Roman Borisyuk

2.0k total citations
87 papers, 1.3k citations indexed

About

Roman Borisyuk is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Artificial Intelligence. According to data from OpenAlex, Roman Borisyuk has authored 87 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Cognitive Neuroscience, 40 papers in Cellular and Molecular Neuroscience and 20 papers in Artificial Intelligence. Recurrent topics in Roman Borisyuk's work include Neural dynamics and brain function (59 papers), Neural Networks and Applications (18 papers) and Nonlinear Dynamics and Pattern Formation (18 papers). Roman Borisyuk is often cited by papers focused on Neural dynamics and brain function (59 papers), Neural Networks and Applications (18 papers) and Nonlinear Dynamics and Pattern Formation (18 papers). Roman Borisyuk collaborates with scholars based in United Kingdom, Russia and United States. Roman Borisyuk's co-authors include Yakov Kazanovich, Galina Borisyuk, Frank C. Hoppensteadt, Alan Roberts, Stephen R. Soffe, M.J. Denham, Oleksandr Burylko, Ivanitskiĭ Gr, Wenchang Li and David Chik and has published in prestigious journals such as Journal of Neuroscience, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Roman Borisyuk

83 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Roman Borisyuk United Kingdom 22 865 454 303 280 193 87 1.3k
Gerold Baier Germany 26 1.0k 1.2× 342 0.8× 439 1.4× 558 2.0× 78 0.4× 103 1.9k
Jonathan Touboul France 22 852 1.0× 325 0.7× 307 1.0× 630 2.3× 120 0.6× 72 1.6k
Matthew H. Higgs United States 16 625 0.7× 718 1.6× 271 0.9× 411 1.5× 149 0.8× 30 1.3k
Jian‐Young Wu United States 21 1.6k 1.9× 1.2k 2.6× 537 1.8× 560 2.0× 63 0.3× 47 2.1k
Martin Stemmler Germany 22 1.4k 1.6× 868 1.9× 157 0.5× 425 1.5× 178 0.9× 41 2.0k
Kanaka Rajan United States 14 1.2k 1.4× 515 1.1× 90 0.3× 246 0.9× 354 1.8× 28 1.6k
Attila Szücs Hungary 21 605 0.7× 488 1.1× 128 0.4× 247 0.9× 55 0.3× 54 1.3k
Antônio C. Roque Brazil 19 493 0.6× 385 0.8× 92 0.3× 192 0.7× 323 1.7× 116 1.4k
Klaus M. Stiefel United States 14 490 0.6× 466 1.0× 97 0.3× 155 0.6× 67 0.3× 40 852
Robert C. Elson United States 20 715 0.8× 544 1.2× 361 1.2× 515 1.8× 61 0.3× 25 1.1k

Countries citing papers authored by Roman Borisyuk

Since Specialization
Citations

This map shows the geographic impact of Roman Borisyuk'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 Roman Borisyuk with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Roman Borisyuk more than expected).

Fields of papers citing papers by Roman Borisyuk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Roman Borisyuk. 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 Roman Borisyuk. The network helps show where Roman Borisyuk may publish in the future.

Co-authorship network of co-authors of Roman Borisyuk

This figure shows the co-authorship network connecting the top 25 collaborators of Roman Borisyuk. A scholar is included among the top collaborators of Roman Borisyuk 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 Roman Borisyuk. Roman Borisyuk 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.
Borisyuk, Roman, et al.. (2023). From phase advance to phase delay: Flexible coordination between neuronal rhythms by the duration of synaptic input. Physical Review Research. 5(3). 2 indexed citations
2.
Zhang, Hongyan, et al.. (2023). Mechanisms Underlying the Recruitment of Inhibitory Interneurons in Fictive Swimming in DevelopingXenopus laevisTadpoles. Journal of Neuroscience. 43(8). 1387–1404. 2 indexed citations
3.
Borisyuk, Roman, et al.. (2020). Tadpole VR: virtual reality visualization of a simulated tadpole spinal cord. Virtual Reality. 25(1). 1–17. 3 indexed citations
4.
Soffe, Stephen R., et al.. (2018). Bifurcations of Limit Cycles in a Reduced Model of the Xenopus Tadpole Central Pattern Generator. SHILAP Revista de lepidopterología. 8(1). 10–10. 7 indexed citations
5.
Masud, Mohammad Shahed, et al.. (2017). Advanced correlation grid: Analysis and visualisation of functional connectivity among multiple spike trains. Journal of Neuroscience Methods. 286. 78–101. 4 indexed citations
6.
Yousif, Nada, Michael Mace, Nicola Pavese, et al.. (2017). A Network Model of Local Field Potential Activity in Essential Tremor and the Impact of Deep Brain Stimulation. PLoS Computational Biology. 13(1). e1005326–e1005326. 20 indexed citations
7.
Davis, Oliver, et al.. (2017). Studying the role of axon fasciculation during development in a computational model of the Xenopus tadpole spinal cord. Scientific Reports. 7(1). 13551–13551. 13 indexed citations
8.
Kazanovich, Yakov & Roman Borisyuk. (2016). Reaction times in visual search can be explained by a simple model of neural synchronization. Neural Networks. 87. 1–7. 11 indexed citations
9.
Burylko, Oleksandr, Yakov Kazanovich, & Roman Borisyuk. (2012). Bifurcations in phase oscillator networks with a central element. Physica D Nonlinear Phenomena. 241(12). 1072–1089. 13 indexed citations
10.
Borisyuk, Roman, et al.. (2011). Modeling the Connectome of a Simple Spinal Cord. Frontiers in Neuroinformatics. 5. 20–20. 16 indexed citations
11.
Sernagor, Evelyne, et al.. (2010). iRaster: A novel information visualization tool to explore spatiotemporal patterns in multiple spike trains. Journal of Neuroscience Methods. 194(1). 158–171. 3 indexed citations
12.
Borisyuk, Roman & Yakov Kazanovich. (2006). Oscillations and waves in the models of interactive neural populations. Biosystems. 86(1-3). 53–62. 5 indexed citations
13.
Cangelosi, Angelo, Guido Bugmann, & Roman Borisyuk. (2005). Modeling language, cognition and action : proceedings of the ninth Neural Computation and Psychology Workshop, University of Plymouth, UK, 8-10 September 2004. Research Explorer (The University of Manchester). 8 indexed citations
14.
Borisyuk, Roman. (2002). Oscillatory activity in the neural networks of spiking elements. Biosystems. 67(1-3). 3–16. 22 indexed citations
15.
Borisyuk, Roman, et al.. (2002). Visualisation of synchronous firing in multi-dimensional spike trains. Biosystems. 67(1-3). 265–279. 10 indexed citations
16.
Kazanovich, Yakov & Roman Borisyuk. (2002). Object selection by an oscillatory neural network. Biosystems. 67(1-3). 103–111. 24 indexed citations
17.
Borisyuk, Roman, M.J. Denham, Susan L. Denham, & Frank C. Hoppensteadt. (1999). Computational Models of Predictive and Memory-Related Functions of the Hippocampus. Reviews in the Neurosciences. 10(3-4). 213–32. 11 indexed citations
18.
Borisyuk, Roman & Frank C. Hoppensteadt. (1999). Oscillatory models of the hippocampus: A study of spatio-temporal patterns of neural activity. Biological Cybernetics. 81(4). 359–371. 21 indexed citations
19.
Cymbalyuk, Gennady, Roman Borisyuk, Uwe Müller-Wilm, & Holk Cruse. (1998). Oscillatory network controlling six-legged locomotion. Neural Networks. 11(7-8). 1449–1460. 8 indexed citations
20.
Cymbalyuk, Gennady, Evgeni V. Nikolaev, & Roman Borisyuk. (1994). In-phase and antiphase self-oscillations in a model of two electrically coupled pacemakers. Biological Cybernetics. 71(2). 153–160. 27 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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