Olivier Marre

4.0k total citations
55 papers, 2.0k citations indexed

About

Olivier Marre is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Molecular Biology. According to data from OpenAlex, Olivier Marre has authored 55 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Cognitive Neuroscience, 34 papers in Cellular and Molecular Neuroscience and 22 papers in Molecular Biology. Recurrent topics in Olivier Marre's work include Neural dynamics and brain function (38 papers), Photoreceptor and optogenetics research (20 papers) and Retinal Development and Disorders (19 papers). Olivier Marre is often cited by papers focused on Neural dynamics and brain function (38 papers), Photoreceptor and optogenetics research (20 papers) and Retinal Development and Disorders (19 papers). Olivier Marre collaborates with scholars based in France, United States and Austria. Olivier Marre's co-authors include Gašper Tkačik, Michael J. Berry, William Bialek, Serge Picaud, Dario Amodei, Pierre Yger, Thierry Mora, Stephanie E. Palmer, Jens Duebel and Yves Frégnac and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and Nature Communications.

In The Last Decade

Olivier Marre

51 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Olivier Marre France 24 1.2k 1.0k 685 314 233 55 2.0k
Tim Gollisch Germany 23 1.6k 1.3× 1.2k 1.2× 859 1.3× 528 1.7× 185 0.8× 53 2.4k
David K. Warland United States 16 1.8k 1.5× 1.3k 1.3× 599 0.9× 358 1.1× 282 1.2× 21 2.5k
Keith P. Purpura United States 24 2.5k 2.1× 1.1k 1.1× 499 0.7× 286 0.9× 252 1.1× 49 3.0k
Pamela Reinagel United States 19 2.0k 1.6× 1.1k 1.1× 603 0.9× 279 0.9× 247 1.1× 31 2.6k
Jeffrey L. Gauthier United States 21 1.8k 1.4× 1.3k 1.3× 770 1.1× 196 0.6× 175 0.8× 26 2.6k
Sheila Nirenberg United States 21 1.4k 1.1× 1.3k 1.3× 840 1.2× 276 0.9× 297 1.3× 33 2.1k
Almut Schüz Germany 18 1.8k 1.5× 1.1k 1.1× 270 0.4× 333 1.1× 154 0.7× 42 2.6k
Michael London Israel 21 1.9k 1.5× 1.9k 1.9× 592 0.9× 530 1.7× 251 1.1× 35 3.2k
Tatyana O. Sharpee United States 26 1.8k 1.5× 703 0.7× 285 0.4× 175 0.6× 172 0.7× 70 2.4k
Simon R. Schultz United Kingdom 25 1.6k 1.3× 1.2k 1.2× 254 0.4× 318 1.0× 229 1.0× 86 2.1k

Countries citing papers authored by Olivier Marre

Since Specialization
Citations

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

Fields of papers citing papers by Olivier Marre

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Olivier Marre

This figure shows the co-authorship network connecting the top 25 collaborators of Olivier Marre. A scholar is included among the top collaborators of Olivier Marre 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 Olivier Marre. Olivier Marre 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.
Zhao, Zhijian, et al.. (2024). Nitric oxide modulates contrast suppression in a subset of mouse retinal ganglion cells. eLife. 13. 3 indexed citations
2.
Yger, Pierre, et al.. (2023). Differences in nonlinearities determine retinal cell types. Journal of Neurophysiology. 130(3). 706–718. 3 indexed citations
3.
Demené, Charlie, Diep Nguyen, Julie Dégardin, et al.. (2023). Ectopic expression of a mechanosensitive channel confers spatiotemporal resolution to ultrasound stimulations of neurons for visual restoration. Nature Nanotechnology. 18(6). 667–676. 49 indexed citations
4.
Callebert, Jacques, Robert M. Duvoisin, Christelle Michiels, et al.. (2022). Mice Lacking Gpr179 with Complete Congenital Stationary Night Blindness Are a Good Model for Myopia. International Journal of Molecular Sciences. 24(1). 219–219. 7 indexed citations
5.
Deny, Stéphane, et al.. (2021). Predicting synchronous firing of large neural populations from sequential recordings. PLoS Computational Biology. 17(1). e1008501–e1008501. 2 indexed citations
6.
Ferrari, Ulisse, Stéphane Deny, Abhishek Sengupta, et al.. (2020). Towards optogenetic vision restoration with high resolution. PLoS Computational Biology. 16(7). e1007857–e1007857. 25 indexed citations
7.
Gardella, Christophe, Olivier Marre, & Thierry Mora. (2018). Blindfold learning of an accurate neural metric. Proceedings of the National Academy of Sciences. 115(13). 3267–3272. 6 indexed citations
8.
Chalk, Matthew, Olivier Marre, & Gašper Tkačik. (2017). Toward a unified theory of efficient, predictive, and sparse coding. Proceedings of the National Academy of Sciences. 115(1). 186–191. 86 indexed citations
9.
Deny, Stéphane, Ulisse Ferrari, Émilie Macé, et al.. (2017). Multiplexed computations in retinal ganglion cells of a single type. Nature Communications. 8(1). 1964–1964. 27 indexed citations
10.
Gardella, Christophe, Olivier Marre, & Thierry Mora. (2017). Restricted Boltzmann Machines provide an accurate metric for retinal responses to visual stimuli. International Conference on Learning Representations. 1 indexed citations
11.
Prentice, Jason, et al.. (2016). Error-Robust Modes of the Retinal Population Code. PLoS Computational Biology. 12(11). e1005148–e1005148. 15 indexed citations
12.
Caplette, Romain, Élisabeth Dubus, Grégory Gauvain, et al.. (2016). Optogenetic visual restoration using ChrimsonR: Validation in degenerative rodent models, rd1 and P23H.. Investigative Ophthalmology & Visual Science. 57(12). 600–600. 2 indexed citations
13.
Marre, Olivier, et al.. (2015). High Accuracy Decoding of Dynamical Motion from a Large Retinal Population. PLoS Computational Biology. 11(7). e1004304–e1004304. 39 indexed citations
14.
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
15.
Fournier, Julien, Cyril Monier, Manuel Levy, et al.. (2014). Hidden Complexity of Synaptic Receptive Fields in Cat V1. Journal of Neuroscience. 34(16). 5515–5528. 28 indexed citations
16.
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
17.
Marre, Olivier, et al.. (2012). Mapping a Complete Neural Population in the Retina. Journal of Neuroscience. 32(43). 14859–14873. 114 indexed citations
18.
Lorach, Henri, Ryad Benosman, Olivier Marre, et al.. (2012). Artificial retina: the multichannel processing of the mammalian retina achieved with a neuromorphic asynchronous light acquisition device. Journal of Neural Engineering. 9(6). 66004–66004. 35 indexed citations
19.
Lorach, Henri, Olivier Marre, José‐Alain Sahel, Ryad Benosman, & Serge Picaud. (2012). Neural stimulation for visual rehabilitation: Advances and challenges. Journal of Physiology-Paris. 107(5). 421–431. 23 indexed citations
20.
Rajan, Kanaka, et al.. (2012). Learning quadratic receptive fields from neural responses to natural stimuli. arXiv (Cornell University). 21 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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