neuron-request@HPLMS2.HPL.HP.COM ("Neuron-Digest Moderator Peter Marvit") (10/26/90)
Neuron Digest Thursday, 25 Oct 1990 Volume 6 : Issue 62 Today's Topics: Re: REFERENCES NEEDED graduate fellowships in cognitive science Control of locomotion REFERENCES ABOUT MODIFICATION OF NN STRUCTURE Hard copies of paper on conjugate gradient backpropagation Bay area AI Forum WORKSHOP ON THEORETICAL ISSUES IN NEURAL NETS, May 20-23, 1991 Two Preprints: Generalization & Representation, Sensorimotor Learning HICSS NN (Part 1) HICSS NN (part 2) Connectionist Faculty Position at Boulder Cognitive Science COnference CNS RFPs Send submissions, questions, address maintenance and requests for old issues to "neuron-request@hplabs.hp.com" or "{any backbone,uunet}!hplabs!neuron-request" Use "ftp" to get old issues from hplpm.hpl.hp.com (15.255.176.205). ------------------------------------------------------------ Subject: Re: REFERENCES NEEDED From: william stevenson <wstevens@uceng.UC.EDU> Date: Sat, 20 Oct 90 13:00:19 -0400 In comp.ai.neural-nets you write: >I am looking for references on automatic modifcation of structure of a >neural network by learning algorithms(i.e. automatically add some links >and nodes to a neural network or remove them from the neural network. >Any information are welcomed. >Thanks in advance. Try Scott Fahlman's Cascade Correlation: adds nodes as needed. Contact him at fahlman@cs.cmu.edu; software (both cascade and quickprop) available by ftp at pt.cs.cmu.edu, in directory /afs/cs/project/connect/code (you must go to this directory directly) I got his reports too, I'm not sure if they're in the same directory. William ------------------------------ Subject: graduate fellowships in cognitive science From: "KRUSCHKE,JOHN,PSY" <kruschke@ucs.indiana.edu> Date: 23 Oct 90 15:47:00 -0500 GRADUATE FELLOWSHIPS AND ASSISTANTSHIPS ARE AVAILABLE FROM THE INDIANA UNIVERSITY COGNITIVE SCIENCE PROGRAM This program offers joint PhDs (and minors associated with PhDs) in combination with a PhD from a home department (such as psychology, computer science, philosophy, linguistics, or any other PhD granting unit). Students must be admitted to, and be members of, some home department. The Cognitive Science Program at Indiana University has a core faculty of 45 professors, supports research activities in numerous areas, publishes a research report series, sponsors a colloquium series, and offers fellowships and assistantships to qualified applicants. A brochure describing the program and admission procedures is available from, and inquiries and requests for information may be directed to, Richard M. Shiffrin, Director Cognitive Science Program Psychology Department Indiana University Bloomington, IN 47405 E-mail: IUCOGSCI@UCS.INDIANA.EDU (Please don't use your e-mail "reply" command, but instead direct inquiries directly to the addresses above.) ------------------------------ Subject: Control of locomotion From: cmah@cns.ucalgary.ca (Chris Mah) Date: Wed, 24 Oct 90 10:27:53 -0600 I'm interested in any references dealing with the use of neural nets for the real time control or simulation of movement, especially locomotion. Ultimately, the group I'm working with wants to understand gait (locomotion ) disorders in humans - to me this means simulation. Can anyone help me with this? Christopher D. Mah Dept. of Clinical Neurosciences University of Calgary ------------------------------ Subject: REFERENCES ABOUT MODIFICATION OF NN STRUCTURE From: qian@icopen.ICO.OLIVETTI.COM (DA QUN QIAN) Date: Thu, 25 Oct 90 10:45:06 +0100 I sent an email to NN Digest for the references, and collected some replys and some emails to ask for the replys. I am now sending the replys to NN Disgest for netters. ===================== Subject: self organization of topologies Date: Sat, 20 Oct 90 13:42:52 EST From: Manoel Fernando Tenorio <tenorio@ecn.purdue.edu> IEEE trans in NN vol. 1 no. 1 1990. Self Organizing Network for System Identification. --ft. ===================== Date: Tue, 23 Oct 90 16:48:55 -0100 From: Joachim Diederich <gmdzi!joachim@relay.EU.net> Subject: Recruitment Learning There are a number of structure-changing learning techniques, for instance: Diederich, J. Steps toward knowledge-intensive connectionist learning. In: J. Barnden & J. Pollack (Eds.): Advances in Connectionist and Neural Computation. Ablex. Publ. 1989 Diederich, J. Instruction and High-Level Learning in Connectionist Networks. Connection Science, Vol.1, No.2, 161-180, 1989 Fanty, M. Learning in Structured Connectionist Networks. Ph.D Thesis, CS Department, University of Rochester, 1988 Feldman, J.A. Dynamic Connections in Neural Networks. Biol. Cybernetics, 46, 27-39, 1982 Frean, M. The Upstart Algorithm: A Method for Constructing and Training Feedforward Neural Networks. Neural Computation, 2, 198-209, 1990 Honavar, V. & Uhr, L. A network of neuron-like units that learn to perceive by generation as well as reweighting of its links. In: Touretzky, D., Hinton, G., Sejnowski, T. (Eds.): Proc. of the Connectionist Models Summer School 1988, Morgan Kaufman Publ., 472-484, San Mateo 1988 With best regards, Joachim Diederich ------------------------------ Subject: Hard copies of paper on conjugate gradient backpropagation From: erik@adams.llnl.gov (ERIK JOHANSSON) Date: Tue, 23 Oct 90 14:46:26 -0700 The response to the posting about my paper on conjugate gradient backpropagation has been overwhelming. I have been inundated with requests for hard copies of the paper; more than I can handle with a Xerox machine. Consequently, I am having copies printed. I will mail them out as soon as I receive them (hopefully in a week or so); please be patient. Thanks, Erik Johansson Lawrence Livermore National Laboratory PO Box 808, L-496 Livermore, CA 94550 (415) 423-9255 email: erik@adams.llnl.gov erik@batman.llnl.gov johansson@icdc.llnl.gov ------------------------------ Subject: Bay area AI Forum From: Kingsley Morse <kingsley@hpwrce.hp.com> Date: Sun, 21 Oct 90 17:27:16 -0700 ************************************************************** * * * A I F O R U M M E E T I N G * * * * * * SPEAKER: Doug Danforth * * TOPIC: Sparse Distributed Memories and * * Neural Networks * * WHEN: 7PM Tuesday 10/23/90 * * WHERE: Lockheed building 202, auditorium * * 3251 Hanover Street * * Palo Alto, CA * * * * AI Forum meetings are free, open and monthly! * * Call (415) 594-1685 for more info * ************************************************************** ------------------------------ Subject: WORKSHOP ON THEORETICAL ISSUES IN NEURAL NETS, May 20-23, 1991 From: Eduardo Sontag <sontag@hilbert.RUTGERS.EDU> Date: Thu, 18 Oct 90 15:43:19 -0400 WORKSHOP ON THEORETICAL ISSUES IN NEURAL NETS Announcement and Call for Contributions The Center for Discrete Mathematics and Theoretical Computer Science (DIMACS) will host a workshop on "Theoretical Issues in Neural Nets" at Rutgers University, for four days, May 20-23, 1991. This will be a mathematically oriented meeting, where technical issues can be discussed in depth. The objective is to have a Workshop that brings together people interested in a serious study of foundations -- plus a few people who will give expository lectures on applied problems and biological nets. The area is of course very diverse, and precisely because of this it might be worth trying to search for conceptual unity in the context of the Workshop. A preliminary list of main speakers is as follows (with tentative topics listed, when available): Dave Ackley, Bellcore (Genetic algorithms: Evolution and learning) Andrew Barron, U. Illinois (Statistical selection of neural net architectures) Andy Barto, U. Mass. (Expository talk: Learning & incrmntl dynamic programming) Eric Baum, NEC Institute (Expository talk: Sample complexity) Ed Blum, USC (Feed-forward networks and approximation in various norms) Roger Brockett, Harvard (Combinatorial optimization via steepest descent) George Cybenko, U. Illinois Merrick Furst, CMU (Circuit complexity & harmonic analysis of Boolean functs) Herbert Gish, BBN (Maximum likelihood training of neural networks) Stephen Grossberg, Boston U. (Expository talk) Steve Hanson, Siemens (Expository talk: Human learning and categorization) Moe Hirsch, Berkeley (Expository talk: Network dynamics) Wolfgang Maass, U. Ill./Chicago (Boltzmann machines for classification) John Moody, Yale Sara Solla, Bell Labs (Supervised learning and statistical physics) Santosh S. Venkatesh, Penn Hal White, UCSD The organizing committee consists of Bradley W. Dickinson (Princeton), Gary M. Kuhn (Institute for Defense Analyses), and Eduardo D. Sontag and Hector J. Sussmann (Rutgers). DIMACS is a National Science Foundation Science and Technology Center, established as a cooperative project between Rutgers University, Princeton University, AT&T Bell Laboratories, and Bellcore. Its objectives are to carry out basic and applied research in discrete mathematics and theoretical computer science. The center provides excellent facilities for workshop participants, including offices and computer support. If you are interested in participating in this workshop, please send a message to Eduardo at sontag@hilbert.rutgers.edu. If you would like to give a talk, please e-mail a title and abstract to the above address by January 15th, 1991. Please keep the abstract short, but give references to published work if appropriate. (Use plain TeX, LaTeX, or a text file; please do not use snailmail.) There is a possibility of proceedings being published, but nothing has been decided in that regard. If you are interested in attending but not talking, send a note explaining your interest in the area. The committee will try to accommodate as many participants and as many talks as possible, but the numbers may have to be limited in order to achieve a relaxed workshop atmosphere conducive to interactions among participants. Notification of people concerning attendance is expected about the middle of February. ------------------------------ Subject: Two Preprints: Generalization & Representation, Sensorimotor Learning From: gluck%psych@Forsythe.Stanford.EDU (Mark Gluck) Date: Sat, 20 Oct 90 11:27:59 -0700 TWO PRE-PRINTS AVAILABLE: 1) Stimulus Generalization and Representation in Adaptive Network Models of Category Learning 2) Sensorimotor Learning and the Cerebellum. _________________________________________________________________ Gluck, M. A. (1991, in press). Stimulus generalization and representation in adaptive network models of category learning To appear in : Psychological Science. Abstract An exponential-decay relationship relationship between the proba- bility of generalization and psychological distance has received considerable support from studies of stimulus generalization (Shepard, 1958) and categorization (Nosofsky, 1984). It is shown here how an approximate exponential generalization gradient em- erges in a "configural-cue" network model of human learning that represents stimulus patterns in terms of elementary features and pair-wise conjunctions of features (Gluck & Bower, 1988b; Gluck, Bower, & Hee, 1989) from stimulus representation assumptions iso- morphic to a special case of Shepard's (1987) theory of stimulus generalization. The network model can be viewed as a combination of Shepard's theory and an associative learning rule derived from Rescorla and Wagner's (1972) theory of classical conditioning. _________________________________________________________________ Bartha, G. T., Thompson, R. F., & Gluck, M. A. (1991, in press) Sensorimotor learning and the cerebellum. In M. A. Arbib and J.-P. Ewert (Eds.), Visual Structures and Integrated Functions, Springer Research Notes in Neural Computing, Berlin: Springer-Verlag. Abstract This paper describes our current work on integrating experimental and theoretical studies of a simple form of sensorimotor learn- ing: the classically conditioned rabbit eyelid closure response. We first review experimental efforts to determine the neural basis of the conditioned eyelid closure response and these sup- port the role of the cerebellum as the site of the memory trace. Then our current work to bring the modeling in closer contact with the biology is described. In particular, we extend our ear- lier model of response topography to be more physiological in the circuit connectivity, the learning algorithm, and the conditioned stimulus representation. The results of these extensions include a more realistic conditioned response topography and reinforce- ment learning which accounts for an experimentally established negative feedback loop. _________________________________________________________________ To request copies, send email to: gluck@psych.stanford.edu with your hard-copy mailing address. Or mail to: Mark A. Gluck, Department of Psychology, Jordan Hall, Bldg. 420, Stanford Univ., Stanford, CA 94305-2130 ------------------------------ Subject: HICSS NN (Part 1) From: "William Remus" <T034360%UHCCMVS.BITNET@CORNELLC.cit.cornell.edu> Date: Sun, 21 Oct 90 14:38:00 -1000 Could you once again publicize our special track in neural network? CALL FOR PAPERS 25th ANNUAL HAWAII INTERNATIONAL CONFERENCE ON SYSTEM SCIENCES (HICSS-25) KAUAI, HAWAII - JANUARY 7-10, 1992 NEURAL NET APPLICATIONS IN BUSINESS III The Emerging Technologies and Applications Track of HICSS-25 will contain a special set of sessions focusing on a broad selection of topics in the area of Neural Net Applications in Business. The presentations will provide a forum to discuss new advances in these applications. Papers are invited that may be theoretical, conceptual, tutorial, or descriptive in nature. Of special interest, however, are papers detailing solutions to practical problems. Those papers selected for presentation will appear in the Conference Proceedings, which are published by the Computer Society of the IEEE. HICSS-25 is sponsored by the University of Hawaii in cooperation with the ACM, the IEEE Computer Society, and the Pacific Research Institute for Information Systems and Management (PRIISM). Submissions are solicited in the areas: (1) The application of neural nets to model business tasks performed by people (e.g. Dutta and Shekhar paper on Applying Neural Nets to Rating Bonds, ICNN, 1988, Vol. II, pp. 443-450). (2) The development of neural nets to model human decision tasks (e.g. Gluck and Bower, Journal of Experimental Psychology: General, 117(3), 227-247). (3) The application of neural nets to improving modeling tools commonly used in business (e.g. neural networks to perform regression-like modeling). (4) The embedding of neural nets in commercial products (e.g. OCR scanners). Our order of preference is from (1) to (4) above. Papers which detail actual usage of neural networks are preferred to those which only propose uses. INSTRUCTIONS FOR SUBMITTING PAPERS: Manuscripts should be 12-26 typewritten, double-spaced pages in length. Do not send submissions that are significantly shorter or longer than this. Each manuscript will be subjected to refereeing. Manuscript papers should have a title page that includes the title of the paper, full name(s) of its author(s), affiliation(s), complete mailing and electronic address(es), telephone number(s), and a 300- word abstract of the paper. DEADLINES A 300-word optional abstract may be submitted by March 1, 1991 by E-mail or mail. (If no reply to E-mail in 7 days, send by U.S. mail also.) Feedback to author concerning abstract by April 1, 1991. Six paper copies of the manuscript are due by June 5, 1991. Notification of accepted papers by September 1, 1991. Accepted manuscripts, camera-ready, are due by October 1, 1991. SEND SUBMISSIONS AND QUESTIONS TO: Prof. William Remus College of Business University of Hawaii 2404 Maile Way Honolulu, HI 96822 USA Tel.: (808) 956-7608 EMAIL: CBADWRE@UHCCVM.BITNET FAX: (808) 956-3261 OR Prof. Tim Hill College of Business University of Hawaii 2404 Maile Way Honolulu, HI 96822 USA Tel.: (808) 956-6657 EMAIL: CBADTHI@UHCCVM.BITNET FAX: (808) 956-3261 ------------------------------ Subject: HICSS NN (part 2) From: "William Remus" <T034360%UHCCMVS.BITNET@CORNELLC.cit.cornell.edu> Date: Sun, 21 Oct 90 14:48:00 -1000 Could you please publicize our current papers? Perhaps attach to the earlier message since these are examples of the kind of papers we would like. Thanks very much. ******************************************************************** Following are the papers and authors in the Neural Network Applications in Business Mini-Track at Hawaii International Conference on Systems Sciences, January 9-11, 1991. There are several hundred other papers to be presented at the conference including others on neural network theory. The papers are available in the proceedings (published by ------- IEEE Press) or directly from the authors. ORGANIZATIONAL SYSTEMS AND TECHNOLOGY TRACK, HICSS-24 NEURAL NETWORKS IN BUSINESS MINITRACK, WILLIAM REMUS, COORDINATOR SESSION 1 1. An Integrated Neural Network Approach for Business Forecasting Francis Wong Research Division Institute of Systems Science National University of Singapore Kent Ridge Republic of Singapore 0511 Tel: 7756666 Telex: ISSNUS RS 39988 Fax: 7782571 2. Estimation of Simultaneous Econometric Equations Using Neural Networks L. Ramkumar Information Systems Department College of Business and Management University of Maryland College Park, MD 20742 (301) 454-8713 kumar@umd5umd.edu 3. A Simulation Study of Neural Networks Leorey Marquez University of Hawaii Department of Decision Sciences Honolulu, HI 96826 CBADLMA@UHCCVM Neural Networks in Business HICSS-24 SESSION 2 1. The Application of Neural Network Based Methods to the Extraction of Knowledge From Accounting Reports Duarte Trigueiros University of East Anglia School of Information Systems Norwich NR4 7TJ United Kingdom (603) 56161 FAX (603) 58556 Telex: 975197 E-mail: A033@UK.AC.UEA.CPC865 co-Author: Robert Berry 2. A Neural Network Application for Bankruptcy Prediction co-authored with Lawrence Schkade and S. Bapiraju Wullianallur Raghupathi University of Texas at Arlington Department of Information Systems and Management Sciences UTA Box 19437 Arlington, Texas 76019 (817) 273-3502 3. Predicting Stock Price Performance: A Neural Network Approach co-authored by George Swales (Department of Finance and General Business) Youngohc Yoon Department of Computer Information Systems College of Business Administration Southwest Missouri State University Springfield, Missouri 65804-0095 yoy971f@smsvma.bitnet fax: (417) 836-6337 4. Contrasting Neural Nets with Regression in Predicting the Performance of Transportation Firms Katherine Duliba Stern School of Business 90 Trinity Place 7th Floor New York, NY 10006 e-mail: kduliba@nybvx1 ------------------------------ Subject: Connectionist Faculty Position at Boulder From: Paul Smolensky <paul@axon.Colorado.EDU> Date: Tue, 23 Oct 90 10:04:58 -0600 The Institute for Cognitive Science at the University of Colorado, Boulder has an opening for which connectionists are invited to apply. As you can see from the official ad below, applications in another field are also being invited. However, should this year's position go to a non-connectionist, we expect another position next year and a search will be held specifically for a connectionist. We would be more than happy to answer any questions you may have... Paul Smolensky & Mike Mozer ------------------------------------- Faculty Position in Cognitive Science The Institute of Cognitive Science at the University of Colorado at Boulder invites applications for a tenured/tenure-track position, either in the area of connectionism or in the area of knowledge-based systems or cooperative problem solving. The position is open as to rank. An important selection criterion will be the candidate's potential to contribute to the Institute's interdisciplinary missions in research, teaching, and service. Candidates in the connectionist area should have demonstrated ability to contribute to connectionist theory as well as connectionist approaches to cognitive science. Candidates in the knowledge based systems or cooperative problem solving area should have an interest in large scale system building efforts and software technologies and tools. The position will be housed in an appropriate academic department associated with the Institute of Cognitive Science (e.g., Computer Science, Linguistics, Philosophy, or Psychology). A resume and three letters of reference should be sent to: Dr. Martha Polson, Assistant Director, Institute of Cognitive Science, University of Colorado, Boulder, Colorado, 80309-0345 by January 18, 1990. The University of Colorado at Boulder has a strong commitment to the principle of diversity in all areas. In that spirit, we are particularly interested in receiving applications from a broad spectrum of people, including women, members of ethnic minorities and disabled individuals. ------------------------------ Subject: Cognitive Science COnference From: leyton@cogsci-1.rutgers.edu (Michael Leyton) Date: Tue, 23 Oct 90 14:40:27 -0400 ---------------------------------------------------- Reminder: COLUMBIA/PRINCETON/RUTGERS Cognitive Science Third One-Day Conference Nov 9th, 11am-6pm Columbia, Schermerhorn, 614 ---------------------------------------------------- Speakers Lynn Cooper, Zenon Pylyshyn, Robert Remez, Georges Rey ----------------------------------------------------- Inquiries: Michael Leyton leyton@cogsci-1.rutgers.edu ------------------------------ Subject: CNS RFPs From: Steve Hanson <jose@learning.siemens.com> Date: Thu, 25 Oct 90 08:38:10 -0400 McDonnell-Pew Program in Cognitive Neuroscience October 1990 Individual Grants-in-Aid for Research and Training Supported jointly by the James S. McDonnell Foundation and The Pew Charitable Trusts INTRODUCTION The McDonnell-Pew Program in Cognitive Neuroscience has been created jointly by the James S. McDonnell Foundation and The Pew Charitable Trusts to promote the development of cognitive neuroscience. The foundations have allocated $12 million over an initial three-year period for this program. Cognitive neuroscience attempts to understand human mental events by specifying how neural tissue carries out computations. Work in cognitive neuroscience is interdisciplinary in character, drawing on developments in clinical and basic neuroscience, computer science, psychology, linguistics, and philosophy. Cognitive neuroscience excludes descriptions of psychological function that do not address the underlying brain mechanisms and neuroscientific descriptions that do not speak to psychological function. The program has three components. (1) Institutional grants have been awarded for the purpose of creating centers where cognitive scientists and neuroscientists can work together. (2) To encourage Ph.D. and M.D. investigators in cognitive neuroscience, small grants-in-aid will be awarded for individual research projects. (3) To encourage Ph.D. and M.D. investigators to acquire skills for interdisciplinary research, small training grants will be awarded. During the program's initial three-year period, approximately $4 million will be available for the latter two components -- individual grants-in-aid for research and training -- which this brochure describes. RESEARCH GRANTS The McDonnell-Pew Program in Cognitive Neuroscience will issue a limited number of awards to support collaborative work by cognitive neuroscientists. Applications are sought for projects of exceptional merit that are not currently fundable through other channels and from investigators who are not at institutions already funded by an institutional grant from the cognitive neuroscience program. Preference will be given to projects requiring collaboration or interaction between at least two subfields of cognitive neuroscience. The goals are to encourage broad national participation in the development of the field and to facilitate the participation of investigators outside the major centers of cognitive neuroscience. Submissions will be reviewed by the program's advisory board. Grant support under this component is limited to $30,000 per year for two years. Indirect costs are to be included in the $30,000 maximum and may not exceed 10 percent of salaries and fringe benefits. Grants are not renewable after two years. The program is looking for innovative proposals that would, for example: * combine experimental data from cognitive psychology and neuroscience; * explore the implications of neurobiological methods for the study of the higher cognitive processes; * bring formal modeling techniques to bear on cognition; * use sensing or imaging techniques to observe the brain during conscious activity; * make imaginative use of patient populations to analyze cognition; * develop new theories of the human mind/brain system. This list of examples is necessarily incomplete but should suggest the general kind of proposals desired. Ideally, a small grant-in-aid for research should facilitate the initial exploration of a novel or risky idea, with success leading to more extensive funding from other sources. TRAINING GRANTS A limited number of grants will also be awarded to support training investigators in cognitive neuroscience. Here again, the objective is to support proposals of exceptional merit that are underfunded or unlikely to be funded from other sources. Training grants to support Ph.D. thesis research of graduate students will not be funded. Some postdoctoral awards for exceptional young scientists will be available; postdoctoral stipends will be funded for up to three years at prevailing rates at the host institution. Highest priority will be given to candidates seeking postdoctoral training outside the field of their previous training. Innovative programs for training young scientists, or broadening the experience of senior scientists, are also encouraged. Some examples of appropriate proposals follow. * Collaboration between a junior scientist in a relevant discipline and a senior scientist in a different discipline has been suggested as an effective method for developing the field. * Two senior scientists might wish to learn each other's discipline through a collaborative project. * An applicant might wish to visit several laboratories in order to acquire new research techniques. * Senior researchers might wish to investigate new methods or technologies in their own fields that are unavailable at their home institutions. Here again, examples can only suggest the kind of training experience that might be considered appropriate. APPLICATIONS Applicants should submit five copies of a proposal that does not exceed 5,000 words. Proposals for research grants should include: * a description of the work to be done and where it might lead; * an account of the investigator's professional qualifications to do the work. Proposals for training grants should include: * a description of the training sought and its relationship to the applicant's work and previous training; * a statement from the mentor as well as the applicant concerning the acceptability of the training plan. Proposals for both research grants and training grants should include: * an account of any plans to collaborate with other cognitive neuroscientists; * a brief description of the available research facilities; The proposal must be accompanied by the following separate information: * a brief, itemized budget and budget justification for the proposed work, including direct and indirect costs (indirect costs may not exceed 10 percent of salaries and fringe benefits); * curriculum(a) vitae of the participating investigator(s); * evidence that the sponsoring organization is a nonprofit, tax-exempt institution; * an authorized form indicating clearance for the use of human and animal subjects; * an endorsement letter from the officer of the sponsoring institution who will be responsible for administering the grant. No other appended documents will be accepted for evaluation, and any incomplete applications will be returned to the applicant. The advisory board reviews proposals twice a year. Applications must be postmarked by the deadlines of February 1 and August 1 to be considered for review. INFORMATION For more information contact: McDonnell-Pew Program in Cognitive Neuroscience Green Hall 1-N-6 Princeton University Princeton, New Jersey 08544-1010 Telephone: 609-258-5014 Facsimile: 609-258-3031 Email: cns@confidence.princeton.edu ADVISORY BOARD Emilio Bizzi, M.D. Eugene McDermott Professor in the Brain Sciences and Human Behavior Chairman, Department of Brain and Cognitive Sciences Whitaker College Massachusetts Institute of Technology, E25-526 Cambridge, Massachusetts 02139 Sheila Blumstein, Ph.D. Professor of Cognitive and Linguistic Sciences Dean of the College Brown University University Hall, Room 218 Providence, Rhode Island 02912 Stephen J. Hanson, Ph.D. Group Leader Learning and Knowledge Acquisition Research Group Siemens Research Center 755 College Road East Princeton, New Jersey 08540 Jon Kaas, Ph.D. Centennial Professor Department of Psychology Vanderbilt University Nashville, Tennessee 37240 George A. Miller, Ph.D. James S. McDonnell Distinguished University Professor of Psychology Department of Psychology Princeton University Princeton, New Jersey 08544-1010 Mortimer Mishkin, Ph.D. Laboratory of Neuropsychology National Institute of Mental Health 9000 Rockville Pike Building 9, Room 1N107 Bethesda, Maryland 20892 Marcus Raichle, M.D. Professor of Neurology and Radiology Division of Radiation Sciences Mallinckrodt Institute of Radiology at Washington University Medical Center 510 S. Kingshighway Blvd., Campus Box 8131 St. Louis, Missouri 63110 Endel Tulving, Ph.D. Department of Psychology University of Toronto Toronto, Ontario M5S 1A1 Canada ------------------------------ End of Neuron Digest [Volume 6 Issue 62] ****************************************