Leenoy Meshulam

552 citations
7 papers · 188 indexed · h-index 4
Topics
Neural dynamics and brain function (4 papers)Gene Regulatory Network Analysis (1 paper)stochastic dynamics and bifurcation (1 paper)
Partner nations
United StatesIsraelJapan

In The Last Decade

Leenoy Meshulam

6 papers receiving 184 citations

Peers

Leenoy Meshulam
Comparison fields: 5 of 52
  • Cognitive Neuroscience 133
  • Cellular and Molecular Neuroscience 79
  • Statistical and Nonlinear Physics 36
  • Molecular Biology 28
  • Artificial Intelligence 14
Replace В. Н. Ильин with:
В. Н. Ильин United States
David C. Sterratt United Kingdom
Ji-Wei He China
Stéphane Deny France
Arthur-Ervin Avrămiea Netherlands
Alexis Dubreuil France
Jonathan S. Caplan United States
Lilach Avitan Australia
Tilman Kispersky United States
Julia Berzhanskaya United States
Leenoy Meshulam relative to В. Н. Ильин United States В. Н. Ильин's profile →
Citations per field
00.5×
В. Н. Ильин · 1×
Citations per year

Countries citing papers authored by Leenoy Meshulam

Since Specialization
Citations

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

Fields of papers citing papers by Leenoy Meshulam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Leenoy Meshulam

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

All Works

7 of 7 papers shown
#WorkIndexed citations
1 24
2
The renormalization group and information bottleneck: a unified framework
0
3 63
4 84
5
Can simple interactions capture complex features of neural activity underlying behavior in a virtual reality environment
2
6
Interpreting collective neural activity underlying spatial navigation in virtual reality
2
7 13

About Leenoy Meshulam

Leenoy Meshulam is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Statistical and Nonlinear Physics, having authored 7 papers that have together received 188 indexed citations. Recurring topics across this work include Neural dynamics and brain function (4 papers), Gene Regulatory Network Analysis (1 paper) and stochastic dynamics and bifurcation (1 paper). The work is most often cited by research in Cognitive Neuroscience (133 citations), Cellular and Molecular Neuroscience (79 citations) and Statistical and Nonlinear Physics (36 citations). Leenoy Meshulam has collaborated with scholars based in United States, Israel and Japan. Frequent co-authors include William Bialek, Carlos D. Brody, Jeffrey L. Gauthier, David W. Tank, Tomoyuki Mano, Sam Reiter, Teresa L. Iglesias, Makoto Hiroi, Kazumichi Shimizu and Dan Frenkel. Their work appears in journals such as Nature, Physical Review Letters and Neuron.

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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