Presentation | 2006-07-14 A neural circuit model for generating complex birdsong syntax Kentaro KATAHIRA, Kazuo OKANOAYA, Masato OKADA, |
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Abstract(in English) | The singing behavior of songbirds has been investigated as a model of sequence learning and production. The song of the Bengalese finches, Lonchura striata var. domestica, is especially well described by a finite state automaton including a stochastic transition of the song sequence. The note sequences of Bengalese finch songs are described as higher-order Markov processes. Focusing on the neural structure of songbirds, we propose a neural network model that generates higher-order Markov process. The neurons in a nucleus, the RA, encode each note and are activated by RA-projecting neurons in another nucleus, the HVC. We hypothesize that one note included in different chunks is encoded by different RA-projecting neuron groups. From this assumption, the output sequence of RA is a higher-order Markov process, even though the RA-projecting neurons in the HVC fire on first-order Markov processes. We propose the neural network model of local circuits in the HVC and explain the mechanism by which RA-projecting neurons transit stochastically on first-order Markov processes. We used a numerical simulation to show that our model can generate first-order Markov process song sequences. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | songbird / HVC / sequence generation / finite state automaton |
Paper # | NC2006-42 |
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Committee | NC |
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Conference Date | 2006/7/7(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) | A neural circuit model for generating complex birdsong syntax |
Sub Title (in English) | |
Keyword(1) | songbird |
Keyword(2) | HVC |
Keyword(3) | sequence generation |
Keyword(4) | finite state automaton |
1st Author's Name | Kentaro KATAHIRA |
1st Author's Affiliation | Graduate School of Frontier Sciences, The University of Tokyo:RIKEN Brain Science Institute() |
2nd Author's Name | Kazuo OKANOAYA |
2nd Author's Affiliation | RIKEN Brain Science Institute |
3rd Author's Name | Masato OKADA |
3rd Author's Affiliation | Graduate School of Frontier Sciences, The University of Tokyo:RIKEN Brain Science Institute |
Date | 2006-07-14 |
Paper # | NC2006-42 |
Volume (vol) | vol.106 |
Number (no) | 163 |
Page | pp.pp.- |
#Pages | 6 |
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