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Paper Abstract and Keywords
Presentation 2021-03-04 14:10
What characteristics are acquired in coding self-motion from visual motion? -- Reconstruction of statistical relationship by neural network and its internal representation --
Daiki Nakamura, Hiroaki Gomi (NTT) NC2020-57
Abstract (in Japanese) (See Japanese page) 
(in English) Efficient coding is a prevailing computational models of sensory coding in the brain. If the sensory information is transformed by this coding mechanism, it could be expected that the neural activities represent sparse and efficient bases decomposed from input signals, independent of the output requirements. While this model was examined as the visual motion coding in the early visual processing, it has not been tested whether or not the characteristics derived by this coding are preserved in the motor output quickly induced by visual motion, which has been considered as a compensatory response to the self-motion. Here we examined this issue by developing a convolutional neural network (CNN) for estimating self-motion from sequential images taken by head-mount camera, and found a spatiotemporal frequency specificity which was similar to that of the motion-induced quick motor response. Interestingly, the specificity was affected by the velocity range of self-motion and a system limitation of the input image sampling. In addition, we analyzed internal representation of the CNN with several indexes employed in describing neural properties in visual cortexes, and found those representation changes in the CNN hierarchy as was found in the brain hierarchical processing. These results suggest that the spatiotemporal frequency specificity of the visually induced motor response is ascribed to the self-motion coding from visual motion rather than the efficient coding.
Keyword (in Japanese) (See Japanese page) 
(in English) Visual motion / Self-motion / Convolutional neural network / Manual following response / Ocular following response / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 403, NC2020-57, pp. 83-88, March 2021.
Paper # NC2020-57 
Date of Issue 2021-02-24 (NC) 
ISSN 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 NC2020-57

Conference Information
Committee NC MBE  
Conference Date 2021-03-03 - 2021-03-05 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Neuro Computing, Medical Engineering, etc. 
Paper Information
Registration To NC 
Conference Code 2021-03-NC-MBE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) What characteristics are acquired in coding self-motion from visual motion? 
Sub Title (in English) Reconstruction of statistical relationship by neural network and its internal representation 
Keyword(1) Visual motion  
Keyword(2) Self-motion  
Keyword(3) Convolutional neural network  
Keyword(4) Manual following response  
Keyword(5) Ocular following response  
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1st Author's Name Daiki Nakamura  
1st Author's Affiliation NTT Communication Science Laboratories (NTT)
2nd Author's Name Hiroaki Gomi  
2nd Author's Affiliation NTT Communication Science Laboratories (NTT)
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Speaker Author-1 
Date Time 2021-03-04 14:10:00 
Presentation Time 25 minutes 
Registration for NC 
Paper # NC2020-57 
Volume (vol) vol.120 
Number (no) no.403 
Page pp.83-88 
#Pages 6 
Date of Issue 2021-02-24 (NC) 

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