| Paper: | PS-2A.22 | ||
| Session: | Poster Session 2A | ||
| Location: | H Lichthof | ||
| Session Time: | Sunday, September 15, 17:15 - 20:15 | ||
| Presentation Time: | Sunday, September 15, 17:15 - 20:15 | ||
| Presentation: | Poster | ||
| Publication: | 2019 Conference on Cognitive Computational Neuroscience, 13-16 September 2019, Berlin, Germany | ||
| Paper Title: | A Study on a Correlation between a Predictive Model of Motion Pictures Imitating the Predictive Coding of the Cerebral Cortex and Brain Activity | ||
| Manuscript: | Click here to view manuscript | ||
| License: |  This work is licensed under a Creative Commons Attribution 3.0 Unported License. |
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| DOI: | https://doi.org/10.32470/CCN.2019.1410-0 | ||
| Authors: | Chihiro Fujiyama, Ochanomizu University, Japan; Shinji Nishimoto, Satoshi Nishida, National Institute of Information and Communications Technology, Japan; Hideki Asoh, National Institute of Advanced Industrial Science and Technology, Japan; Ichiro Kobayashi, Ochanomizu University, Japan | ||
| Abstract: | In recent years, deep neural networks inspired by the notion of predictive coding have been shown to make accurate predictions of future frames. In this study, we focus on a predictive neural network, one of such implementations to evaluate the relationship between natural and artificial neural networks. By using PredNet, a predictive neural architecture, we show that representations extracted from the architecture are correlative with brain activities evoked by natural movie stimuli. Our result gives a verification result on the theoretical hypothesis of predictive coding. | ||