Stephanie E. Palmer

1.6k total citations
36 papers, 773 citations indexed

About

Stephanie E. Palmer is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Molecular Biology. According to data from OpenAlex, Stephanie E. Palmer has authored 36 papers receiving a total of 773 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Cognitive Neuroscience, 14 papers in Cellular and Molecular Neuroscience and 7 papers in Molecular Biology. Recurrent topics in Stephanie E. Palmer's work include Neural dynamics and brain function (18 papers), Visual perception and processing mechanisms (10 papers) and Neurobiology and Insect Physiology Research (6 papers). Stephanie E. Palmer is often cited by papers focused on Neural dynamics and brain function (18 papers), Visual perception and processing mechanisms (10 papers) and Neurobiology and Insect Physiology Research (6 papers). Stephanie E. Palmer collaborates with scholars based in United States, France and United Kingdom. Stephanie E. Palmer's co-authors include William Bialek, Olivier Marre, Michael J. Berry, Leslie C. Osborne, Stephen G. Lisberger, Thierry Mora, Gašper Tkačik, Dario Amodei, David J. Freedman and Marcus R. Kronforst and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of Neuroscience.

In The Last Decade

Stephanie E. Palmer

33 papers receiving 754 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Stephanie E. Palmer United States 14 471 197 140 117 107 36 773
Johnatan Aljadeff United States 15 351 0.7× 239 1.2× 67 0.5× 72 0.6× 89 0.8× 21 617
Cyrus P. Billimoria United States 10 327 0.7× 376 1.9× 94 0.7× 36 0.3× 83 0.8× 13 609
Christopher L. Buckley United Kingdom 17 537 1.1× 71 0.4× 107 0.8× 150 1.3× 72 0.7× 55 903
Joseph Ayers United States 21 292 0.6× 394 2.0× 97 0.7× 65 0.6× 68 0.6× 48 1.2k
John P. Miller United States 13 465 1.0× 607 3.1× 71 0.5× 71 0.6× 100 0.9× 29 913
Cengiz Pehlevan United States 13 382 0.8× 289 1.5× 38 0.3× 139 1.2× 53 0.5× 48 741
Scott W. Linderman United States 17 451 1.0× 344 1.7× 132 0.9× 159 1.4× 40 0.4× 42 972
Eviatar Yemini United States 14 208 0.4× 299 1.5× 271 1.9× 49 0.4× 43 0.4× 22 1.2k
Udo Ernst Germany 17 882 1.9× 311 1.6× 60 0.4× 71 0.6× 319 3.0× 48 1.3k
Susanne Schreiber Germany 19 902 1.9× 669 3.4× 252 1.8× 70 0.6× 273 2.6× 53 1.3k

Countries citing papers authored by Stephanie E. Palmer

Since Specialization
Citations

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

Fields of papers citing papers by Stephanie E. Palmer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stephanie E. Palmer. 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 Stephanie E. Palmer. The network helps show where Stephanie E. Palmer may publish in the future.

Co-authorship network of co-authors of Stephanie E. Palmer

This figure shows the co-authorship network connecting the top 25 collaborators of Stephanie E. Palmer. A scholar is included among the top collaborators of Stephanie E. Palmer 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 Stephanie E. Palmer. Stephanie E. Palmer 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.
VanKuren, Nicholas W., et al.. (2025). Sex-limited diversification of the eye in Heliconius cydno butterflies. Journal of Comparative Physiology A.
2.
Lynn, Christopher W., et al.. (2025). Exact minimax entropy models of large-scale neuronal activity. Physical review. E. 111(5). 54411–54411. 3 indexed citations
3.
Wildenberg, Gregg, Griffin Badalamente, P. B. Littlewood, et al.. (2024). Synchrotron‐source micro‐x‐ray computed tomography for examining butterfly eyes. Ecology and Evolution. 14(4). e11137–e11137. 2 indexed citations
4.
Dotson, Nicholas M., et al.. (2023). The double-drift illusion biases the marmoset oculomotor system. Journal of Vision. 23(10). 4–4. 2 indexed citations
5.
Hanlon, Roger T., et al.. (2023). Aposematic coloration of Pacific newts (Taricha) provides a qualitatively but not quantitatively honest signal to predators. Biological Journal of the Linnean Society. 139(1). 1–17. 1 indexed citations
6.
Palmer, Stephanie E., et al.. (2023). Predictive saccades and decision making in the beetle-predating saffron robber fly. Current Biology. 33(14). 2912–2924.e5. 8 indexed citations
7.
Palmer, Stephanie E., et al.. (2021). Gaussian Information Bottleneck and the Non-Perturbative Renormalization Group. arXiv (Cornell University). 9 indexed citations
8.
Wang, Siwei, Idan Segev, Alexander Borst, & Stephanie E. Palmer. (2021). Maximally efficient prediction in the early fly visual system may support evasive flight maneuvers. PLoS Computational Biology. 17(5). e1008965–e1008965. 13 indexed citations
9.
Mora, Thierry, et al.. (2021). Optimal prediction with resource constraints using the information bottleneck. PLoS Computational Biology. 17(3). e1008743–e1008743. 7 indexed citations
10.
Stern, Menachem, et al.. (2020). Supervised learning through physical changes in a mechanical system. Proceedings of the National Academy of Sciences. 117(26). 14843–14850. 48 indexed citations
11.
Palmer, Stephanie E., et al.. (2020). Nonlinear mixed selectivity supports reliable neural computation. PLoS Computational Biology. 16(2). e1007544–e1007544. 38 indexed citations
12.
Westerman, Erica L., Nicholas W. VanKuren, Darli Massardo, et al.. (2018). Aristaless Controls Butterfly Wing Color Variation Used in Mimicry and Mate Choice. Current Biology. 28(21). 3469–3474.e4. 60 indexed citations
13.
Liu, Bing, et al.. (2018). State dependence of stimulus-induced variability tuning in macaque MT. PLoS Computational Biology. 14(10). e1006527–e1006527. 6 indexed citations
14.
Zhang, Wei, et al.. (2017). Tracing the origin and evolution of supergene mimicry in butterflies. Nature Communications. 8(1). 1269–1269. 36 indexed citations
15.
Palmer, Stephanie E., et al.. (2016). Optimal Prediction in the Retina and Natural Motion Statistics. Journal of Statistical Physics. 162(5). 1309–1323. 22 indexed citations
16.
Tkačik, Gašper, Thierry Mora, Olivier Marre, et al.. (2015). Thermodynamics and signatures of criticality in a network of neurons. Proceedings of the National Academy of Sciences. 112(37). 11508–11513. 134 indexed citations
17.
Prentice, Jason, Kristina D. Simmons, Gašper Tkačik, et al.. (2014). Transformation of stimulus correlations by the retina. Bulletin of the American Physical Society. 2014. 1 indexed citations
18.
Osborne, Leslie C., Stephanie E. Palmer, Stephen G. Lisberger, & William Bialek. (2008). The Neural Basis for Combinatorial Coding in a Cortical Population Response. Journal of Neuroscience. 28(50). 13522–13531. 116 indexed citations
19.
Palmer, Stephanie E. & Kenneth D. Miller. (2007). Effects of Inhibitory Gain and Conductance Fluctuations in a Simple Model for Contrast-Invariant Orientation Tuning in Cat V1. Journal of Neurophysiology. 98(1). 63–78. 14 indexed citations
20.
Alexander, Bryan, et al.. (1997). E-COMP: a few words about teaching writing with computers. Nottingham Trent University's Institutional Repository (Nottingham Trent Repository). 1 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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