems.


        Core faculty:

        Yaser Abu-Mostafa, John Allman, Alan Barr, James Bower, Rodney
        Goodman, John Hopfield, Bela Julesz, Christof Koch, Masakazu
        Konishi, Gilles Laurent, Henry Lester, Carver Mead, Jerome Pine,
        Edward Posner, Demitri Psaltis, David van Essen.


        Selection of ourses:


    CNS 124 : Pattern Recognition (two quarters)

       Covers classic results from pattern recognition and discusses in this
       context associative memories and related neural network models of
       computation.

       Given by D. Psaltis.


    CNS 174 : Computer Graphics Laboratory (three quarters)

       The art of making pictures by computer.

       Given by A. H. Barr.


    CNS 182 : Analog Integrated Circuit Design (three quarters)

       Device, circuit, and system techniques for designing large-scale
       CMOS analog systems.

       Given by C. A. Mead.


    CNS 184 : Analog Integrated Circuit Projects Laboratory (three quarters)

       Design projects in large-scale analog integrated systems.

       Given by C. A. Mead.


    CNS 185 : Collective Computation (one quarter)

       Neural network theory and applications.

       Given by J. J. Hopfield.


    CNS 186 : Vision: From Computational Theory to Neuronal Mechanisms
       (one quarter)

       Lecture and discussion course aimed at understanding visual
       information processing in both biological and artificial systems.

       Given by C. Koch and D. C. Van Essen.


    CNS 221 : Computational Neurobiology (one quarter)

       Lecture, discussion and laboratory aimed at understanding
       computational aspects of information processing within the nervous
       system.

       Given by J. Bower and C. Koch.


    CNS 256 : Methods of Multineural Recording (one quarter)

       Reading and discussion course. Topics included span a range of
       multineural recording techniques from multielectrode recording
       to positron emission tomography.

       Given by J. Pine.




        Student personal description ( H. H. Suarez, fourth year graduate
        student;  hhs at aurel.caltech.edu):

       According to my experience, this program's emphasis really spans
       a wide range, but two areas stand out especially for me: modelling
       biological systems in a very detailed fashion and building artificial
       sensory-motor systems (analog VLSI - based systems) whose design is
       strongly influenced by knowledge of the corresponding biological
       system. The overall ambiance from a student's point of view is
       very good, due to the personal qualities of the faculty and the
       students. There is a fair amount of interaction among the researchers
       in the program, and on the average two or three talks a week
       on CNS-related topics, often from researchers outside Caltech.
       Thus there is little chance of getting bored ...