Eric Lowet

1.4k total citations
26 papers, 710 citations indexed

About

Eric Lowet is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Statistical and Nonlinear Physics. According to data from OpenAlex, Eric Lowet has authored 26 papers receiving a total of 710 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Cognitive Neuroscience, 19 papers in Cellular and Molecular Neuroscience and 5 papers in Statistical and Nonlinear Physics. Recurrent topics in Eric Lowet's work include Neural dynamics and brain function (24 papers), Neuroscience and Neural Engineering (12 papers) and Photoreceptor and optogenetics research (10 papers). Eric Lowet is often cited by papers focused on Neural dynamics and brain function (24 papers), Neuroscience and Neural Engineering (12 papers) and Photoreceptor and optogenetics research (10 papers). Eric Lowet collaborates with scholars based in Netherlands, United States and United Kingdom. Eric Lowet's co-authors include Mark Roberts, Peter De Weerd, Pascal Fries, Marije Ter Wal, Nicolas M. Brunet, Paul Tiesinga, Alina Peter, Avgis Hadjipapas, Pietro Bonizzi and Joël Karel and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Neuron.

In The Last Decade

Eric Lowet

25 papers receiving 709 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Eric Lowet Netherlands 12 617 345 64 41 36 26 710
Michael Denker Germany 14 449 0.7× 321 0.9× 63 1.0× 100 2.4× 55 1.5× 38 630
Bruss Lima Brazil 15 878 1.4× 405 1.2× 46 0.7× 52 1.3× 16 0.4× 40 950
Thomas T. G. Hahn Germany 6 799 1.3× 664 1.9× 65 1.0× 55 1.3× 27 0.8× 9 878
Jarrod Robert Dowdall Germany 7 967 1.6× 292 0.8× 42 0.7× 49 1.2× 19 0.5× 10 1.0k
Rishidev Chaudhuri United States 8 955 1.5× 278 0.8× 73 1.1× 90 2.2× 29 0.8× 11 1.1k
Muhammad Habib United States 6 775 1.3× 397 1.2× 125 2.0× 49 1.2× 32 0.9× 14 901
Tobias C. Potjans Japan 8 651 1.1× 404 1.2× 66 1.0× 261 6.4× 27 0.8× 15 781
Alexander Zhigalov United Kingdom 15 893 1.4× 182 0.5× 57 0.9× 47 1.1× 50 1.4× 19 993
Alexander O. Komendantov United States 11 304 0.5× 313 0.9× 44 0.7× 32 0.8× 19 0.5× 17 454
Bartosz Teleńczuk France 14 497 0.8× 300 0.9× 66 1.0× 83 2.0× 22 0.6× 21 590

Countries citing papers authored by Eric Lowet

Since Specialization
Citations

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

Fields of papers citing papers by Eric Lowet

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eric Lowet

This figure shows the co-authorship network connecting the top 25 collaborators of Eric Lowet. A scholar is included among the top collaborators of Eric Lowet 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 Eric Lowet. Eric Lowet 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.
Kondabolu, Krishnakanth, et al.. (2025). Kilohertz electrical stimulation evokes robust cellular responses like conventional frequencies but distinct population dynamics. Communications Biology. 8(1). 19–19. 2 indexed citations
2.
Lowet, Eric, et al.. (2024). Beta-frequency sensory stimulation enhances gait rhythmicity through strengthened coupling between striatal networks and stepping movement. Nature Communications. 15(1). 8336–8336. 1 indexed citations
3.
Xiao, Sheng, W. J. Cunningham, Krishnakanth Kondabolu, et al.. (2024). Large-scale deep tissue voltage imaging with targeted-illumination confocal microscopy. Nature Methods. 21(6). 1094–1102. 11 indexed citations
4.
Lowet, Eric, et al.. (2023). Striatal cholinergic interneuron membrane voltage tracks locomotor rhythms in mice. Nature Communications. 14(1). 3802–3802. 12 indexed citations
5.
Lowet, Eric, Daniel J. Sheehan, Sheng Xiao, et al.. (2023). Theta and gamma rhythmic coding through two spike output modes in the hippocampus during spatial navigation. Cell Reports. 42(8). 112906–112906. 9 indexed citations
6.
Lowet, Eric, Peter De Weerd, Mark Roberts, & Avgis Hadjipapas. (2022). Tuning Neural Synchronization: The Role of Variable Oscillation Frequencies in Neural Circuits. Frontiers in Systems Neuroscience. 16. 908665–908665. 7 indexed citations
7.
Lowet, Eric, et al.. (2022). Deep brain stimulation creates informational lesion through membrane depolarization in mouse hippocampus. Nature Communications. 13(1). 7709–7709. 26 indexed citations
8.
Zachariou, Margarita, Mark Roberts, Eric Lowet, Peter De Weerd, & Avgis Hadjipapas. (2021). Empirically constrained network models for contrast-dependent modulation of gamma rhythm in V1. NeuroImage. 229. 117748–117748. 6 indexed citations
9.
Xiao, Sheng, Eric Lowet, Howard J. Gritton, et al.. (2021). Large-scale voltage imaging in behaving mice using targeted illumination. iScience. 24(11). 103263–103263. 24 indexed citations
10.
Lowet, Eric, Sheng Xiao, Jérôme Mertz, & Xue Han. (2021). Ultrafast Voltage Imaging of Single Neurons at Ten Kilohertz in Behaving Mice. FM5E.1–FM5E.1. 2 indexed citations
11.
Lowet, Eric, et al.. (2020). Context-Dependent Sensory Processing across Primary and Secondary Somatosensory Cortex. Neuron. 106(3). 515–525.e5. 40 indexed citations
12.
13.
Lowet, Eric, et al.. (2018). Microsaccade-rhythmic modulation of neural synchronization and coding within and across cortical areas V1 and V2. PLoS Biology. 16(5). e2004132–e2004132. 16 indexed citations
14.
Lowet, Eric, et al.. (2018). Enhanced Neural Processing by Covert Attention only during Microsaccades Directed toward the Attended Stimulus. Neuron. 99(1). 207–214.e3. 75 indexed citations
15.
Lowet, Eric, Mark Roberts, Alina Peter, Bart Gips, & Peter De Weerd. (2017). A quantitative theory of gamma synchronization in macaque V1. eLife. 6. 42 indexed citations
16.
Gips, Bart, Ali Bahramisharif, Eric Lowet, et al.. (2016). Discovering recurring patterns in electrophysiological recordings. Journal of Neuroscience Methods. 275. 66–79. 8 indexed citations
17.
Lowet, Eric, Mark Roberts, Pietro Bonizzi, Joël Karel, & Peter De Weerd. (2016). Quantifying Neural Oscillatory Synchronization: A Comparison between Spectral Coherence and Phase-Locking Value Approaches. PLoS ONE. 11(1). e0146443–e0146443. 90 indexed citations
18.
Lowet, Eric, et al.. (2015). Input-Dependent Frequency Modulation of Cortical Gamma Oscillations Shapes Spatial Synchronization and Enables Phase Coding. PLoS Computational Biology. 11(2). e1004072–e1004072. 46 indexed citations
19.
Lowet, Eric, Mark Roberts, Conrado A. Bosman, Pascal Fries, & Peter De Weerd. (2015). Areas V1 and V2 show microsaccade‐related 3–4‐Hz covariation in gamma power and frequency. European Journal of Neuroscience. 43(10). 1286–1296. 49 indexed citations
20.
Roberts, Mark, Eric Lowet, Nicolas M. Brunet, et al.. (2013). Robust Gamma Coherence between Macaque V1 and V2 by Dynamic Frequency Matching. Neuron. 78(3). 523–536. 186 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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