学術論文

基本情報

氏名 池上 高志
氏名(カナ) イケガミ タカシ
氏名(英語) Takashi Ikegami
所属
職名 センター特任教授
researchmap研究者コード
researchmap機関

名称

Spiking neural networks produce informational closure by stimulus avoidance

単著、共著の別

共著

年月日

2023

発行所等

Biosystems, 104972

出版社

巻・号

開始ページ

終了ページ

査読の有無

概要

Atsushi Masumori and Takashi Ikegami
URL: https://www.sciencedirect.com/science/article/pii/S0303264723001478
Original Abstract: The concept of Learning by Stimulus Avoidance (LSA) has been proposed in recent literature, and the methods of avoiding stimuli: action, prediction, and separation appear to align well with the formation of Bertschinger’s informational closure. In this study, we provide experimental evidence demonstrating that spiking neural networks, which avoid stimuli, can indeed facilitate the emergence of informational closure. The established link between LSA and informational closure lays the foundation for further exploration of autopoietic relationships and the self-organization of closure within neural networks.
Summary (EN): Connects Learning by Stimulus Avoidance (LSA) to Bertschinger's informational closure, and shows experimentally that spiking neural networks that avoid stimuli facilitate the emergence of informational closure—laying groundwork for studying autopoietic, self-organized closure within neural networks.
概要(日本語): 刺激回避による学習(Learning by Stimulus Avoidance, LSA)と、Bertschingerの情報的閉鎖(informational closure)との対応を論じる。刺激を回避するスパイキングニューラルネットワークが情報的閉鎖の創発を促すことを実験的に示し、神経回路における自己組織的な閉鎖性・オートポイエーシス的関係を探る基盤を与える。