Viola S. Störmer

2.7k total citations
63 papers, 1.5k citations indexed

About

Viola S. Störmer is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Viola S. Störmer has authored 63 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 59 papers in Cognitive Neuroscience, 16 papers in Experimental and Cognitive Psychology and 10 papers in Computer Vision and Pattern Recognition. Recurrent topics in Viola S. Störmer's work include Neural and Behavioral Psychology Studies (40 papers), Visual perception and processing mechanisms (38 papers) and Neural dynamics and brain function (29 papers). Viola S. Störmer is often cited by papers focused on Neural and Behavioral Psychology Studies (40 papers), Visual perception and processing mechanisms (38 papers) and Neural dynamics and brain function (29 papers). Viola S. Störmer collaborates with scholars based in United States, Germany and Canada. Viola S. Störmer's co-authors include George A. Alvarez, Timothy F. Brady, John J. McDonald, Steven A. Hillyard, Shu Li, Antı́gona Martı́nez, Wenfeng Feng, Ulman Lindenberger, Hauke R. Heekeren and Patrick Cavanagh and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Neuroscience and NeuroImage.

In The Last Decade

Viola S. Störmer

59 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Viola S. Störmer United States 22 1.3k 480 206 132 114 63 1.5k
Marnix Naber Netherlands 18 1.1k 0.9× 210 0.4× 247 1.2× 176 1.3× 66 0.6× 70 1.4k
‪Søren K. Andersen Germany 25 1.8k 1.4× 317 0.7× 160 0.8× 99 0.8× 79 0.7× 49 1.9k
Daryl Fougnie United States 19 1.6k 1.2× 370 0.8× 326 1.6× 42 0.3× 108 0.9× 51 1.8k
Joseph Krummenacher Germany 23 1.6k 1.2× 390 0.8× 202 1.0× 94 0.7× 353 3.1× 38 1.7k
Maria Chait United Kingdom 27 1.9k 1.5× 679 1.4× 104 0.5× 148 1.1× 49 0.4× 71 2.1k
José van Velzen United Kingdom 20 1.4k 1.0× 417 0.9× 234 1.1× 66 0.5× 32 0.3× 40 1.5k
Mónika Kiss United Kingdom 28 2.4k 1.9× 591 1.2× 205 1.0× 151 1.1× 209 1.8× 36 2.6k
Karin Petrini United Kingdom 18 612 0.5× 516 1.1× 266 1.3× 164 1.2× 58 0.5× 63 973
Richard Godijn Netherlands 15 1.6k 1.2× 351 0.7× 155 0.8× 190 1.4× 174 1.5× 19 1.7k
Wieske van Zoest Italy 21 1.4k 1.0× 329 0.7× 174 0.8× 220 1.7× 352 3.1× 58 1.5k

Countries citing papers authored by Viola S. Störmer

Since Specialization
Citations

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

Fields of papers citing papers by Viola S. Störmer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Viola S. Störmer. 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 Viola S. Störmer. The network helps show where Viola S. Störmer may publish in the future.

Co-authorship network of co-authors of Viola S. Störmer

This figure shows the co-authorship network connecting the top 25 collaborators of Viola S. Störmer. A scholar is included among the top collaborators of Viola S. Störmer 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 Viola S. Störmer. Viola S. Störmer 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.
Störmer, Viola S., et al.. (2025). Early Cortical Sensitivity and Speeded Target Selection Underlie Incidentally Learned Prioritization of Visual Features. Journal of Neuroscience. 45(36). e0607252025–e0607252025.
2.
Störmer, Viola S., et al.. (2024). Similarity in feature space dictates the efficiency of attentional selection during ensemble processing. Psychonomic Bulletin & Review. 32(3). 1318–1327. 1 indexed citations
3.
Störmer, Viola S., et al.. (2024). Target–distractor similarity predicts visual search efficiency but only for highly similar features. Attention Perception & Psychophysics. 86(6). 1872–1882.
4.
Störmer, Viola S., et al.. (2024). Cutting Through the Noise: Auditory Scenes and Their Effects on Visual Object Processing. Psychological Science. 35(7). 814–824. 1 indexed citations
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Störmer, Viola S., et al.. (2024). Attention to object categories: Selection history determines the breadth of attentional tuning during real-world object search.. Journal of Experimental Psychology General. 153(6). 1568–1581. 4 indexed citations
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Störmer, Viola S., et al.. (2022). No evidence for proactive suppression of explicitly cued distractor features. Psychonomic Bulletin & Review. 29(4). 1338–1346. 13 indexed citations
10.
Brady, Timothy F., et al.. (2022). Guidance of attention by working memory is a matter of representational fidelity.. Journal of Experimental Psychology Human Perception & Performance. 48(3). 202–231. 18 indexed citations
11.
Störmer, Viola S., et al.. (2022). What You See Is What You Hear: Sounds Alter the Contents of Visual Perception. Psychological Science. 33(12). 2109–2122. 8 indexed citations
12.
Störmer, Viola S., et al.. (2022). Distractor ignoring is as effective as target enhancement when incidentally learned but not when explicitly cued. Attention Perception & Psychophysics. 85(3). 834–844. 8 indexed citations
13.
Wöstmann, Malte, Viola S. Störmer, Jonas Obleser, et al.. (2022). Ten simple rules to study distractor suppression. Progress in Neurobiology. 213. 102269–102269. 48 indexed citations
14.
Störmer, Viola S., et al.. (2021). Cross-modal orienting of exogenous attention results in visual-cortical facilitation, not suppression. Scientific Reports. 11(1). 10237–10237. 7 indexed citations
15.
Amadeo, Maria Bianca, Viola S. Störmer, Claudio Campus, & Monica Gori. (2019). Peripheral sounds elicit stronger activity in contralateral occipital cortex in blind than sighted individuals. Scientific Reports. 9(1). 11637–11637. 3 indexed citations
16.
Störmer, Viola S., John J. McDonald, & Steven A. Hillyard. (2019). Involuntary orienting of attention to sight or sound relies on similar neural biasing mechanisms in early visual processing. Neuropsychologia. 132. 107122–107122. 10 indexed citations
17.
Brady, Timothy F., Viola S. Störmer, & George A. Alvarez. (2016). Working memory is not fixed-capacity: More active storage capacity for real-world objects than for simple stimuli. Proceedings of the National Academy of Sciences. 113(27). 7459–7464. 159 indexed citations
18.
Störmer, Viola S. & George A. Alvarez. (2014). Feature-Based Attention Elicits Surround Suppression in Feature Space. Current Biology. 24(17). 1985–1988. 115 indexed citations
19.
Störmer, Viola S., Patrick Cavanagh, & George A. Alvarez. (2013). The profile of multifocal attention: surround-suppression between and within hemifields. Journal of Vision. 13(9). 1283–1283. 1 indexed citations
20.
Störmer, Viola S., Shu Li, Hauke R. Heekeren, & Ulman Lindenberger. (2011). Feature-based interference from unattended visual field during attentional tracking in younger and older adults. Journal of Vision. 11(2). 1–1. 57 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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