Angelo Arleo

3.3k total citations · 1 hit paper
81 papers, 1.8k citations indexed

About

Angelo Arleo is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Automotive Engineering. According to data from OpenAlex, Angelo Arleo has authored 81 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Cognitive Neuroscience, 20 papers in Cellular and Molecular Neuroscience and 14 papers in Automotive Engineering. Recurrent topics in Angelo Arleo's work include Memory and Neural Mechanisms (27 papers), Neural dynamics and brain function (23 papers) and Visual perception and processing mechanisms (17 papers). Angelo Arleo is often cited by papers focused on Memory and Neural Mechanisms (27 papers), Neural dynamics and brain function (23 papers) and Visual perception and processing mechanisms (17 papers). Angelo Arleo collaborates with scholars based in France, Switzerland and United States. Angelo Arleo's co-authors include Wulfram Gerstner, Denis Sheynikhovich, José‐Alain Sahel, Alexandre Delaux, Sidney I. Wiener, Alain Berthoz, Fabrizio Smeraldi, Élise Boulanger-Scemama, Isabelle Audo and Simona Degli Esposti and has published in prestigious journals such as Nature Medicine, Journal of Neuroscience and SHILAP Revista de lepidopterología.

In The Last Decade

Angelo Arleo

79 papers receiving 1.8k citations

Hit Papers

Partial recovery of visual function in a blind patient af... 2021 2026 2022 2024 2021 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Angelo Arleo France 21 1.0k 787 314 165 158 81 1.8k
David C. Bradley United States 20 3.0k 3.0× 663 0.8× 439 1.4× 59 0.4× 246 1.6× 32 3.6k
Ralph M. Siegel United States 17 2.4k 2.4× 372 0.5× 260 0.8× 60 0.4× 215 1.4× 40 2.7k
Ehud Zohary Israel 33 4.9k 4.8× 988 1.3× 219 0.7× 56 0.3× 224 1.4× 62 5.4k
Manfred Fahle Germany 39 5.4k 5.3× 612 0.8× 385 1.2× 76 0.5× 173 1.1× 191 6.1k
Gregory D. Horwitz United States 24 1.4k 1.4× 694 0.9× 317 1.0× 31 0.2× 85 0.5× 49 1.9k
Mark E. McCourt United States 30 3.2k 3.2× 224 0.3× 138 0.4× 263 1.6× 88 0.6× 99 3.8k
Bart Krekelberg United States 30 3.2k 3.1× 648 0.8× 282 0.9× 30 0.2× 518 3.3× 94 3.6k
Suliann Ben Hamed France 31 2.9k 2.8× 306 0.4× 173 0.6× 46 0.3× 378 2.4× 81 3.4k
Dwight J. Kravitz United States 28 3.5k 3.4× 291 0.4× 137 0.4× 108 0.7× 101 0.6× 58 4.0k
Anthony M. Norcia United States 47 5.9k 5.9× 841 1.1× 689 2.2× 66 0.4× 216 1.4× 208 7.2k

Countries citing papers authored by Angelo Arleo

Since Specialization
Citations

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

Fields of papers citing papers by Angelo Arleo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Angelo Arleo

This figure shows the co-authorship network connecting the top 25 collaborators of Angelo Arleo. A scholar is included among the top collaborators of Angelo Arleo 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 Angelo Arleo. Angelo Arleo 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.
Authié, Colas, et al.. (2024). Wide-angle simulated artificial vision enhances spatial navigation and object interaction in a naturalistic environment. Journal of Neural Engineering. 21(6). 66005–66005. 1 indexed citations
2.
Sahel, José‐Alain, et al.. (2023). The vertical position of visual information conditions spatial memory performance in healthy aging. Communications Psychology. 1(1). 2–2. 1 indexed citations
3.
Ramanoël, Stephen, et al.. (2022). Future trends in brain aging research: Visuo-cognitive functions at stake during mobility and spatial navigation. SHILAP Revista de lepidopterología. 2. 100034–100034. 7 indexed citations
4.
Luque, Niceto R., et al.. (2022). Electrical coupling regulated by GABAergic nucleo-olivary afferent fibres facilitates cerebellar sensory–motor adaptation. Neural Networks. 155. 422–438. 2 indexed citations
5.
Delaux, Alexandre, Stephen Ramanoël, Lukas Gehrke, et al.. (2021). Mobile brain/body imaging of landmark‐based navigation with high‐density EEG. European Journal of Neuroscience. 54(12). 8256–8282. 31 indexed citations
6.
Rossi, Ethan A., Chiara M. Eandi, Kate Grieve, et al.. (2020). A new method for visualizing drusen and their progression in adaptive optics ophthalmoscopy. Investigative Ophthalmology & Visual Science. 61(7). 203–203. 1 indexed citations
7.
Luque, Niceto R., Francisco Naveros, Richard R. Carrillo, Eduardo Ros, & Angelo Arleo. (2019). Spike burst-pause dynamics of Purkinje cells regulate sensorimotor adaptation. PLoS Computational Biology. 15(3). e1006298–e1006298. 15 indexed citations
9.
Arleo, Angelo, et al.. (2018). Internal noise sources limiting contrast sensitivity. Scientific Reports. 8(1). 2596–2596. 10 indexed citations
10.
Masquelier, Timothée, et al.. (2018). Convis: A Toolbox to Fit and Simulate Filter-Based Models of Early Visual Processing. Frontiers in Neuroinformatics. 12. 9–9. 4 indexed citations
11.
Naël, Virginie, Karine Pérès, Isabelle Carrière, et al.. (2017). Visual Impairment, Undercorrected Refractive Errors, and Activity Limitations in Older Adults: Findings From the Three-City Alienor Study. Investigative Ophthalmology & Visual Science. 58(4). 2359–2359. 18 indexed citations
12.
Allard, Rémy & Angelo Arleo. (2017). Reducing luminance intensity can improve motion perception in noise. Scientific Reports. 7(1). 43140–43140. 3 indexed citations
13.
Etienne, C, Angelo Arleo, & Rémy Allard. (2016). Maximizing noise energy for noise-masking studies. Behavior Research Methods. 49(4). 1278–1290. 7 indexed citations
14.
Bengtsson, Fredrik, Romain Brasselet, Roland S. Johansson, Angelo Arleo, & Henrik Jörntell. (2013). Integration of Sensory Quanta in Cuneate Nucleus Neurons In Vivo. PLoS ONE. 8(2). e56630–e56630. 49 indexed citations
15.
Sheynikhovich, Denis, Satoru Otani, & Angelo Arleo. (2011). The role of tonic and phasic dopamine for long-term synaptic plasticity in the prefrontal cortex: A computational model. Journal of Physiology-Paris. 105(1-3). 45–52. 12 indexed citations
16.
Sheynikhovich, Denis, et al.. (2009). Is there a geometric module for spatial orientation? Insights from a rodent navigation model.. Psychological Review. 116(3). 540–566. 88 indexed citations
17.
Brasselet, Romain, Roland S. Johansson, & Angelo Arleo. (2009). Optimal context separation of spiking haptic signals by second-order somatosensory neurons. Neural Information Processing Systems. 22. 180–188. 7 indexed citations
18.
Burguière, Eric, Angelo Arleo, Mohammad Reza Hojjati, et al.. (2005). Spatial navigation impairment in mice lacking cerebellar LTD: a motor adaptation deficit?. Nature Neuroscience. 8(10). 1292–1294. 69 indexed citations
19.
Arleo, Angelo, Fabrizio Smeraldi, & Wulfram Gerstner. (2004). Cognitive Navigation Based on Nonuniform Gabor Space Sampling, Unsupervised Growing Networks, and Reinforcement Learning. IEEE Transactions on Neural Networks. 15(3). 639–652. 59 indexed citations
20.
Arleo, Angelo, et al.. (2000). Place Cells and Spatial Navigation Based on 2D Visual Feature Extraction, Path Integration, and Reinforcement Learning. Neural Information Processing Systems. 13. 89–95. 8 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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