視覚的注意のパルスニューラルネットワークモデル

• 齋木 潤

  京都大学大学院情報学研究科

書誌事項

タイトル別名

• A Pulsed Neural Network Model for Selective Visual Attention
• シカクテキ チュウイ ノ パルスニューラルネットワークモデル

抄録

Pulsed neural network models can account for the cognitive processes in which internal states change rapidly and abruptly. This study constructed a pulsed neural network model for selective visual attention based on the temporal tagging hypothesis. According to the temporal tagging hypothesis, the effect of visual attention reflects the modulation of spatiotemporal correlation of neural activities, not the modulation of firing rates. The proposed model produced the temporal synchrony of spikes purely within the simple spike response model framework. The model could simulate the data from Moran & Desimone (1985), and showed that simple pulsed neural networks without excessive neurophysiological details were at the appropriate level for the models of visual cognition. Compared with traditional connectionist models, pulsed neural network models appear to be the better framework to deal with real-time temporal dynamics of cognitive process including feature binding.

収録刊行物

• 認知科学

  認知科学 9 (1), 120-134, 2002

  日本認知科学会

キーワード

• パルスニューラルネットワーク
• 視覚的注意
• 同期発火
• 注意の抑制効果

詳細情報

• CRID: 1390001204482435328
• NII論文ID: 130004491309
• NII論文ID: 10009707621
• NII書誌ID: AN1047304X
• DOI: 10.11225/jcss.9.120
• ISSN: 18815995
• ISSN: 13417924
• NDL書誌ID: 025099118
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I025099118
• 本文言語コード: ja
• データソース種別:
  • JaLC
  • NDL
  • CiNii Articles
• 抄録ライセンスフラグ: 使用不可