Valentin Piëch

2.7k total citations · 2 hit papers
9 papers, 2.0k citations indexed

About

Valentin Piëch is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Biophysics. According to data from OpenAlex, Valentin Piëch has authored 9 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Cognitive Neuroscience, 3 papers in Cellular and Molecular Neuroscience and 2 papers in Biophysics. Recurrent topics in Valentin Piëch's work include Visual perception and processing mechanisms (6 papers), Neural dynamics and brain function (5 papers) and Neuroscience and Neuropharmacology Research (2 papers). Valentin Piëch is often cited by papers focused on Visual perception and processing mechanisms (6 papers), Neural dynamics and brain function (5 papers) and Neuroscience and Neuropharmacology Research (2 papers). Valentin Piëch collaborates with scholars based in United States, China and Germany. Valentin Piëch's co-authors include Charles D. Gilbert, Morgan Sheng, Maria Passafaro, Wu Li, Nathan R. Wilson, Carlo Sala, Guosong Liu, George N. Reeke, Jörg Polzehl and Karsten Tabelow and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Neuron and Nature Neuroscience.

In The Last Decade

Valentin Piëch

8 papers receiving 2.0k citations

Hit Papers

Regulation of Dendritic Spine Morphology and Synaptic Fun... 2001 2026 2009 2017 2001 2001 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Valentin Piëch United States 8 1.0k 1.0k 723 217 133 9 2.0k
Jin‐Hee Han South Korea 22 1.2k 1.1× 1.3k 1.3× 662 0.9× 206 0.9× 167 1.3× 58 2.3k
Siegrid Löwel Germany 29 2.0k 1.9× 1.9k 1.9× 1.3k 1.8× 186 0.9× 123 0.9× 84 3.5k
Christopher T. Richie United States 24 516 0.5× 1.1k 1.0× 1.0k 1.4× 279 1.3× 125 0.9× 49 2.4k
Jinhyun Kim South Korea 24 1.1k 1.0× 1.7k 1.6× 1.1k 1.5× 159 0.7× 190 1.4× 54 2.9k
Noritaka Ichinohe Japan 25 1.1k 1.0× 1.0k 1.0× 500 0.7× 54 0.2× 113 0.8× 96 2.1k
Jack Waters United States 29 1.4k 1.3× 1.8k 1.8× 976 1.3× 169 0.8× 153 1.2× 55 2.9k
Conny Kopp‐Scheinpflug Germany 25 1.1k 1.1× 951 0.9× 572 0.8× 140 0.6× 52 0.4× 45 2.2k
Matthew F. Nolan United Kingdom 27 1.6k 1.5× 2.0k 2.0× 846 1.2× 102 0.5× 90 0.7× 56 2.8k
Isabel A. Muzzio United States 17 733 0.7× 994 1.0× 539 0.7× 133 0.6× 92 0.7× 38 1.5k
J. Alexander Heimel Netherlands 25 923 0.9× 1.1k 1.0× 664 0.9× 96 0.4× 62 0.5× 55 1.8k

Countries citing papers authored by Valentin Piëch

Since Specialization
Citations

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

Fields of papers citing papers by Valentin Piëch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Valentin Piëch

This figure shows the co-authorship network connecting the top 25 collaborators of Valentin Piëch. A scholar is included among the top collaborators of Valentin Piëch 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 Valentin Piëch. Valentin Piëch is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Piëch, Valentin. (2025). Perceptual Learning, Long-Range Horizontal Connections And Top-Down Influences In Primary Visual Cortex. Digital Commons - RU (Rockefeller University).
2.
Piëch, Valentin, Wu Li, George N. Reeke, & Charles D. Gilbert. (2013). Network model of top-down influences on local gain and contextual interactions in visual cortex. Proceedings of the National Academy of Sciences. 110(43). E4108–17. 55 indexed citations
3.
Gilbert, Charles D., et al.. (2009). Perceptual learning and adult cortical plasticity. The Journal of Physiology. 587(12). 2743–2751. 104 indexed citations
4.
Tabelow, Karsten, Valentin Piëch, Jörg Polzehl, & Henning U. Voss. (2008). High-resolution fMRI: Overcoming the signal-to-noise problem. Journal of Neuroscience Methods. 178(2). 357–365. 21 indexed citations
5.
Li, Wu, Valentin Piëch, & Charles D. Gilbert. (2008). Learning to Link Visual Contours. Neuron. 57(3). 442–451. 171 indexed citations
6.
Li, Wu, Valentin Piëch, & Charles D. Gilbert. (2006). Contour Saliency in Primary Visual Cortex. Neuron. 50(6). 951–962. 186 indexed citations
7.
Li, Wu, Valentin Piëch, & Charles D. Gilbert. (2004). Perceptual learning and top-down influences in primary visual cortex. Nature Neuroscience. 7(6). 651–657. 364 indexed citations
8.
Sala, Carlo, Valentin Piëch, Nathan R. Wilson, et al.. (2001). Regulation of Dendritic Spine Morphology and Synaptic Function by Shank and Homer. Neuron. 31(1). 115–130. 564 indexed citations breakdown →
9.
Passafaro, Maria, Valentin Piëch, & Morgan Sheng. (2001). Subunit-specific temporal and spatial patterns of AMPA receptor exocytosis in hippocampal neurons. Nature Neuroscience. 4(9). 917–926. 529 indexed citations breakdown →

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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