Sophie Denève

6.1k total citations
58 papers, 3.6k citations indexed

About

Sophie Denève is a scholar working on Cognitive Neuroscience, Electrical and Electronic Engineering and Cellular and Molecular Neuroscience. According to data from OpenAlex, Sophie Denève has authored 58 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Cognitive Neuroscience, 17 papers in Electrical and Electronic Engineering and 16 papers in Cellular and Molecular Neuroscience. Recurrent topics in Sophie Denève's work include Neural dynamics and brain function (44 papers), Visual perception and processing mechanisms (21 papers) and Advanced Memory and Neural Computing (17 papers). Sophie Denève is often cited by papers focused on Neural dynamics and brain function (44 papers), Visual perception and processing mechanisms (21 papers) and Advanced Memory and Neural Computing (17 papers). Sophie Denève collaborates with scholars based in France, United States and Portugal. Sophie Denève's co-authors include Alexandre Pouget, Christian K. Machens, Jean‐René Duhamel, Peter E. Latham, Etienne Olivier, Timm Lochmann, Marie Avillac, Renaud Jardri, Kechen Zhang and Bernard Fraysse and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Neuron.

In The Last Decade

Sophie Denève

58 papers receiving 3.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sophie Denève France 29 3.1k 759 671 640 558 58 3.6k
Stephen V. David United States 32 4.9k 1.6× 1.2k 1.6× 316 0.5× 622 1.0× 348 0.6× 64 5.5k
David J. Freedman United States 35 4.9k 1.6× 742 1.0× 295 0.4× 549 0.9× 464 0.8× 65 6.0k
Jeffrey M. Beck United States 19 2.7k 0.9× 534 0.7× 231 0.3× 465 0.7× 431 0.8× 30 3.2k
Rufin VanRullen France 45 7.8k 2.5× 1.1k 1.5× 492 0.7× 1.1k 1.7× 375 0.7× 159 8.7k
József Fiser United States 26 3.5k 1.1× 518 0.7× 216 0.3× 734 1.1× 632 1.1× 76 4.8k
Christos Constantinidis United States 37 5.1k 1.6× 1.5k 2.0× 322 0.5× 518 0.8× 287 0.5× 107 6.0k
Carlos D. Brody United States 39 5.5k 1.7× 2.0k 2.7× 527 0.8× 397 0.6× 584 1.0× 73 6.2k
Denis Fize France 18 4.1k 1.3× 405 0.5× 295 0.4× 513 0.8× 234 0.4× 26 4.9k
Anne K. Churchland United States 30 3.7k 1.2× 1.1k 1.5× 219 0.3× 369 0.6× 283 0.5× 52 4.4k
André M. Bastos United States 19 5.0k 1.6× 1.4k 1.8× 239 0.4× 432 0.7× 219 0.4× 32 5.6k

Countries citing papers authored by Sophie Denève

Since Specialization
Citations

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

Fields of papers citing papers by Sophie Denève

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sophie Denève

This figure shows the co-authorship network connecting the top 25 collaborators of Sophie Denève. A scholar is included among the top collaborators of Sophie Denève 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 Sophie Denève. Sophie Denève 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.
Zeldenrust, Fleur, Boris Gutkin, & Sophie Denève. (2021). Efficient and robust coding in heterogeneous recurrent networks. PLoS Computational Biology. 17(4). e1008673–e1008673. 29 indexed citations
2.
Recanatesi, Stefano, et al.. (2021). Predictive learning as a network mechanism for extracting low-dimensional latent space representations. Nature Communications. 12(1). 1417–1417. 40 indexed citations
3.
Leptourgos, Pantelis, et al.. (2020). A functional theory of bistable perception based on dynamical circular inference. PLoS Computational Biology. 16(12). e1008480–e1008480. 11 indexed citations
5.
Zeldenrust, Fleur, et al.. (2017). Estimating the Information Extracted by a Single Spiking Neuron from a Continuous Input Time Series. Frontiers in Computational Neuroscience. 11. 49–49. 14 indexed citations
6.
Denève, Sophie, et al.. (2015). Enforcing balance allows local supervised learning in spiking recurrent networks. Neural Information Processing Systems. 28. 982–990. 14 indexed citations
7.
Savin, Cristina & Sophie Denève. (2014). Spatio-temporal Representations of Uncertainty in Spiking Neural Networks. Neural Information Processing Systems. 27. 2024–2032. 20 indexed citations
8.
Machens, Christian K., et al.. (2013). Predictive Coding of Dynamical Variables in Balanced Spiking Networks. PLoS Computational Biology. 9(11). e1003258–e1003258. 148 indexed citations
9.
Barrett, David G. T., Sophie Denève, & Christian K. Machens. (2013). Firing rate predictions in optimal balanced networks. Neural Information Processing Systems. 26. 1538–1546. 10 indexed citations
10.
Barrett, David G. T., et al.. (2012). Learning optimal spike-based representations. Neural Information Processing Systems. 25. 2285–2293. 29 indexed citations
11.
Morel, Pierre, et al.. (2011). Optimal and Suboptimal Use of Postsaccadic Vision in Sequences of Saccades. Journal of Neuroscience. 31(27). 10039–10049. 6 indexed citations
12.
Munuera, Jérôme, Pierre Morel, Jean‐René Duhamel, & Sophie Denève. (2009). Optimal Sensorimotor Control in Eye Movement Sequences. Journal of Neuroscience. 29(10). 3026–3035. 44 indexed citations
13.
Rouger, J., S. Lagleyre, Bernard Fraysse, et al.. (2007). Evidence that cochlear-implanted deaf patients are better multisensory integrators. Proceedings of the National Academy of Sciences. 104(17). 7295–7300. 219 indexed citations
14.
Denève, Sophie. (2007). Bayesian Spiking Neurons I: Inference. Neural Computation. 20(1). 91–117. 209 indexed citations
15.
Ernst, Udo, Sophie Denève, & Günter Meinhardt. (2007). Detection of gabor patch arrangements is explained by natural image statistics. BMC Neuroscience. 8(S2). 1 indexed citations
16.
Denève, Sophie & Alexandre Pouget. (2003). Basis Functions for Object-Centered Representations. Neuron. 37(2). 347–359. 62 indexed citations
17.
Denève, Sophie, Jean‐René Duhamel, & Alexandre Pouget. (2000). A New Model of Spatial Representation in Multimodal Brain Areas. Neural Information Processing Systems. 13. 117–123. 1 indexed citations
18.
Denève, Sophie, Alexandre Pouget, & Peter E. Latham. (1998). Divisive Normalization, Line Attractor Networks and Ideal Observers. Neural Information Processing Systems. 11. 104–110. 8 indexed citations
19.
Pouget, Alexandre, Kechen Zhang, Sophie Denève, & Peter E. Latham. (1998). Statistically Efficient Estimation Using Population Coding. Neural Computation. 10(2). 373–401. 169 indexed citations
20.
Denève, Sophie & Alexandre Pouget. (1997). Neural Basis of Object-Centered Representations. Neural Information Processing Systems. 24–30. 15 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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