Sergey V. Stasenko
- Cognitive Neuroscience top 10%
- Cellular and Molecular Neuroscience top 10%
- Electrical and Electronic Engineering
- Statistical and Nonlinear Physics top 10%
- Neurology
- Co-authors
- Victor KazantsevAlexander DityatevSusanna GordleevaEvgeniya V. PankratovaAlexey SemyanovAlena KalyakulinaAlexander E. HramovAlexey Mikhaylov
- Topics
- Neural dynamics and brain function (23 papers)Neuroscience and Neuropharmacology Research (13 papers)stochastic dynamics and bifurcation (8 papers)
- Journals
- PLoS ONEScientific ReportsSensors
In The Last Decade
Sergey V. Stasenko
30 papers receiving 285 citations
Peers
Comparison fields: 5 of 45
- Cognitive Neuroscience 191
- Cellular and Molecular Neuroscience 165
- Electrical and Electronic Engineering 77
- Statistical and Nonlinear Physics 66
- Neurology 37
Countries citing papers authored by Sergey V. Stasenko
This map shows the geographic impact of Sergey V. Stasenko'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 Sergey V. Stasenko with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sergey V. Stasenko more than expected).
Fields of papers citing papers by Sergey V. Stasenko
This network shows the impact of papers produced by Sergey V. Stasenko. 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 Sergey V. Stasenko. The network helps show where Sergey V. Stasenko may publish in the future.
Co-authorship network of co-authors of Sergey V. Stasenko
This figure shows the co-authorship network connecting the top 25 collaborators of Sergey V. Stasenko. A scholar is included among the top collaborators of Sergey V. Stasenko 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 Sergey V. Stasenko. Sergey V. Stasenko is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 10 | |
| 7 | 6 | |
| 8 | 15 | |
| 9 | 1 | |
| 10 | 5 | |
| 11 | 13 | |
| 12 | 5 | |
| 13 | 6 | |
| 14 | 0 | |
| 15 | 4 | |
| 16 | 7 | |
| 17 | 17 | |
| 18 | Modeling of Neural Networks with Tetrapartite Synapses | 1 |
| 19 | 15 | |
| 20 | 22 |
About Sergey V. Stasenko
Sergey V. Stasenko is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Statistical and Nonlinear Physics, having authored 36 papers that have together received 287 indexed citations. Recurring topics across this work include Neural dynamics and brain function (23 papers), Neuroscience and Neuropharmacology Research (13 papers) and stochastic dynamics and bifurcation (8 papers). The work is most often cited by research in Cognitive Neuroscience (191 citations), Cellular and Molecular Neuroscience (165 citations) and Statistical and Nonlinear Physics (66 citations). Sergey V. Stasenko has collaborated with scholars based in Russia, Germany and France. Frequent co-authors include Victor Kazantsev, Alexander Dityatev, Susanna Gordleeva, Evgeniya V. Pankratova, Alexey Semyanov, Alena Kalyakulina, Alexander E. Hramov, Alexey Mikhaylov, Andreï Zinovyev and Alexander N. Gorban. Their work appears in journals such as PLoS ONE, Scientific Reports and Sensors.
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.