| Project/Area Number |
20500279
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Bioinformatics/Life informatics
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| Research Institution | The Institute of Physical and Chemical Research |
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Principal Investigator |
OKAMOTO Hiroshi The Institute of Physical and Chemical Research, 脳回路機能理論研究チーム, 客員研究員 (00374067)
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| Project Period (FY) |
2008 – 2010
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| Project Status |
Completed (Fiscal Year 2010)
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| Budget Amount *help |
¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
Fiscal Year 2010: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2009: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2008: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
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| Keywords | 脳型記憶想起 / 時間積分 / 複雑ネットワーク / 時系列想起 / ベイズ推定 / ニューラルネットワーク / ヒステリシス / 確率過程 / 時系列 / 隣接行列 / 記憶想起 / 引用ネットワーク / 連続アトラクター / 揺らぎ / 準安定 / ベイズ / 経路積分 / 双安定 / 漸次的持続活性 |
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| Research Abstract |
The purpose of this study is to develop a method of extracting temporally organized information by analogy to memory retrieval in the brain. We have demonstrated that stochastic dynamics of a grand network of recurrent neural networks, which models a minimal structure of cortical circuits, can produce transient and sequential activation of neurons. Different cue presentations represented by the initial state of grand network activation generate different temporal sequences. Statistical-mechanical exploration has revealed that retrieval of temporal sequences by this model conforms to Bayesian inference.
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