Maya Geva‐Sagiv

17 total papers · 889 total citations
11 papers, 528 citations indexed

About

Maya Geva‐Sagiv is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, Maya Geva‐Sagiv has authored 11 papers receiving a total of 528 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Cognitive Neuroscience, 4 papers in Cellular and Molecular Neuroscience and 3 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in Maya Geva‐Sagiv's work include Memory and Neural Mechanisms (6 papers), Neuroscience and Neuropharmacology Research (4 papers) and Sleep and Wakefulness Research (3 papers). Maya Geva‐Sagiv is often cited by papers focused on Memory and Neural Mechanisms (6 papers), Neuroscience and Neuropharmacology Research (4 papers) and Sleep and Wakefulness Research (3 papers). Maya Geva‐Sagiv collaborates with scholars based in Israel and United States. Maya Geva‐Sagiv's co-authors include Nachum Ulanovsky, Liora Las, Yossi Yovel, Yuval Nir, Sandro Romani, Nachum Soroker, Aharon Weissbrod, Noam Sobel, Lavi Secundo and Michael M. Yartsev and has published in prestigious journals such as Cell, Nature Neuroscience and Nature reviews. Neuroscience.

In The Last Decade

Maya Geva‐Sagiv

11 papers receiving 513 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Maya Geva‐Sagiv 306 195 97 67 59 11 528
Martine J. Robards 169 0.6× 190 1.0× 43 0.4× 47 0.7× 154 2.6× 11 500
Michelle Symonds 329 1.1× 189 1.0× 101 1.0× 108 1.6× 130 2.2× 23 581
Alister U. Nicol 242 0.8× 167 0.9× 73 0.8× 36 0.5× 29 0.5× 32 563
Olesya T. Shevchouk 140 0.5× 162 0.8× 74 0.8× 58 0.9× 30 0.5× 19 526
Andreas Aschoff 287 0.9× 222 1.1× 56 0.6× 31 0.5× 292 4.9× 11 607
Thomas Fenzl 237 0.8× 144 0.7× 68 0.7× 52 0.8× 23 0.4× 40 543
SvenO.E. Ebbesson 134 0.4× 138 0.7× 51 0.5× 30 0.4× 60 1.0× 9 486
Satomi Ebara 173 0.6× 154 0.8× 39 0.4× 38 0.6× 38 0.6× 21 489
B. H. Pubols 260 0.8× 181 0.9× 35 0.4× 20 0.3× 45 0.8× 16 507
Jesper Ericsson 200 0.7× 253 1.3× 38 0.4× 24 0.4× 25 0.4× 9 500

Countries citing papers authored by Maya Geva‐Sagiv

Since Specialization
Citations

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

Fields of papers citing papers by Maya Geva‐Sagiv

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Maya Geva‐Sagiv. 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 Maya Geva‐Sagiv. The network helps show where Maya Geva‐Sagiv may publish in the future.

Co-authorship network of co-authors of Maya Geva‐Sagiv

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

All Works

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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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