Presentation | 2014-01-20 Efficient Phase Response Curve Estimation from Colored Spike Triggered Average Kazuhiko MORINAGA, Ryota MIYATA, Toru AONISHI, |
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Abstract(in English) | Phase response curve (PRC) is an important measure to study neural ensemble synchrony. Recently, for this purpose several groups have tried to estimate the PRC from real neurons. Ermentrout et al. derived an equation that relates the PRC to the spike triggered average (STA) when applying white noise to oscillatory neurons. In this paper, we derive an equation that relates the PRC and STA when using colored noise. Here, the STA with colored noise is referred to as a colored spike triggered average (cSTA). On the basis of this relation, we propose a method for estimation of the PRC from the cSTA. Our numerical results suggest that the convergence speed of cSTA to its asymptotic value is faster than that of STA with white noise, and our estimation method can provide the more accurate PRC from the cSTA than from the STA with white noise under finite sample size situations. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Phase Response Curve / Spike Triggered Average / Colored Noise |
Paper # | NC2013-67 |
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Committee | NC |
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Conference Date | 2014/1/13(1days) |
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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) | Efficient Phase Response Curve Estimation from Colored Spike Triggered Average |
Sub Title (in English) | |
Keyword(1) | Phase Response Curve |
Keyword(2) | Spike Triggered Average |
Keyword(3) | Colored Noise |
1st Author's Name | Kazuhiko MORINAGA |
1st Author's Affiliation | Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology() |
2nd Author's Name | Ryota MIYATA |
2nd Author's Affiliation | Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology |
3rd Author's Name | Toru AONISHI |
3rd Author's Affiliation | Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology |
Date | 2014-01-20 |
Paper # | NC2013-67 |
Volume (vol) | vol.113 |
Number (no) | 382 |
Page | pp.pp.- |
#Pages | 6 |
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