Okinawa Computational Neuroscience Course

Schedule

Abstracts of Lectures

 

Tuesday, November 9th

11:30-
Registration
 
13:20-13:40
Opening
 
13:40-16:40
Alex Pouget: Population coding
 
17:30-20
Welcome party
Wednesday, November 10th
  9-12 Jeff Bilmes: Dynamic graphical models: Theory and applications
  13:30-16 Student presentations on their own works, part 1
  19-22 Adrianne Fairhall: Spike coding
Thursday, November 11th
 
9-12
Peter Latham: Computing with population codes
 
13:30-16
Student presentations on their own works, part 2
 
19-22
Jonathan Pillow: Estimating neuron models from spike trains
Friday, November 12th
 
9-12
Richard Zemel: Coding and decoding uncertainty
 
13:30-16:30
Excursion to OIST campus site in Onna village
 
19-22
Michael Shadlen: A Neural Mechanism for Making Decisions
Saturday, November 13th
  9-12 Emanuel Todorov: Optimality principles in sensorimotor control
  13:30-16:30 Karl Friston: Dynamic causal modelling
  18-20 Barbecue party
Sunday, November 14th: Day off
Monday, November 15th
 
9-12
Shun-ichi Amari: Statistical approach to neural learning and population coding
 
19-22
David Knill: Bayesian models of sensory cue integration
Tuesday, November 16th
 
9-12
Rajesh Rao: Probabilistic Models of Cortical Computation
 
13:30-17:00
Excursion to OIST Initial Research Project Lab. in Gushikawa city
 
19-22
Konrad Koerding: Bayesian combination of priors and perception: Optimality in sensorimotor integration
Wednesday, November 17th
 
9-12
Wolfgang Maass: Computational properties of neural micorcircuit models
 
19-22
Barry Richmond: Neural coding: Determinsim vs stochasticity
Thursday, November 18th
 
9-12
Bruno Olshausen: Representing what and where in time-varying images
 
19-22
Tai Sing Lee:Cortical mechanisms of visual scene segmentation -- a hierarchical Bayesian perspective --
Friday, November 19th
 
9-12
Anthony Bell: Unsupervised machine learning with spike timings
 
13:30-17
Presentations of student projects
 
19-21
Farewell party

 

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