| Presentation | 2010-01-19 Hidden Structures Detection in Nonstationary Spike Trains Ken TAKIYAMA, Masato OKADA, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | We propose an algorithm that can simlutaneously estimate nonstationary firing rates, timings of transitions of neural states and numbers of neural states using only one spike train. Our algorithm consists of a Switching State Space Model (SSSM). We construct estimation and learning algorithms for a non-Gaussian SSSM, whose non- Gaussian property is caused by a binary observation process, using variational Bayes and local variational methods. The variational Bayes method enables to estimate the numbers of neural states based on automatic relevance determination. Synthetic data analysis reveals that our algorithm can accurately estimate a nonstationary firing rate and detect timings of transitions of neural states compared to previous methods. We apply our algorithm to neural data on area MT. The analysis of real data suggests that our algorithm can estimate nonstationary firing rates, timings of neural state transitions and numbers of neural states even for real data. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | nongaussian switching state space model / variational bayes method / local variational method / firing rate estimation / change point detection / neural state |
| Paper # | NC2009-83 |
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| Conference Information | |
| Committee | NC |
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| Conference Date | 2010/1/11(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) | Hidden Structures Detection in Nonstationary Spike Trains |
| Sub Title (in English) | |
| Keyword(1) | nongaussian switching state space model |
| Keyword(2) | variational bayes method |
| Keyword(3) | local variational method |
| Keyword(4) | firing rate estimation |
| Keyword(5) | change point detection |
| Keyword(6) | neural state |
| 1st Author's Name | Ken TAKIYAMA |
| 1st Author's Affiliation | Graduate School of Frontier Sciences, The University of Tokyo() |
| 2nd Author's Name | Masato OKADA |
| 2nd Author's Affiliation | Graduate School of Frontier Sciences, The University of Tokyo:Brain Science Institute, RIKEN |
| Date | 2010-01-19 |
| Paper # | NC2009-83 |
| Volume (vol) | vol.109 |
| Number (no) | 363 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |