Design and evaluation of brain-inspired predictive coding networks based on the free-energy principle for novel neuromorphic hardware
Author:
Affiliation:
1. Graduate School of Information Science and Technology, Hokkaido University
2. Faculty of Information Science and Technology, Hokkaido University
3. Graduate School of Science, Osaka University
Publisher
Institute of Electronics, Information and Communications Engineers (IEICE)
Subject
Rehabilitation,Physical Therapy, Sports Therapy and Rehabilitation,General Medicine
Link
https://www.jstage.jst.go.jp/article/nolta/15/1/15_107/_pdf
Reference20 articles.
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2. [2] R. Rao and D. Ballard, “Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects,” Nature Neuroscience, vol. 2, no. 1, pp. 79-87, January 1999. DOI: 10.1038/4580
3. [3] K. Friston and S. Kiebel, “Predictive coding under the free-energy principle,” Patterns, vol. 3, no. 12, December 2022. DOI: 10.1016/j.patter.2022.100639
4. [4] A. Ali, N. Ahmad, E. Groot, M.A.J. Gerven, and T.C. Kietzmann, “Predictive coding is a consequence of energy efficiency in recurrent neural networks,” Jornal of Physiology, vol. 364, no. 1521, pp. 1211-1221, May 2009. DOI: 10.1098/rstb.2008.0300
5. [5] P. Merolla, J. Arthur, R. Alvarez-Icaza, A. Cassidy, J. Sawada, F. Akopyan, B. Jackson, N. Imam, C. Guo, Y. Nakamura, B. Brezzo, I. Vo, S. Esser, R. Appuswamy, B. Taba, A. Amir, M. Flickner, W. Risk, R. Manohar, and D. Modha, “A million spiking-neuron integrated circuit with a scalable communication network and interface,” Science, vol. 345, no. 6197, 2014. DOI: 10.1126/science.1254642
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