Ralf Weßel

1.8k total citations
47 papers, 1.2k citations indexed

About

Ralf Weßel is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Statistical and Nonlinear Physics. According to data from OpenAlex, Ralf Weßel has authored 47 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Cognitive Neuroscience, 24 papers in Cellular and Molecular Neuroscience and 11 papers in Statistical and Nonlinear Physics. Recurrent topics in Ralf Weßel's work include Neural dynamics and brain function (39 papers), Visual perception and processing mechanisms (12 papers) and stochastic dynamics and bifurcation (11 papers). Ralf Weßel is often cited by papers focused on Neural dynamics and brain function (39 papers), Visual perception and processing mechanisms (12 papers) and stochastic dynamics and bifurcation (11 papers). Ralf Weßel collaborates with scholars based in United States, Germany and Russia. Ralf Weßel's co-authors include Nathaniel C. Wright, David Kleinfeld, Zhengyu Ma, Keith B. Hengen, Harald Luksch, Wesley Clawson, Woodrow L. Shew, Gina G. Turrigiano, Uwe Drescher and Thomas Ciossek and has published in prestigious journals such as Physical Review Letters, Nature Communications and Neuron.

In The Last Decade

Ralf Weßel

45 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ralf Weßel United States 16 694 658 265 211 159 47 1.2k
Attila Szücs Hungary 21 488 0.7× 605 0.9× 321 1.2× 247 1.2× 43 0.3× 54 1.3k
Joël Tabak United States 22 563 0.8× 610 0.9× 363 1.4× 429 2.0× 144 0.9× 55 1.5k
Jason N. MacLean United States 22 985 1.4× 1.1k 1.7× 213 0.8× 88 0.4× 212 1.3× 47 1.6k
Hermann Cuntz Germany 22 868 1.3× 736 1.1× 284 1.1× 50 0.2× 156 1.0× 45 1.5k
Frances K. Skinner Canada 24 1.4k 2.0× 1.3k 2.0× 445 1.7× 359 1.7× 82 0.5× 86 2.0k
Elisabeth C. Walcott United States 11 363 0.5× 442 0.7× 323 1.2× 151 0.7× 33 0.2× 19 1.1k
Luis M. Martı́nez Spain 23 1.2k 1.7× 1.5k 2.3× 281 1.1× 78 0.4× 65 0.4× 45 1.9k
Vatsala Thirumalai India 17 623 0.9× 372 0.6× 219 0.8× 59 0.3× 176 1.1× 26 991
Sandrine Lefort Switzerland 12 1.0k 1.4× 1.1k 1.6× 208 0.8× 156 0.7× 28 0.2× 13 1.5k
Vladimir Itskov United States 13 970 1.4× 1.4k 2.2× 121 0.5× 89 0.4× 39 0.2× 21 1.8k

Countries citing papers authored by Ralf Weßel

Since Specialization
Citations

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

Fields of papers citing papers by Ralf Weßel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ralf Weßel

This figure shows the co-authorship network connecting the top 25 collaborators of Ralf Weßel. A scholar is included among the top collaborators of Ralf Weßel 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 Ralf Weßel. Ralf Weßel 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.
Weßel, Ralf, et al.. (2025). Brain-like border ownership signals support prediction of natural videos. iScience. 28(4). 112199–112199. 1 indexed citations
2.
Wang, Chao, Yuqi Liu, Ralf Weßel, et al.. (2024). Failure in a population: Tauopathy disrupts homeostatic set-points in emergent dynamics despite stability in the constituent neurons. Neuron. 112(21). 3567–3584.e5. 1 indexed citations
3.
Xu, Yifan, et al.. (2024). Sleep restores an optimal computational regime in cortical networks. Nature Neuroscience. 27(2). 328–338. 17 indexed citations
4.
Goard, Michael J., et al.. (2021). Stable representation of a naturalistic movie emerges from episodic activity with gain variability. Nature Communications. 12(1). 22 indexed citations
5.
Ma, Zhengyu, Haixin Liu, Takaki Komiyama, & Ralf Weßel. (2020). Stability of motor cortex network states during learning-associated neural reorganizations. Journal of Neurophysiology. 124(5). 1327–1342. 13 indexed citations
6.
Moseley, Benjamin, et al.. (2020). Pre-Synaptic Pool Modification (PSPM): A supervised learning procedure for recurrent spiking neural networks. PLoS ONE. 15(2). e0229083–e0229083. 1 indexed citations
7.
Wright, Nathaniel C., et al.. (2019). Dynamics and sources of response variability and its coordination in visual cortex. Visual Neuroscience. 36. E012–E012. 5 indexed citations
8.
Wright, Nathaniel C., et al.. (2019). Single-Cell Membrane Potential Fluctuations Evince Network Scale-Freeness and Quasicriticality. Journal of Neuroscience. 39(24). 4738–4759. 15 indexed citations
9.
Wright, Nathaniel C. & Ralf Weßel. (2017). Network activity influences the subthreshold and spiking visual responses of pyramidal neurons in the three-layer turtle cortex. Journal of Neurophysiology. 118(4). 2142–2155. 6 indexed citations
10.
Wright, Nathaniel C., et al.. (2017). Adaptation modulates correlated subthreshold response variability in visual cortex. Journal of Neurophysiology. 118(2). 1257–1269. 9 indexed citations
11.
Wright, Nathaniel C., et al.. (2017). Coupling of synaptic inputs to local cortical activity differs among neurons and adapts after stimulus onset. Journal of Neurophysiology. 118(6). 3345–3359. 5 indexed citations
12.
Ma, Zhengyu, et al.. (2017). Neocortical activity is stimulus- and scale-invariant. PLoS ONE. 12(5). e0177396–e0177396. 25 indexed citations
13.
Wright, Nathaniel C., et al.. (2017). The turtle visual system mediates a complex spatiotemporal transformation of visual stimuli into cortical activity. Journal of Comparative Physiology A. 204(2). 167–181. 1 indexed citations
14.
Weßel, Ralf, et al.. (2015). Coherent and intermittent ensemble oscillations emerge from networks of irregular spiking neurons. Journal of Neurophysiology. 115(1). 457–469. 8 indexed citations
15.
Wright, Nathaniel C., et al.. (2015). Turtle Dorsal Cortex Pyramidal Neurons Comprise Two Distinct Cell Types with Indistinguishable Visual Responses. PLoS ONE. 10(12). e0144012–e0144012. 14 indexed citations
16.
Eggebrecht, Adam T., et al.. (2010). Electrophysiological properties of isthmic neurons in frogs revealed by in vitro and in vivo studies. Journal of Comparative Physiology A. 196(4). 249–262. 5 indexed citations
17.
Nussinov, Zohar, et al.. (2009). Intricate phase diagram of a prevalent visual circuit reveals universal dynamics, phase transitions, and resonances. Physical Review E. 80(5). 51923–51923. 4 indexed citations
18.
Meyer, Ulrike, et al.. (2008). Distributed delays stabilize neural feedback systems. Biological Cybernetics. 99(1). 79–87. 20 indexed citations
19.
Weßel, Ralf, et al.. (2007). Winner-take-all selection in a neural system with delayed feedback. Biological Cybernetics. 97(3). 221–228. 10 indexed citations
20.
Luksch, Harald, et al.. (2004). Synaptic dynamics mediate sensitivity to motion independent of stimulus details. Nature Neuroscience. 7(4). 380–388. 36 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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