A neural network model of the episodic memory based on a word co-occurrence network
| Project/Area Number |
26540069
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| Research Category |
Grant-in-Aid for Challenging Exploratory Research
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| Allocation Type | Multi-year Fund |
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| Research Field |
Cognitive science
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| Research Institution | Future University-Hakodate |
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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)
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| Project Period (FY) |
2014-04-01 – 2016-03-31
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| Project Status |
Completed (Fiscal Year 2015)
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| Budget Amount *help |
¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
Fiscal Year 2015: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2014: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
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| 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 |
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| 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.
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Report
(3 results)
Research Products
(11 results)
