Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Tomoki Tokuda"'
Publikováno v:
Frontiers in Psychiatry, Vol 12 (2021)
Recently, the dimensional approach has attracted much attention, bringing a paradigm shift to a continuum of understanding of different psychiatric disorders. In line with this new paradigm, we examined whether there was common functional connectivit
Externí odkaz:
https://doaj.org/article/d135853648a643dfbc9014f4702eb334
Autor:
Tomoki Tokuda, Hirohiko Shimada
Publikováno v:
Scientific Reports, Vol 9, Iss 1, Pp 1-14 (2019)
Abstract Recently, slow earthquakes (slow EQ) have received much attention relative to understanding the mechanisms underlying large earthquakes and to detecting their precursors. Low-frequency earthquakes (LFE) are a specific type of slow EQ. In the
Externí odkaz:
https://doaj.org/article/2f4843eb473041379ea70dbe67d6c8e4
Autor:
Tomoki Tokuda, Ryo Tsuruda, Takuya Hara, Zongzi Hou, Haruki Kobayashi, Katsufumi Tanaka, Wataru Takarada, Takeshi Kikutani, Juan P. Hinestroza, Joselito M. Razal, Midori Takasaki
Publikováno v:
Materials, Vol 15, Iss 6, p 2209 (2022)
In this work, laser-heated electrospinning (LES) process using carbon dioxide laser was explored as an eco-friendly method for producing ultrafine fibers. To enhance the thinning of fibers and the formation of fiber structure, planar or equibiaxial s
Externí odkaz:
https://doaj.org/article/9a496cb62d734405aec2cdb706546948
Autor:
Katsuhiko Miyazaki, Kayoko W. Miyazaki, Akihiro Yamanaka, Tomoki Tokuda, Kenji F. Tanaka, Kenji Doya
Publikováno v:
Nature Communications, Vol 9, Iss 1, Pp 1-11 (2018)
Activation of serotonin neurons in the dorsal raphe nucleus promotes patience in waiting for future rewards. Here the authors show that this effect is maximal for high probability reward or high temporal reward uncertainty suggesting that it boosts t
Externí odkaz:
https://doaj.org/article/b0fdafa1f6534d138542e800b9bfc267
Autor:
Tomoki Tokuda, Ryo Tsuruda, Takuya Hara, Haruki Kobayashi, Katsufumi Tanaka, Wataru Takarada, Takeshi Kikutani, Juan P. Hinestroza, Joselito M. Razal, Midori Takasaki
Publikováno v:
Materials, Vol 13, Iss 24, p 5783 (2020)
Melt-electrospinning is an eco-friendly method for producing ultra-fine fibers without using any solvent. We prepared webs of poly(ethylene terephthalate) (PET) through melt-electrospinning using CO2 laser irradiation for heating. The PET webs compri
Externí odkaz:
https://doaj.org/article/d6d57fadc3d643508f4bd336190fce3e
Autor:
Tomoki Tokuda
Publikováno v:
PLoS ONE, Vol 13, Iss 3, p e0194079 (2018)
We propose a novel method to test the existence of community structure in undirected, real-valued, edge-weighted graphs. The method is based on the asymptotic behavior of extreme eigenvalues of a real symmetric edge-weight matrix. We provide a theore
Externí odkaz:
https://doaj.org/article/5de52cd87a1847f0a280ee62fe60423b
Publikováno v:
Neural Networks. 142:269-287
In neuroscience, the functional magnetic resonance imaging (fMRI) is a vital tool to non-invasively access brain activity. Using fMRI, the functional connectivity (FC) between brain regions can be inferred, which has contributed to a number of findin
Autor:
Tomoki Tokuda, Junichiro Yoshimoto, Yu Shimizu, Go Okada, Masahiro Takamura, Yasumasa Okamoto, Shigeto Yamawaki, Kenji Doya
Publikováno v:
PLoS ONE, Vol 12, Iss 10, p e0186566 (2017)
We propose a novel method for multiple clustering, which is useful for analysis of high-dimensional data containing heterogeneous types of features. Our method is based on nonparametric Bayesian mixture models in which features are automatically part
Externí odkaz:
https://doaj.org/article/78e30af3b33649a0ba9150444843ae52
Autor:
Keita Nakashima, Haruki Kobayashi, Midori Takasaki, Ryo Tsuruda, Katsufumi Tanaka, Tomoki Tokuda
Publikováno v:
Journal of Macromolecular Science, Part B. 58:592-602
In recent years drug-loaded nanofibers prepared using solution electrospinning methods have been actively studied. However, there are a number of problems connected to their solution electrospinnin...
Publikováno v:
BIBM
To uncover the rich temporal dynamics from the noisy fMRI time series, we propose a data-driven time series model: temporal reconstruction model, targets on reconstructing subsequences of fMRI time series via encoded contextual representations. This