Bayesian Brain course in Okinawa, Nov 9-19th

Call for Applications
OKINAWA COMPUTATIONAL NEUROSCIENCE COURSE
November 9-19, 2004. Okinawa, Japan.

The special topic for this year’s course is “Bayesian Brain: Probabilistic
Approaches to Neural Coding and Learning.” Lectures by leading theoretical
and experimental neuroscientists will be given in the morning and evening,
and the afternoon will be open for free discussions and student projects.

http://www.irp.oist.jp/ocnc

The aim of Okinawa Computational Neuroscience Course is to provide
opportunities for young researchers with theoretical backgrounds to learn
up-to-date neurobiological findings, and those with experimental
backgrounds to have hands-on experience in computational modeling.
We invite graduate students and postgraduate researchers to participate
in the course, held from November 9th through 19th at Bankoku Shinryokan,
a seaside conference facility that hosted 2000 Okinawa Summit.

The special topic for this year’s course is “Bayesian Brain: Probabilistic
Approaches to Neural Coding and Learning.” Lectures by leading theoretical
and experimental neuroscientists will be given in the morning and evening,
and the afternoon will be open for free discussions and student projects.
Each student will give a short presentation of his/her current work at the
beginning of the course and present the summary of his/her project work at
the end of the course.

Those interested in attending the course should send the materials below
by the course web page, e-mail, or postal mail to the course secretariat by
SEPTEMBER 10TH. We will accept 30 students by considering the matching
of each student’s background and motivation to the course content, and also
by considering the balance of members’ research disciplines, geographic
origins, and genders. The sponsor will provide lodging expenses during
the course and a support for travel to Okinawa.

This course is the second of the tutorial courses sponsored by the Cabinet
Office of the Japanese government as a precursory activity for Okinawa
Institute of Science and Technology. We hope that this course will be a good
opportunity for theoretical and experimental neuroscientists to meet together
and to explore the attractive nature and culture of Okinawa, the southernmost
island prefecture of Japan.

********
Okinawa Computational Neuroscience Course (OCNC 2004)
– Bayesian Brain: Probabilistic Approaches to Neural Coding and Learning –

Date: November 9th to 19th, 2004
Place: Bankoku Shinryo-kan (http://www.shinryokan.com/)
Lodging: The Busena Terrace (http://www.terrace.co.jp/index-e.html)

Sponsor:
Okinawa Institute of Science and Technology Project, Cabinet Office, Japan
Co-sponsors:
Japanese Neural Network Society
Center of Excellence Program, Tamagawa University
Center of Excellence Program, Kyushu Institute of Technology
Advisory Board:
Sydney Brenner, Salk Institute
Masao Ito, RIKEN Brain Science Institute
Terry Sejnowski, Salk Institute
Susumu Tonegawa, MIT
Torsten Wiesel, Rockfeller University
Co-organizers:
Kenji Doya, Initial Research Project, Okinawa Institute of Science and Technology
Shin Ishii, Nara Institute of Science and Technology
Alex Pouget, University of Rochester
Rajesh Rao, University of Washington

LECTURES (confirmed speakers and topics)

Theoretical Foundations
Shun-ichi Amari (RIKEN Brain Science Inst.):
Statistical approach to neural learning and population coding
Neurobiological Foundations
Barry Richmond (National Inst. of Health): Neural coding
Alex Pouget (U. Rochester): Population coding
Adrienne Fairhall (U. Washington): Spike Coding
Computational Modeling
Anthony Bell (Redwood Neuroscience Inst.):
Unsupervised machine learning with spike timings: rigorous results
Peter Latham (UCL): Computing with population codes
Richard Zemel (U. Toronto): Coding and decoding uncertainty
Rajesh Rao (U. Washington): Bayesian computation in cortical networks
Bruno Olshausen (UC Davis):
Representing what and where in=A0 time-varying images
Emanuel Todorov (UC, San Diego):
Optimality principles in sensorimotor control
Experimental Approaches
Tai-Sing Lee (Carnegie Mellon U.):
Hierarchical Bayesian inference in=A0visual cortex
David Knill (U. of Rochester): Multiple cue integration
Konrad Koerding (UCL): Bayesian combination of priors and perception
Michael Shadlen (U. of Washington): Decision making
Karl Friston (UCL): Dynamic causal modelling

APPLICATION

Please send the following through the web application page to be opened
in early August (http://www.irp.oist.jp/ocnc/), an e-mail (ocnc@irp.oist.jp),
or postal mail to the secretariat below by SEPTEMBER 10TH.

1) Name, 2) Date of birth, 3) Gender, 4) Nationality, 5) Affiliation,
6) Postal address, 7) Phone, 8) Fax, 9) E-mail, 10) Web page URL (if any),
11) Educational background, 12) Work experience, 13) List of publications,
14) Research interests (up to 500 words), 15) Motivations for attending the
course (up to 500 words), 16) Two letters of recommendation.

The items 11) to 14) can be replaced by a CV. Letters of recommendation
should be sent directly from the referees to the secretariat by e-mail or postal mail.

SECRETARIAT

Okinawa Computational Neuroscience Course
c/o Initial Research Project, Okinawa Institute of Science and Technology
12-22 Suzaki, Gushikawa
Okinawa 904-2234, Japan
Phone: +81-98-921-3795
Fax: +81-98-934-1401
E-mail: ocnc@irp.oist.jp

For updated information, please visit the web page: http://www.irp.oist.jp/ocnc

Advertisements

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s