Hidetoshi Urakubo

1.1k total citations
27 papers, 706 citations indexed

About

Hidetoshi Urakubo is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Molecular Biology. According to data from OpenAlex, Hidetoshi Urakubo has authored 27 papers receiving a total of 706 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Cognitive Neuroscience, 13 papers in Cellular and Molecular Neuroscience and 10 papers in Molecular Biology. Recurrent topics in Hidetoshi Urakubo's work include Neuroscience and Neuropharmacology Research (12 papers), Neural dynamics and brain function (11 papers) and Advanced Memory and Neural Computing (5 papers). Hidetoshi Urakubo is often cited by papers focused on Neuroscience and Neuropharmacology Research (12 papers), Neural dynamics and brain function (11 papers) and Advanced Memory and Neural Computing (5 papers). Hidetoshi Urakubo collaborates with scholars based in Japan, United States and France. Hidetoshi Urakubo's co-authors include Shin Ishii, Haruo Kasai, Sho Yagishita, Graham C. R. Ellis‐Davies, Akiko Hayashi‐Takagi, Shinya Kuroda, Robert C. Froemke, Yoshiyuki Kubota, Shigeyuki Oba and Keiko Tanaka and has published in prestigious journals such as Science, Journal of Neuroscience and PLoS ONE.

In The Last Decade

Hidetoshi Urakubo

25 papers receiving 698 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Hidetoshi Urakubo Japan 11 423 352 209 88 53 27 706
Badri Roysam United States 7 416 1.0× 290 0.8× 93 0.4× 73 0.8× 23 0.4× 13 711
James Kozloski United States 13 323 0.8× 349 1.0× 130 0.6× 58 0.7× 22 0.4× 43 749
J. J. Johannes Hjorth Sweden 14 553 1.3× 353 1.0× 239 1.1× 62 0.7× 131 2.5× 25 842
Torsten Bullmann Germany 13 635 1.5× 294 0.8× 222 1.1× 166 1.9× 52 1.0× 21 1.0k
Irina Erchova United Kingdom 13 489 1.2× 564 1.6× 103 0.5× 82 0.9× 11 0.2× 24 853
Zahid Padamsey United Kingdom 13 314 0.7× 178 0.5× 169 0.8× 72 0.8× 15 0.3× 20 639
Amanda J. Foust United Kingdom 14 503 1.2× 322 0.9× 162 0.8× 40 0.5× 20 0.4× 34 733
Christina M. Weaver United States 11 316 0.7× 238 0.7× 103 0.5× 23 0.3× 33 0.6× 23 519
Hana Roš United Kingdom 7 491 1.2× 462 1.3× 184 0.9× 49 0.6× 49 0.9× 7 788
Farran Briggs United States 16 534 1.3× 915 2.6× 194 0.9× 41 0.5× 20 0.4× 32 1.1k

Countries citing papers authored by Hidetoshi Urakubo

Since Specialization
Citations

This map shows the geographic impact of Hidetoshi Urakubo's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Hidetoshi Urakubo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hidetoshi Urakubo more than expected).

Fields of papers citing papers by Hidetoshi Urakubo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hidetoshi Urakubo. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Hidetoshi Urakubo. The network helps show where Hidetoshi Urakubo may publish in the future.

Co-authorship network of co-authors of Hidetoshi Urakubo

This figure shows the co-authorship network connecting the top 25 collaborators of Hidetoshi Urakubo. A scholar is included among the top collaborators of Hidetoshi Urakubo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hidetoshi Urakubo. Hidetoshi Urakubo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ezure, Tomonobu, Kyoichi Matsuzaki, Hidetoshi Urakubo, & Nobuhiko Ohno. (2025). Three-dimensional ultrastructural analysis of human skin with the arrector pili muscle interacting with the hair follicle epithelium. Scientific Reports. 15(1). 4195–4195.
2.
Pandey, Vikas, Tomohisa Hosokawa, Yasunori Hayashi, & Hidetoshi Urakubo. (2025). Multiphasic protein condensation governed by shape and valency. Cell Reports. 44(4). 115504–115504. 3 indexed citations
3.
Mursalimov, Sergey, Mami Matsumoto, Hidetoshi Urakubo, Е. В. Дейнеко, & Nobuhiko Ohno. (2023). Unusual nuclear structures in male meiocytes of wild-type rye as revealed by volume microscopy. Annals of Botany. 132(6). 1159–1174.
4.
Onai, Takayuki, Noritaka Adachi, Hidetoshi Urakubo, et al.. (2023). Ultrastructure of the lamprey head mesoderm reveals evolution of the vertebrate head. iScience. 26(12). 108338–108338. 1 indexed citations
5.
Kume, Hideaki, et al.. (2022). Tri-view two-photon microscopic image registration and deblurring with convolutional neural networks. Neural Networks. 152. 57–69. 6 indexed citations
6.
Urakubo, Hidetoshi, Sho Yagishita, Haruo Kasai, Yoshiyuki Kubota, & Shin Ishii. (2021). The critical balance between dopamine D2 receptor and RGS for the sensitive detection of a transient decay in dopamine signal. PLoS Computational Biology. 17(9). e1009364–e1009364. 5 indexed citations
7.
Urakubo, Hidetoshi, Sho Yagishita, Haruo Kasai, & Shin Ishii. (2020). Signaling models for dopamine-dependent temporal contiguity in striatal synaptic plasticity. PLoS Computational Biology. 16(7). e1008078–e1008078. 15 indexed citations
8.
Urakubo, Hidetoshi, et al.. (2020). Mu-net: Multi-scale U-net for two-photon microscopy image denoising and restoration. Neural Networks. 125. 92–103. 55 indexed citations
9.
Parajuli, Laxmi Kumar, Hidetoshi Urakubo, Hirohide Iwasaki, et al.. (2020). Geometry and the Organizational Principle of Spine Synapses along a Dendrite. eNeuro. 7(6). ENEURO.0248–20.2020. 18 indexed citations
10.
Urakubo, Hidetoshi, Torsten Bullmann, Yoshiyuki Kubota, Shigeyuki Oba, & Shin Ishii. (2019). UNI-EM: An Environment for Deep Neural Network-Based Automated Segmentation of Neuronal Electron Microscopic Images. Scientific Reports. 9(1). 19413–19413. 29 indexed citations
11.
Kobayashi, Chiaki, Kazuki Okamoto, Yasuhiro Mochizuki, et al.. (2018). GABAergic inhibition reduces the impact of synaptic excitation on somatic excitation. Neuroscience Research. 146. 22–35. 3 indexed citations
12.
Hayashi, Yuichiro, et al.. (2014). An explanation of an afterimage rotation illusion by focusing time of retinal ON/OFF response. IEICE Technical Report; IEICE Tech. Rep.. 113(500). 31–36. 1 indexed citations
13.
Yagishita, Sho, Akiko Hayashi‐Takagi, Graham C. R. Ellis‐Davies, et al.. (2014). A critical time window for dopamine actions on the structural plasticity of dendritic spines. Science. 345(6204). 1616–1620. 401 indexed citations
14.
Urakubo, Hidetoshi, et al.. (2014). Stochasticity in Ca2+ Increase in Spines Enables Robust and Sensitive Information Coding. PLoS ONE. 9(6). e99040–e99040. 5 indexed citations
15.
Urakubo, Hidetoshi, et al.. (2014). In Vitro Reconstitution of a CaMKII Memory Switch by an NMDA Receptor-Derived Peptide. Biophysical Journal. 106(6). 1414–1420. 18 indexed citations
16.
Hayashi, Yuichiro, Shin Ishii, & Hidetoshi Urakubo. (2014). A Computational Model of Afterimage Rotation in the Peripheral Drift Illusion Based on Retinal ON/OFF Responses. PLoS ONE. 9(12). e115464–e115464. 4 indexed citations
17.
Nakae, Ken, Yuji Ikegaya, Tomoe Ishikawa, et al.. (2014). A Statistical Method of Identifying Interactions in Neuron–Glia Systems Based on Functional Multicell Ca2+ Imaging. PLoS Computational Biology. 10(11). e1003949–e1003949. 6 indexed citations
18.
Urakubo, Hidetoshi, et al.. (2011). Analysis of Development of Direction Selectivity in Retinotectum by a Neural Circuit Model with Spike Timing-Dependent Plasticity. Journal of Neuroscience. 31(4). 1516–1527. 14 indexed citations
19.
Urakubo, Hidetoshi, et al.. (2008). Requirement of an Allosteric Kinetics of NMDA Receptors for Spike Timing-Dependent Plasticity. Journal of Neuroscience. 28(13). 3310–3323. 53 indexed citations
20.
Urakubo, Hidetoshi, Takeshi Aihara, Shinya Kuroda, Masataka Watanabe, & Shunsuke Kondo. (2004). Spatial Localization of Synapses Required for Supralinear Summation of Action Potentials and EPSPs. Journal of Computational Neuroscience. 16(3). 251–256. 10 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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