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Paper Abstract and Keywords
Presentation 2009-01-20 14:40
Which model can properly describe dynamics and smoothness of firing rate?
Ken Takiyama (The Univ. of Tokyo), Kentaro Katahira, Masato Okada (The Univ. of Tokyo/RIKEN) NC2008-98
Abstract (in Japanese) (See Japanese page) 
(in English) We construct the algorithm using belief propagation(BP), which algorithm simultaneously estimates
firing rate and calculates marginal likelihood. Our algorithm can determine the degree and the form of the firing
rate smoothness based on hyperparameter estimation and model selection by maximizing the marginal likelihood.
Prior distribution is Line process model, Gauss model, or Cauchy model. We discuss which model is appropriate
to describe the firing rate and whether appropriate model changes or not depending on the functional form of the
firing rate. We conduct two firing rate estimation experiments: the first firing rate evolves smoothly, but the second
firing rate involves discontinuity. The second experiment is assumed that the extrinsic stimuli whose timings are
entirely-unknown are added to the neuron. The Line process model shows the largest mariginal likelihood value of
the three models in both experiments. The Line process model also being able to estimate the unknown stimulus
timings, we show the effectivness of the Line process model in the firing estimation issue.
Keyword (in Japanese) (See Japanese page) 
(in English) Firing rate estimation / Belief propagation / Bayesian estimation / Line process / Gaussian graphical model / Hyperparameter estimation / Model selection /  
Reference Info. IEICE Tech. Rep., vol. 108, no. 383, NC2008-98, pp. 89-94, Jan. 2009.
Paper # NC2008-98 
Date of Issue 2009-01-12 (NC) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF NC2008-98

Conference Information
Committee NC  
Conference Date 2009-01-19 - 2009-01-20 
Place (in Japanese) (See Japanese page) 
Place (in English) Hokkaido Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Neural Dynamics, etc. 
Paper Information
Registration To NC 
Conference Code 2009-01-NC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Which model can properly describe dynamics and smoothness of firing rate? 
Sub Title (in English)  
Keyword(1) Firing rate estimation  
Keyword(2) Belief propagation  
Keyword(3) Bayesian estimation  
Keyword(4) Line process  
Keyword(5) Gaussian graphical model  
Keyword(6) Hyperparameter estimation  
Keyword(7) Model selection  
Keyword(8)  
1st Author's Name Ken Takiyama  
1st Author's Affiliation The university of Tokyo (The Univ. of Tokyo)
2nd Author's Name Kentaro Katahira  
2nd Author's Affiliation The University of Tokyo/RIKEN (The Univ. of Tokyo/RIKEN)
3rd Author's Name Masato Okada  
3rd Author's Affiliation The University of Tokyo/RIKEN (The Univ. of Tokyo/RIKEN)
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Speaker Author-1 
Date Time 2009-01-20 14:40:00 
Presentation Time 25 minutes 
Registration for NC 
Paper # NC2008-98 
Volume (vol) vol.108 
Number (no) no.383 
Page pp.89-94 
#Pages 6 
Date of Issue 2009-01-12 (NC) 

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