István Sulykos

469 total citations
23 papers, 359 citations indexed

About

István Sulykos is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Statistics and Probability. According to data from OpenAlex, István Sulykos has authored 23 papers receiving a total of 359 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Cognitive Neuroscience, 19 papers in Experimental and Cognitive Psychology and 2 papers in Statistics and Probability. Recurrent topics in István Sulykos's work include Multisensory perception and integration (19 papers), Neuroscience and Music Perception (17 papers) and Neural dynamics and brain function (9 papers). István Sulykos is often cited by papers focused on Multisensory perception and integration (19 papers), Neuroscience and Music Perception (17 papers) and Neural dynamics and brain function (9 papers). István Sulykos collaborates with scholars based in Hungary and United Kingdom. István Sulykos's co-authors include István Czigler, Zsófia Anna Gaál, László Balázs, Bálint File, Szonya Durant, Ferenc Honbolygó, Péter Galambos, Péter Bárányi, Valéria Csépe and Andrea Kóbor and has published in prestigious journals such as PLoS ONE, Brain Research and Neuropsychologia.

In The Last Decade

István Sulykos

23 papers receiving 352 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
István Sulykos Hungary 12 333 259 40 22 14 23 359
David Van Valkenburg United States 5 230 0.7× 168 0.6× 38 0.9× 36 1.6× 6 0.4× 7 310
Karin M. Bausenhart Germany 14 532 1.6× 243 0.9× 60 1.5× 15 0.7× 3 0.2× 30 581
Shani Shalgi Israel 8 338 1.0× 145 0.6× 58 1.4× 7 0.3× 14 1.0× 8 395
Alberta Ipser United Kingdom 9 229 0.7× 176 0.7× 56 1.4× 3 0.1× 15 1.1× 15 306
Zohar Eitan Israel 11 434 1.3× 365 1.4× 129 3.2× 155 7.0× 7 0.5× 25 593
Gaëtan Sanchez France 7 343 1.0× 89 0.3× 36 0.9× 30 1.4× 3 0.2× 10 368
Jürg Kühnis Switzerland 11 307 0.9× 98 0.4× 35 0.9× 23 1.0× 3 0.2× 12 333
Martijn Baart Netherlands 14 358 1.1× 379 1.5× 54 1.4× 40 1.8× 8 0.6× 29 477
Sarah Dolscheid Germany 10 133 0.4× 310 1.2× 75 1.9× 8 0.4× 7 0.5× 24 393
Geoffrey L. Collier United States 10 319 1.0× 142 0.5× 125 3.1× 114 5.2× 6 0.4× 14 427

Countries citing papers authored by István Sulykos

Since Specialization
Citations

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

Fields of papers citing papers by István Sulykos

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of István Sulykos

This figure shows the co-authorship network connecting the top 25 collaborators of István Sulykos. A scholar is included among the top collaborators of István Sulykos 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 István Sulykos. István Sulykos 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.
Sulykos, István, et al.. (2019). Visual mismatch negativity and stimulus-specific adaptation: the role of stimulus complexity. Experimental Brain Research. 237(5). 1179–1194. 12 indexed citations
2.
Durant, Szonya, István Sulykos, & István Czigler. (2018). Automatic detection of the duration of visual static and dynamic stimuli. Brain Research. 1686. 34–41. 1 indexed citations
3.
Sulykos, István, et al.. (2018). Automatic change detection and spatial attention: a visual mismatch negativity study. European Journal of Neuroscience. 52(11). 4423–4431. 12 indexed citations
4.
Sulykos, István, Zsófia Anna Gaál, & István Czigler. (2018). Automatic Change Detection in Older and Younger Women: A Visual Mismatch Negativity Study. Gerontology. 64(4). 318–325. 6 indexed citations
5.
Sulykos, István, Zsófia Anna Gaál, & István Czigler. (2017). Visual mismatch negativity to vanishing parts of objects in younger and older adults. PLoS ONE. 12(12). e0188929–e0188929. 13 indexed citations
6.
Durant, Szonya, István Sulykos, & István Czigler. (2017). Automatic detection of orientation variance. Neuroscience Letters. 658. 43–47. 9 indexed citations
7.
File, Bálint, et al.. (2017). Visual mismatch negativity (vMMN) for low- and high-level deviances: A control study. Attention Perception & Psychophysics. 79(7). 2153–2170. 25 indexed citations
8.
Sulykos, István, et al.. (2017). Automatic change detection in vision: Adaptation, memory mismatch, or both? II: Oddball and adaptation effects on event-related potentials. Attention Perception & Psychophysics. 79(8). 2396–2411. 9 indexed citations
9.
Czigler, István, Zsófia Anna Gaál, & István Sulykos. (2017). S141 Aging and automatic detection of deviancy in vision: Event-related potential studies. Clinical Neurophysiology. 128(9). e224–e224. 1 indexed citations
10.
Sulykos, István, et al.. (2015). Asymmetric effect of automatic deviant detection: The effect of familiarity in visual mismatch negativity. Brain Research. 1626. 108–117. 13 indexed citations
11.
Sulykos, István & István Czigler. (2014). Visual mismatch negativity is sensitive to illusory brightness changes. Brain Research. 1561. 48–59. 12 indexed citations
12.
Czigler, István, et al.. (2014). Refractory issue and visual mismatch negativity: A skeleton in the cupboard. International Journal of Psychophysiology. 94(2). 155–155. 1 indexed citations
13.
Sulykos, István, Péter Galambos, Andrea Kóbor, et al.. (2014). Comparison between wireless and wired EEG recordings in a virtual reality lab: Case report. University of Debrecen Electronic Archive (University of Debrecen). 16. 599–603. 9 indexed citations
14.
Czigler, István, et al.. (2013). Asymmetry of automatic change detection shown by the visual mismatch negativity: An additional feature is identified faster than missing features. Cognitive Affective & Behavioral Neuroscience. 14(1). 278–285. 7 indexed citations
15.
Sulykos, István, et al.. (2013). Is it a face of a woman or a man? Visual mismatch negativity is sensitive to gender category. Frontiers in Human Neuroscience. 7. 532–532. 47 indexed citations
16.
Sulykos, István, et al.. (2013). Mismatch Negativity Does Not Show Evidence of Memory Reactivation in the Visual Modality. Journal of Psychophysiology. 27(1). 1–6. 13 indexed citations
17.
Sulykos, István, et al.. (2012). Visual mismatch negativity is sensitive to symmetry as a perceptual category. European Journal of Neuroscience. 37(4). 662–667. 40 indexed citations
18.
Sulykos, István & István Czigler. (2011). One plus one is less than two: Visual features elicit non-additive mismatch-related brain activity. Brain Research. 1398. 64–71. 51 indexed citations
19.
Czigler, István & István Sulykos. (2010). Deviant visual features or deviant events? 1+1>2. International Journal of Psychophysiology. 77(3). 221–222. 1 indexed citations
20.
Czigler, István & István Sulykos. (2009). Visual mismatch negativity to irrelevant changes is sensitive to task-relevant changes. Neuropsychologia. 48(5). 1277–1282. 40 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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