Ivan Raikov

545 citations
22 papers · 300 · h-index 6

Impact in

    • Neural dynamics and brain function
    • Memory and Neural Mechanisms
    • Functional Brain Connectivity Studies
    • Neuroscience and Neuropharmacology Research
    • Neuroscience and Neural Engineering
    • Photoreceptor and optogenetics research

Papers in

Ivan Raikov

17 papers receiving 298 citations

Peers

Ivan Raikov
Comparison fields: 5 of 47
  • Cognitive Neuroscience 218
  • Cellular and Molecular Neuroscience 173
  • Neurology 40
  • Biophysics 20
  • Sensory Systems 11
Replace Rie Kimura with:
Rie Kimura Japan
Susanne Reichinnek Germany
Sonia Bolea United States
Ingrid van Welie Netherlands
Alexander O. Komendantov United States
Tamás Tompa Hungary
Enrique H.S. Toloza United States
Sadra Sadeh United Kingdom
Zhenrui Liao United States
Steffen Kandler Germany
Ivan Raikov relative to Rie Kimura Japan Rie Kimura's profile →
Citations per field
00.5×1.6×
Rie Kimura · 1×
Citations per year

Countries citing papers authored by Ivan Raikov

Since Specialization
Citations

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

Fields of papers citing papers by Ivan Raikov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ivan Raikov, 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 Ivan Raikov Line = papers co-authored together Ivan Raikov links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016125
2 202138
3 201732
4 200332
5 201124
6 202323
7 20245
8 20125
9 20224
10 20213
11 20213
12 20231
13 20141
14 20111
15 20151
16 20051
17 20161
18 20250
19 20090
20 20120

About Ivan Raikov

Ivan Raikov is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience, Electrical and Electronic Engineering, Molecular Biology and General Health Professions, having authored 22 papers that have together received 300 indexed citations. Recurring topics across this work include Neural dynamics and brain function (9 papers), Neuroscience and Neuropharmacology Research (6 papers), Advanced Memory and Neural Computing (4 papers), Memory and Neural Mechanisms (4 papers), Functional Brain Connectivity Studies (3 papers), Homelessness and Social Issues (2 papers), Neuroscience and Neural Engineering (2 papers) and Zebrafish Biomedical Research Applications (2 papers). The work is most often cited by research in Cognitive Neuroscience (218 citations), Cellular and Molecular Neuroscience (173 citations), Neurology (40 citations), Biophysics (20 citations) and Sensory Systems (11 citations). Ivan Raikov has collaborated with scholars based in United States, Belgium and Japan. Frequent co-authors include Marianne Bezaire, Ivan Soltesz, Kelly Burk, Robert J. Butera, Iván Soltész, Erik De Schutter, Zhenrui Liao, Attila Losonczy, Darian Hadjiabadi and Matthew Lovett-Barron. Their work appears in journals such as BMC Neuroscience, PLoS Computational Biology, Neuron, iScience and Frontiers in Neurorobotics.

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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