Igor Belykh

820 total citations
10 papers, 641 citations indexed

About

Igor Belykh is a scholar working on Statistical and Nonlinear Physics, Cognitive Neuroscience and Computer Networks and Communications. According to data from OpenAlex, Igor Belykh has authored 10 papers receiving a total of 641 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Statistical and Nonlinear Physics, 10 papers in Cognitive Neuroscience and 9 papers in Computer Networks and Communications. Recurrent topics in Igor Belykh's work include Neural dynamics and brain function (10 papers), stochastic dynamics and bifurcation (10 papers) and Nonlinear Dynamics and Pattern Formation (9 papers). Igor Belykh is often cited by papers focused on Neural dynamics and brain function (10 papers), stochastic dynamics and bifurcation (10 papers) and Nonlinear Dynamics and Pattern Formation (9 papers). Igor Belykh collaborates with scholars based in United States, Switzerland and Denmark. Igor Belykh's co-authors include Enno de Lange, Martin Hasler, Andrey Shilnikov, Kun Zhao, В. Н. Белых and Erik Mosekilde and has published in prestigious journals such as Physical Review Letters, Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences and Chaos An Interdisciplinary Journal of Nonlinear Science.

In The Last Decade

Igor Belykh

10 papers receiving 612 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Igor Belykh United States	9	481	460	458	81	55	10	641
Kensuke Arai Japan	11	270 0.6×	366 0.8×	311 0.7×	88 1.1×	51 0.9×	35	591
Xiaoming Liang China	13	371 0.8×	306 0.7×	218 0.5×	50 0.6×	32 0.6×	46	504
Thiago de Lima Prado Brazil	16	333 0.7×	248 0.5×	313 0.7×	71 0.9×	33 0.6×	50	521
Kunichika Tsumoto Japan	14	290 0.6×	201 0.4×	244 0.5×	104 1.3×	181 3.3×	30	582
Jun-nosuke Teramae Japan	15	459 1.0×	438 1.0×	558 1.2×	189 2.3×	67 1.2×	31	846
Shenquan Liu China	15	380 0.8×	266 0.6×	324 0.7×	91 1.1×	84 1.5×	75	647
Luis F. Lago-Fernández Spain	6	291 0.6×	228 0.5×	308 0.7×	50 0.6×	69 1.3×	20	591
Peter F. Rowat United States	11	252 0.5×	130 0.3×	331 0.7×	94 1.2×	30 0.5×	16	448
Yasuhiro Tsubo Japan	11	203 0.4×	130 0.3×	364 0.8×	176 2.2×	42 0.8×	19	477
Ernest Montbrió Spain	18	455 0.9×	719 1.6×	544 1.2×	100 1.2×	24 0.4×	24	884

Countries citing papers authored by Igor Belykh

Since Specialization

Citations

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

Fields of papers citing papers by Igor Belykh

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Igor Belykh

This figure shows the co-authorship network connecting the top 25 collaborators of Igor Belykh. A scholar is included among the top collaborators of Igor Belykh 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 Igor Belykh. Igor Belykh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

Belykh, Igor, et al.. (2017). When two wrongs make a right: synchronized neuronal bursting from combined electrical and inhibitory coupling. Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences. 375(2096). 20160282–20160282. 12 indexed citations

Belykh, Igor, et al.. (2015). Synergistic effect of repulsive inhibition in synchronization of excitatory networks. Physical Review E. 91(6). 62919–62919. 25 indexed citations

Belykh, Igor, et al.. (2014). When Transitions Between Bursting Modes Induce Neural Synchrony. International Journal of Bifurcation and Chaos. 24(8). 1440013–1440013. 8 indexed citations

Belykh, Igor, et al.. (2012). Spikes matter for phase-locked bursting in inhibitory neurons. Physical Review E. 85(3). 36214–36214. 38 indexed citations

Belykh, Igor, et al.. (2010). Fast reciprocal inhibition can synchronize bursting neurons. Physical Review E. 81(4). 45201–45201. 43 indexed citations

Belykh, Igor, et al.. (2010). Burst-duration mechanism of in-phase bursting in inhibitory networks. Regular and Chaotic Dynamics. 15(2-3). 146–158. 6 indexed citations

Belykh, Igor & Andrey Shilnikov. (2008). When Weak Inhibition Synchronizes Strongly Desynchronizing Networks of Bursting Neurons. Physical Review Letters. 101(7). 78102–78102. 83 indexed citations

Shilnikov, Andrey, et al.. (2008). Polyrhythmic synchronization in bursting networking motifs. Chaos An Interdisciplinary Journal of Nonlinear Science. 18(3). 37120–37120. 56 indexed citations

Belykh, Igor, Enno de Lange, & Martin Hasler. (2005). Synchronization of Bursting Neurons: What Matters in the Network Topology. Physical Review Letters. 94(18). 188101–188101. 348 indexed citations

10.

Белых, В. Н., Igor Belykh, & Erik Mosekilde. (2005). HYPERBOLIC PLYKIN ATTRACTOR CAN EXIST IN NEURON MODELS. International Journal of Bifurcation and Chaos. 15(11). 3567–3578. 22 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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