Estimations of neural networks by fluctuations of neuron spikes
| Project/Area Number |
18079003
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| Research Category |
Grant-in-Aid for Scientific Research on Priority Areas
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| Allocation Type | Single-year Grants |
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| Review Section |
Science and Engineering
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| Research Institution | The University of Tokyo |
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Principal Investigator |
OKADA Masato The University of Tokyo, 大学院・新領域創成科学研究科, 教授 (90233345)
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| Co-Investigator(Kenkyū-buntansha) |
MIMURA Kazushi 広島市立大学, 情報学部, 准教授 (40353297)
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| Project Period (FY) |
2006 – 2009
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| Project Status |
Completed (Fiscal Year 2009)
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| Budget Amount *help |
¥64,900,000 (Direct Cost: ¥64,900,000)
Fiscal Year 2009: ¥18,200,000 (Direct Cost: ¥18,200,000)
Fiscal Year 2008: ¥19,700,000 (Direct Cost: ¥19,700,000)
Fiscal Year 2007: ¥19,700,000 (Direct Cost: ¥19,700,000)
Fiscal Year 2006: ¥7,300,000 (Direct Cost: ¥7,300,000)
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| Keywords | 多体問題 / 統計力学 / 神経科学 / BMI / データマイニング / 計力学 |
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| Research Abstract |
It has become possible to make simultaneous measurements of neural activity (spikes) in large numbers of neurons with large arrays of electrodes. Significant advantage of the statistical mechanical informatics (SMI) is to extract a macroscopic description of the system with a small number of parameters by performing reduction of many microscopic degrees of freedom. Hierarchy, reduction, and macroscopic description should also be essential in order to understand the brain. From this point of view, we proposed new SMI frameworks for neural network models, and methods for analyzing neuronal spike data based on the information theory and the Bayesian inference.
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Report
(6 results)
Research Products
(144 results)
