Camilo Libedinsky

1.4k total citations
40 papers, 698 citations indexed

About

Camilo Libedinsky is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Electrical and Electronic Engineering. According to data from OpenAlex, Camilo Libedinsky has authored 40 papers receiving a total of 698 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Cognitive Neuroscience, 22 papers in Cellular and Molecular Neuroscience and 8 papers in Electrical and Electronic Engineering. Recurrent topics in Camilo Libedinsky's work include Neural dynamics and brain function (19 papers), EEG and Brain-Computer Interfaces (19 papers) and Neuroscience and Neural Engineering (18 papers). Camilo Libedinsky is often cited by papers focused on Neural dynamics and brain function (19 papers), EEG and Brain-Computer Interfaces (19 papers) and Neuroscience and Neural Engineering (18 papers). Camilo Libedinsky collaborates with scholars based in Singapore, United States and United Kingdom. Camilo Libedinsky's co-authors include Michael W.L. Chee, Scott A. Huettel, Margaret S. Livingstone, Shih‐Cheng Yen, Roger Herikstad, Aishwarya Parthasarathy, Stijn A. A. Massar, Rosa Q. So, Hillary R. Rodman and Harvey J. Karten and has published in prestigious journals such as Nature Communications, Journal of Neuroscience and Nature Neuroscience.

In The Last Decade

Camilo Libedinsky

38 papers receiving 689 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Camilo Libedinsky Singapore 13 526 148 123 71 55 40 698
Ashwini K. Pandey United States 16 467 0.9× 201 1.4× 92 0.7× 30 0.4× 22 0.4× 33 800
Thomas E. Hazy United States 11 725 1.4× 140 0.9× 151 1.2× 18 0.3× 20 0.4× 12 889
Jan Willem de Gee Netherlands 11 870 1.7× 87 0.6× 129 1.0× 8 0.1× 61 1.1× 23 994
Mototaka Suzuki Germany 13 898 1.7× 265 1.8× 65 0.5× 50 0.7× 16 0.3× 23 1.0k
Xiaochuan Pan China 15 428 0.8× 176 1.2× 47 0.4× 56 0.8× 10 0.2× 37 573
Reka Daniel United States 8 582 1.1× 73 0.5× 142 1.2× 8 0.1× 64 1.2× 9 757
Yutaka Komura Japan 4 580 1.1× 129 0.9× 137 1.1× 15 0.2× 16 0.3× 5 697
Mark S. Gilzenrat United States 7 835 1.6× 89 0.6× 159 1.3× 6 0.1× 50 0.9× 7 957
Niels A Kloosterman Germany 12 757 1.4× 75 0.5× 99 0.8× 8 0.1× 28 0.5× 19 846
Sergio Ruíz Chile 17 1000 1.9× 114 0.8× 156 1.3× 28 0.4× 7 0.1× 37 1.2k

Countries citing papers authored by Camilo Libedinsky

Since Specialization
Citations

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

Fields of papers citing papers by Camilo Libedinsky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Camilo Libedinsky

This figure shows the co-authorship network connecting the top 25 collaborators of Camilo Libedinsky. A scholar is included among the top collaborators of Camilo Libedinsky 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 Camilo Libedinsky. Camilo Libedinsky 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.
Libedinsky, Camilo, et al.. (2024). Spike-Weighted Spiking Neural Network with Spiking Long Short-Term Memory: A Biomimetic Approach to Decoding Brain Signals. Algorithms. 17(4). 156–156. 1 indexed citations
2.
Herikstad, Roger, et al.. (2024). Working Memory Updating in the Macaque Lateral Prefrontal Cortex. Journal of Neuroscience. 45(37). e1770242024–e1770242024. 1 indexed citations
3.
Libedinsky, Camilo. (2023). Comparing representations and computations in single neurons versus neural networks. Trends in Cognitive Sciences. 27(6). 517–527. 3 indexed citations
4.
Herikstad, Roger, et al.. (2023). Distinct Lateral Prefrontal Regions Are Organized in an Anterior–Posterior Functional Gradient. Journal of Neuroscience. 43(38). 6564–6572. 4 indexed citations
5.
Lo, Yu Tung, et al.. (2022). Neural correlates of learning in a linear discriminant analysis brain-computer interface paradigm. Journal of Neural Engineering. 19(5). 56041–56041.
6.
Tan, Cheston, et al.. (2021). A nonlinear hidden layer enables actor–critic agents to learn multiple paired association navigation. Cerebral Cortex. 32(18). 3917–3936. 2 indexed citations
7.
Blasiak, Agata, Kian Ann Ng, Gil Gerald Lasam Gammad, et al.. (2021). STEER: 3D Printed Guide for Nerve Regrowth Control and Neural Interface in Non-Human Primate Model. IEEE Transactions on Biomedical Engineering. 69(3). 1085–1092. 3 indexed citations
8.
Libedinsky, Camilo, et al.. (2019). Graded Memory: A Cognitive Category to Replace Spatial Sustained Attention and Working Memory
.. Europe PMC (PubMed Central). 92(1). 121–125. 1 indexed citations
9.
Parthasarathy, Aishwarya, et al.. (2019). Time-invariant working memory representations in the presence of code-morphing in the lateral prefrontal cortex. Nature Communications. 10(1). 4995–4995. 40 indexed citations
10.
Wu, Shuang, Kah Junn Tan, James Stewart, et al.. (2019). Fully automated leg tracking of Drosophila neurodegeneration models reveals distinct conserved movement signatures. PLoS Biology. 17(6). e3000346–e3000346. 18 indexed citations
11.
Parthasarathy, Aishwarya, et al.. (2017). Mixed selectivity morphs population codes in prefrontal cortex. Nature Neuroscience. 20(12). 1770–1779. 126 indexed citations
12.
Tay, Nicole, Youran Tan, Keefe Chng, et al.. (2017). Effect of human milk formula with bovine colostrum supplementation on bone mineral density in infant cynomolgus macaques. Journal of Developmental Origins of Health and Disease. 9(2). 172–181. 1 indexed citations
13.
Massar, Stijn A. A., et al.. (2015). Separate and overlapping brain areas encode subjective value during delay and effort discounting. NeuroImage. 120. 104–113. 95 indexed citations
14.
Sheshadri, Swathi, Jukka Kortelainen, Jacopo Rigosa, et al.. (2015). Classification of phases of hand grasp task by the extraction of miniature compound nerve action potentials (mCNAPs). 154. 593–596. 2 indexed citations
15.
So, Rosa Q., Zhiming Xu, Camilo Libedinsky, et al.. (2015). Neural representations of movement intentions during brain-controlled self-motion. 119. 228–231. 6 indexed citations
16.
Lee, Ying, Mary F-F Chong, Jean CJ Liu, et al.. (2013). Dietary disinhibition modulates neural valuation of food in the fed and fasted states. American Journal of Clinical Nutrition. 97(5). 919–925. 12 indexed citations
17.
Libedinsky, Camilo & Margaret S. Livingstone. (2011). Role of Prefrontal Cortex in Conscious Visual Perception. Journal of Neuroscience. 31(1). 64–69. 57 indexed citations
18.
Libedinsky, Camilo, et al.. (2011). Sleep Deprivation Alters Valuation Signals in the Ventromedial Prefrontal Cortex. Frontiers in Behavioral Neuroscience. 5. 70–70. 64 indexed citations
19.
Libedinsky, Camilo, et al.. (2009). Perceptual and physiological evidence for a role for early visual areas in motion-induced blindness. Journal of Vision. 9(1). 14–14. 28 indexed citations
20.
Rodman, Hillary R., et al.. (2003). Pattern of retinal projections in the California ground squirrel (Spermophilus beecheyi): Anterograde tracing study using cholera toxin. The Journal of Comparative Neurology. 463(3). 317–340. 44 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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