Authors
Hiroto Tamura1, *, Yuichi Katori2, 3, Kazuyuki Aihara3
1Graduate School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
2Future University Hakodate, 116-2 Kamedanakano-cho, Hakodate, Hokkaido 041-8655, Japan
3Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan
*Corresponding author. Email: [email protected]
Corresponding Author
Hiroto Tamura
Received 12 October 2018, Accepted 28 November 2018, Available Online 25 June 2019.
DOI
https://doi.org/10.2991/jrnal.k.190531.009
Keywords
Visual system; perception; predictive coding; reservoir computing; context; nonlinear dynamics
Abstract
The predictive coding is a widely accepted hypothesis on how our internal visual perceptions are generated. Dynamical predictive coding with reservoir computing (PCRC) models have been proposed, but how they work remains to be clarified. Therefore, we first construct a simple PCRC network and analyze the nonlinear dynamics underlying it. Since the influence of contexts is another important factor on the visual perception, we also construct PCRC networks for the context-dependent task, and observe their attractor-landscapes on each context.
Copyright
© 2019 The Authors. Published by ALife Robotics Corp. Ltd.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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