| Presentation | 2001/5/18 Mutual Information Analysis of Neural Codes through Joint Density Estimation by the Variational Bayes Method Tetsuya Furukawa, Masaaki Sato, Kenji Doya, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Mutual Information is often used to quantify the response property of a neuron to sensory or neural inputs. To calculate mutual information from experimental data, it is necessary to estimate the joint probability density of the input and the output. A common method is to make a histogram of data samples by discretizing them into appropriate bins. However, the result is highly dependent on the choice of bin size and is subject to approximation error, especially when the number of data is limited. We propose an alternative method in which the input-output joint density is estimated without discretization. Specifically, we use the variational Bayes method for estimating the parameters as well as the complexity of mixture Gaussian models. A better performance compared to conventional methods is verified through a numerical experiment with a simple Poisson neuron model. Its applicability to realistic problems is demonstrated in the experiment with electrically-coupled inferior olive neuron models. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | mutual information / variational Bayes method / model selection / mixture Gaussian model |
| Paper # | NC2001-4 |
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| Conference Information | |
| Committee | NC |
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| Conference Date | 2001/5/18(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Neurocomputing (NC) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Mutual Information Analysis of Neural Codes through Joint Density Estimation by the Variational Bayes Method |
| Sub Title (in English) | |
| Keyword(1) | mutual information |
| Keyword(2) | variational Bayes method |
| Keyword(3) | model selection |
| Keyword(4) | mixture Gaussian model |
| 1st Author's Name | Tetsuya Furukawa |
| 1st Author's Affiliation | Nara Institute of Science and Technology:Information Science Division, ATR International:CREST, Japan Science and Technology Corporation() |
| 2nd Author's Name | Masaaki Sato |
| 2nd Author's Affiliation | Information Science Division, ATR International:CREST, Japan Science and Technology Corporation |
| 3rd Author's Name | Kenji Doya |
| 3rd Author's Affiliation | Nara Institute of Science and Technology:Information Science Division, ATR International:CREST, Japan Science and Technology Corporation |
| Date | 2001/5/18 |
| Paper # | NC2001-4 |
| Volume (vol) | vol.101 |
| Number (no) | 94 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |