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Hippocampal-neocortical episodic memory model

Research Project

Project/Area Number 25330286
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Research Field Soft computing
Research InstitutionUniversity of Yamanashi

Principal Investigator

HATTORI Motonobu  山梨大学, 総合研究部, 准教授 (40293435)

Project Period (FY) 2013-04-01 – 2016-03-31
Project Status Completed (Fiscal Year 2015)
Budget Amount *help
¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000)
Fiscal Year 2015: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2014: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2013: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Keywords海馬 / 大脳皮質 / エピソード記憶 / 破局的忘却 / カオスニューロン / 神経新生 / スパイクタイミング依存性シナプス可塑性 / 海馬モデル
Outline of Final Research Achievements

In this research, we have constructed a hippocampal-neocortical model for episodic memories based on physiological, anatomical and neuropsychological findings and examined its characteristics by computer simulation. As the results, we have shown that the proposed model can deal with general temporal sequences owing to the neurogenesis in DG, chaotic neurons in CA3, and the asymmetric spike timing dependent synaptic plasticity introduced to the learning of CA3. Moreover, we have revealed that the chaotic recall in the hippocampal network much contributes to extract stored sequences, reduce catastrophic forgetting in the neocortical network, and the consolidation of the long-term memory.

Report

(4 results)
  • 2015 Annual Research Report   Final Research Report ( PDF )
  • 2014 Research-status Report
  • 2013 Research-status Report
  • Research Products

    (7 results)

All 2016 2015 2014 2013

All Journal Article (2 results) (of which Peer Reviewed: 2 results) Presentation (5 results) (of which Int'l Joint Research: 2 results)

  • [Journal Article] A biologically inspired dual-network memory model for reduction of catastrophic forgetting2014

    • Author(s)
      Hattori, M.
    • Journal Title

      Neurocomputing

      Volume: 134 Pages: 262-268

    • DOI

      10.1016/j.neucom.2013.08.044

    • Related Report
      2013 Research-status Report
    • Peer Reviewed
  • [Journal Article] Dual-Network Memory Model for Temporal Sequences2013

    • Author(s)
      Hattori, M. and Suzuki, R.
    • Journal Title

      International Journal of Computer, Information Science and Engineering

      Volume: 7 Pages: 73-77

    • Related Report
      2013 Research-status Report
    • Peer Reviewed
  • [Presentation] A Hippocampal Model for Episodic Memory using Neurogenesis and Asymmetric STDP2016

    • Author(s)
      Hattori, M. and Kobayashi, Y.
    • Organizer
      IEEE and INNS International Joint Conference on Neural Networks
    • Place of Presentation
      Vancouver, Canada
    • Year and Date
      2016-07-23
    • Related Report
      2015 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Applying Pseudorehearsal to Multilayer Neural Networks Trained by No-Prop Algorithm2015

    • Author(s)
      Hattori, M. and Hosaka, T.
    • Organizer
      The 16th International Conference on Neural Networks
    • Place of Presentation
      Rome, Italy
    • Year and Date
      2015-11-07
    • Related Report
      2015 Annual Research Report
    • Int'l Joint Research
  • [Presentation] 神経新生と非対称STDPを用いた海馬エピソード記憶モデル2015

    • Author(s)
      小林良視, 服部元信
    • Organizer
      第25回日本神経回路学会全国大会
    • Place of Presentation
      電気通信大学(東京都・調布市)
    • Year and Date
      2015-09-02
    • Related Report
      2015 Annual Research Report
  • [Presentation] 擬似パターンを用いた知識転写によるニューラルネットワークの構造獲得2015

    • Author(s)
      齋藤成人,服部元信
    • Organizer
      電子情報通信学会総合大会
    • Place of Presentation
      立命館大学(滋賀県草津市)
    • Year and Date
      2015-03-10 – 2015-03-13
    • Related Report
      2014 Research-status Report
  • [Presentation] Dual-Network Memory Model for Temporal Sequences2013

    • Author(s)
      Hattori, M. and Suzuki, R.
    • Organizer
      International Conference on Artificial Intelligence and Neural Networks
    • Place of Presentation
      Phuket, Thailand
    • Related Report
      2013 Research-status Report

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Published: 2014-07-25   Modified: 2019-07-29  

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