Presentation 2007-12-22
Numerical Simulation on Sequence Learning of Dual Network
Takeshi NAITOU, Toshiya IWAI,
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Abstract(in English) In order to realize the mechanics to maintain short term memory (STM) and to form the long term memory (LTM) from STM by a neural computing, Jensen et al. propose the dual network model by extracting physiological phenomena appeared in and around the Hippocampus. They indicate in their paper the possibility to learn two sequences that have a same item. The method of their numerical experiments for the sequence learning is not shown in their paper in detail. However, our numerical experiments of the sequence learning by using their model is not succeeded: Well learned synaptic weights of the first sequence are destroyed during the learning of the second sequence. By applying STDP to a learning rule of synaptic weights, two sequences which have a same item are successfully learned.
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Keyword(in English) Hippocampus / Short Term Memory / Long Term Memory / Sequence Learning
Paper # NC2007-77
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Committee NC
Conference Date 2007/12/15(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Numerical Simulation on Sequence Learning of Dual Network
Sub Title (in English)
Keyword(1) Hippocampus
Keyword(2) Short Term Memory
Keyword(3) Long Term Memory
Keyword(4) Sequence Learning
1st Author's Name Takeshi NAITOU
1st Author's Affiliation Department of Computer Science, Faculty of Engineering, Nihon University()
2nd Author's Name Toshiya IWAI
2nd Author's Affiliation Department of Computer Science, Faculty of Engineering, Nihon University
Date 2007-12-22
Paper # NC2007-77
Volume (vol) vol.107
Number (no) 410
Page pp.pp.-
#Pages 6
Date of Issue