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Neuron Digest Volume 06 Number 62
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]
****************************************
