PATON : 文脈依存性を表現する動的神経回路網モデル PATON : A Dynamic Neural Network Model of Context Dependent Memory Access

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著者

    • 大森 隆司 OMORI Takashi
    • 東京農工大学大学院生物システム応用科学研究科 Graduate School of Bio-Appllcations and Systems Engineering, Tokyo University of Agriculture & Technology

抄録

In our real life, it is well known that our cognitive process is always influenced by our environment. It is called as "context dependency" of the cognition. In this paper, we propose a memory model "PATON" that is based on a macroscopic structure of a cortico-hippocampal memory system; it has three components of a symbolic layer, a pattern layer, and an attentional system. The attentional system sends signals to control a change of the model's structure dynamically. The change induces a modulation of metric between memorized items. Computer simulation shows an association process dependent upon a context based on the modulation.

収録刊行物

  • 日本神経回路学会誌 = The Brain & neural networks

    日本神経回路学会誌 = The Brain & neural networks 3(3), 81-89, 1996-09-05

    Japanese Neural Network Society

参考文献:  11件中 1-11件 を表示

被引用文献:  24件中 1-24件 を表示

各種コード

  • NII論文ID(NAID)
    10008841165
  • NII書誌ID(NCID)
    AA11658570
  • 本文言語コード
    JPN
  • 資料種別
    ART
  • ISSN
    1340766X
  • データ提供元
    CJP書誌  CJP引用  J-STAGE 
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