Anna Levina

2.0k citations
42 papers · 1.1k · h-index 15

Impact in

Papers in

Anna Levina

37 papers receiving 1.1k citations

Peers

Anna Levina
Comparison fields: 5 of 98
  • Cognitive Neuroscience 717
  • Statistical and Nonlinear Physics 462
  • Cellular and Molecular Neuroscience 247
  • Condensed Matter Physics 100
  • Mathematical Physics 76
Replace Bruno Cessac with:
Bruno Cessac France
Juan G. Restrepo United States
Ruedi Stoop Switzerland
Thomas Petermann Switzerland
Antônio M. Batista Brazil
Ernest Barreto United States
Sonya Bahar United States
R. Stoop Switzerland
Paul So United States
Eckehard Olbrich Germany
Anna Levina relative to Bruno Cessac France Bruno Cessac's profile →
Citations per field
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Citations per year

Countries citing papers authored by Anna Levina

Since Specialization
Citations

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

Fields of papers citing papers by Anna Levina

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Anna Levina, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Anna Levina Line = papers co-authored together Anna Levina links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007383
2 2011147
3 2009104
4 201769
5 202155
6 201543
7 202342
8 202134
9 202223
10 202323
11 202220
12 201319
13 202217
14 200616
15 202014
16
Dynamical Synapses Give Rise to a Power-Law Distribution of Neuronal Avalanches
200512
17 202412
18 202312
19 202011
20 20229

About Anna Levina

Anna Levina is a scholar working on Cognitive Neuroscience, Statistical and Nonlinear Physics, Artificial Intelligence, Electrical and Electronic Engineering and Cellular and Molecular Neuroscience, having authored 42 papers that have together received 1.1k indexed citations. Recurring topics across this work include Neural dynamics and brain function (23 papers), Advanced Memory and Neural Computing (11 papers), stochastic dynamics and bifurcation (8 papers), Neural Networks and Applications (6 papers), Functional Brain Connectivity Studies (4 papers), Theoretical and Computational Physics (4 papers), Complex Network Analysis Techniques (4 papers) and Neuroscience and Neural Engineering (3 papers). The work is most often cited by research in Cognitive Neuroscience (717 citations), Statistical and Nonlinear Physics (462 citations), Cellular and Molecular Neuroscience (247 citations), Condensed Matter Physics (100 citations) and Mathematical Physics (76 citations). Anna Levina has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include J. Michael Herrmann, T. Geisel, Viola Priesemann, Jan Nagler, Marc Timme, Jürgen Jost, Tatiana A. Engel, Johannes Zierenberg, Menahem Segal and Elisha Moses. Their work appears in journals such as BMC Neuroscience, PLoS Computational Biology, Nature Communications, Stochastics and Dynamics and Physical review. E.

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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