JACIII Vol.15 No.8 pp. 1123-1130
doi: 10.20965/jaciii.2011.p1123


Solving the Binding Problem with Separated Extraction of Information by Oscillatory Self-Organizing Maps

Ryota Miyata* and Koji Kurata**

*Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, 4259-G5-17, Nagatsuta-cho, Midori-ku, Yokohama, Kanagawa 226-8502, Japan

**Faculty of Engineering, University of the Ryukyus, 1 Senbaru, Nishihara, Nakagami, Okinawa 903-0213, Japan

March 5, 2011
July 15, 2011
October 20, 2011
separated extraction of information, binding problem, synchronous firing hypothesis, oscillatory selforganizing map, selective Hebbian learning
One solution to the binding problem is the hypothesis that property binding should be represented by phaselocking among neuronal oscillatory firing. We introduce this synchronous firing hypothesis into the selforganizing maps, or SOMs. Here we propose oscillatory self-organizing maps. Using the computer simulation, we show that our model composed of the oscillatory SOMs can separate and extract information of the shapes and the colors from two simultaneous inputs, solving the binding problem.
Cite this article as:
R. Miyata and K. Kurata, “Solving the Binding Problem with Separated Extraction of Information by Oscillatory Self-Organizing Maps,” J. Adv. Comput. Intell. Intell. Inform., Vol.15 No.8, pp. 1123-1130, 2011.
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