| Presentation | 2018-06-08 Application of tensor decomposition to chaotic itinerancy time series Takahiro Arai, Toshio Aoyagi, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Tensor decomposition is a typical method for analyzing resting-state BOLD signals. This method can decompose the observed spatiotemporal brain activity into time-independent spatial patterns with their time-dependent weights. Brain activity can be then regarded as transition among these spatial patterns. Some experimental results suggest that brain activity is chaotic itinerancy, which means chaotic transition among attractor-ruins. Tensor decomposition is expected to describe brain activity as transition among attractor-ruins, which correspond to the time-independent spatial patterns. From experimental time series data, however, there is no way to determine whether the dynamics exhibit chaotic itinerancy or not. Hence, in search of properties indicating chaotic itinerancy, we apply tensor decomposition to multi-dimensional time-series data generated from a simple mathematical model and examine the resultant tensor decomposition. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Chaotic itinerancy / Tensor decomposition / Dynamical system / Milnor attractor |
| Paper # | NLP2018-29,CCS2018-2 |
| Date of Issue | 2018-06-01 (NLP, CCS) |
| Conference Information | |
| Committee | NLP / CCS |
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| Conference Date | 2018/6/8(3days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Kyoto Terrsa |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Synchronization, Networks, etc |
| Chair | Norikazu Takahashi(Okayama Univ.) / Mikio Hasegawa(Tokyo Univ. of Science) |
| Vice Chair | Hiroaki Kurokawa(Tokyo University of Tech.) / Makoto Naruse(NICT) / Shigeki Shokawa(Kanagawa Inst. of Tech.) |
| Secretary | Hiroaki Kurokawa(Hiroshima Inst. of Tech.) / Makoto Naruse(Nippon Institute of Tech.) / Shigeki Shokawa(Tokyo City Univ.) |
| Assistant | Masayuki Kimura(Kyoto Univ.) / Yutaka Shimada(Saitama Univ.) / Yuusuke Kawakita(Kanagawa Inst. of Tech.) / Hiroyasu Ando(Univ. of Tsukuba) / Takashi Matsubara(Kobe Univ.) / Ryo Takahashi(AUT) |
| Paper Information | |
| Registration To | Technical Committee on Nonlinear Problems / Technical Committee on Complex Communication Sciences |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Application of tensor decomposition to chaotic itinerancy time series |
| Sub Title (in English) | |
| Keyword(1) | Chaotic itinerancy |
| Keyword(2) | Tensor decomposition |
| Keyword(3) | Dynamical system |
| Keyword(4) | Milnor attractor |
| 1st Author's Name | Takahiro Arai |
| 1st Author's Affiliation | Kyoto University(Kyoto Univ.) |
| 2nd Author's Name | Toshio Aoyagi |
| 2nd Author's Affiliation | Kyoto University(Kyoto Univ.) |
| Date | 2018-06-08 |
| Paper # | NLP2018-29,CCS2018-2 |
| Volume (vol) | vol.118 |
| Number (no) | NLP-75,CCS-76 |
| Page | pp.pp.7-12(NLP), pp.7-12(CCS), |
| #Pages | 6 |
| Date of Issue | 2018-06-01 (NLP, CCS) |