Elad Schneidman

6.4k total citations · 1 hit paper
51 papers, 3.8k citations indexed

About

Elad Schneidman is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Molecular Biology. According to data from OpenAlex, Elad Schneidman has authored 51 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Cognitive Neuroscience, 23 papers in Cellular and Molecular Neuroscience and 12 papers in Molecular Biology. Recurrent topics in Elad Schneidman's work include Neural dynamics and brain function (33 papers), Neural Networks and Applications (12 papers) and Neuroscience and Neural Engineering (10 papers). Elad Schneidman is often cited by papers focused on Neural dynamics and brain function (33 papers), Neural Networks and Applications (12 papers) and Neuroscience and Neural Engineering (10 papers). Elad Schneidman collaborates with scholars based in Israel, United States and Austria. Elad Schneidman's co-authors include Michael J. Berry, William Bialek, Ronen Segev, Idan Segev, Barry Freedman, Gašper Tkačik, Elad Ganmor, Jason Puchalla, Susanne Still and R. Adron Harris and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Physical Review Letters.

In The Last Decade

Elad Schneidman

49 papers receiving 3.7k citations

Hit Papers

Weak pairwise correlations imply strongly correlated netw... 2006 2026 2012 2019 2006 250 500 750 1000

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Elad Schneidman Israel 25 2.4k 1.3k 814 769 493 51 3.8k
Ronen Segev Israel 27 2.5k 1.0× 1.4k 1.1× 612 0.8× 989 1.3× 373 0.8× 72 3.8k
Rob R. de Ruyter van Steveninck United States 13 2.5k 1.0× 1.7k 1.3× 612 0.8× 694 0.9× 537 1.1× 20 3.8k
Fred Wolf Germany 37 2.2k 0.9× 1.6k 1.2× 675 0.8× 668 0.9× 172 0.3× 138 3.9k
Andreas V. M. Herz Germany 35 2.4k 1.0× 1.7k 1.3× 722 0.9× 417 0.5× 389 0.8× 89 4.0k
Jean‐Marc Fellous United States 35 3.5k 1.4× 2.3k 1.8× 601 0.7× 338 0.4× 477 1.0× 90 6.6k
Adrienne L. Fairhall United States 30 2.4k 1.0× 1.7k 1.3× 709 0.9× 348 0.5× 380 0.8× 64 3.8k
Paul Tiesinga United States 31 3.5k 1.4× 2.2k 1.7× 664 0.8× 503 0.7× 159 0.3× 118 4.5k
Jonathan W. Pillow United States 34 4.7k 1.9× 2.0k 1.5× 500 0.6× 564 0.7× 658 1.3× 111 5.6k
Carlos D. Brody United States 39 5.5k 2.2× 2.0k 1.6× 313 0.4× 395 0.5× 584 1.2× 73 6.2k
L. F. Abbott United States 18 3.2k 1.3× 2.0k 1.5× 803 1.0× 412 0.5× 570 1.2× 31 4.1k

Countries citing papers authored by Elad Schneidman

Since Specialization
Citations

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

Fields of papers citing papers by Elad Schneidman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Elad Schneidman

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

All Works

20 of 20 papers shown
1.
Haque, Rizwanul, Ramiro Lorenzo, Gil Stelzer, et al.. (2025). Decoding sexual dimorphism of the sex-shared nervous system at single-neuron resolution. Science Advances. 11(28). eadv9106–eadv9106. 3 indexed citations
4.
Salzberg, Yehuda, Renee M. Miller, Douglas Portman, et al.. (2022). Reprogramming the topology of the nociceptive circuit in C. elegans reshapes sexual behavior. Current Biology. 32(20). 4372–4385.e7. 18 indexed citations
5.
Tkačik, Gašper, et al.. (2020). Learning probabilistic neural representations with randomly connected circuits. Proceedings of the National Academy of Sciences. 117(40). 25066–25073. 19 indexed citations
6.
Schneidman, Elad, et al.. (2020). Social interactions drive efficient foraging and income equality in groups of fish. eLife. 9. 25 indexed citations
7.
Ganmor, Elad, Ronen Segev, & Elad Schneidman. (2015). A thesaurus for a neural population code. eLife. 4. 33 indexed citations
8.
Tkačik, Gašper, Anandamohan Ghosh, Elad Schneidman, & Ronen Segev. (2014). Adaptation to Changes in Higher-Order Stimulus Statistics in the Salamander Retina. PLoS ONE. 9(1). e85841–e85841. 10 indexed citations
9.
Tkačik, Gašper, Olivier Marre, Dario Amodei, et al.. (2014). Searching for Collective Behavior in a Large Network of Sensory Neurons. PLoS Computational Biology. 10(1). e1003408–e1003408. 150 indexed citations
10.
Tkačik, Gašper, et al.. (2013). Stimulus-dependent Maximum Entropy Models of Neural Population Codes. PLoS Computational Biology. 9(3). e1002922–e1002922. 64 indexed citations
11.
Vasserman, Genadiy, Elad Schneidman, & Ronen Segev. (2013). Adaptive Colour Contrast Coding in the Salamander Retina Efficiently Matches Natural Scene Statistics. PLoS ONE. 8(10). e79163–e79163. 5 indexed citations
12.
Deutsch, David, Maciej Pietr, Per Magne Knutsen, Ehud Ahissar, & Elad Schneidman. (2012). Fast Feedback in Active Sensing: Touch-Induced Changes to Whisker-Object Interaction. PLoS ONE. 7(9). e44272–e44272. 52 indexed citations
13.
Weiss, Tali, et al.. (2012). Perceptual convergence of multi-component mixtures in olfaction implies an olfactory white. Proceedings of the National Academy of Sciences. 109(49). 19959–19964. 91 indexed citations
14.
Schneidman, Elad, Jason Puchalla, Ronen Segev, et al.. (2011). Synergy from Silence in a Combinatorial Neural Code. Journal of Neuroscience. 31(44). 15732–15741. 50 indexed citations
15.
Lapid, Hadas, Han‐Seok Seo, Benno Schuster, et al.. (2009). Odorant Concentration Dependence in Electroolfactograms Recorded From the Human Olfactory Epithelium. Journal of Neurophysiology. 102(4). 2121–2130. 15 indexed citations
16.
Schneidman, Elad, Michael J. Berry, Ronen Segev, & William Bialek. (2006). Weak pairwise correlations imply strongly correlated network states in a neural population. Nature. 440(7087). 1007–1012. 1100 indexed citations breakdown →
17.
Puchalla, Jason, Elad Schneidman, R. Adron Harris, & Michael J. Berry. (2005). Redundancy in the Population Code of the Retina. Neuron. 46(3). 493–504. 164 indexed citations
18.
Schneidman, Elad, Susanne Still, Michael J. Berry, & William Bialek. (2003). Network Information and Connected Correlations. Physical Review Letters. 91(23). 238701–238701. 191 indexed citations
19.
Schneidman, Elad, et al.. (2000). Universality and individuality in a neural code. ArXiv.org. 13. 159–165. 13 indexed citations
20.
Schneidman, Elad, Idan Segev, & Naftali Tishby. (1999). Information Capacity and Robustness of Stochastic Neuron Models. Neural Information Processing Systems. 12. 178–184. 22 indexed citations

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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