A neural network model of the episodic memory based on a word co-occurrence network

2015 Fiscal Year Final Research Report

• Project/Area Number: 26540069
• Research Category: Grant-in-Aid for Challenging Exploratory Research
• Allocation Type: Multi-year Fund
• Research Field: Cognitive science
• Research Institution: Future University-Hakodate
• Principal Investigator: Sato Naoyuki 公立はこだて未来大学, システム情報科学部, 教授 (70312668)
• Project Period (FY): 2014-04-01 – 2016-03-31
• Keywords: 脳 / 神経科学 / ニューラルネットワーク / 認知科学 / 視覚 / 記憶

Outline of Final Research Achievements

Neural representation of complicated experiences in daily life is a fundamental issue for the understanding of the episodic memory. In this study, a neural representation analogous to a word co-occurrence network in a large text corpus was hypothesized as a cortical representation and it was evaluated by electroencephalogram (EEG) experiment and neural modeling using computer simulation. Results indicated that the hypothesized representation was available for detecting memory-related EEG components and explaining the memory based on a hippocampal network. It was suggested that the word co-occurrence network can produce a clue for the understanding of the episodic memory.

Free Research Field

計算論的神経科学