David Melcher

5.7k total citations
138 papers, 3.8k citations indexed

About

David Melcher is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Computer Vision and Pattern Recognition. According to data from OpenAlex, David Melcher has authored 138 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 127 papers in Cognitive Neuroscience, 33 papers in Experimental and Cognitive Psychology and 19 papers in Computer Vision and Pattern Recognition. Recurrent topics in David Melcher's work include Visual perception and processing mechanisms (97 papers), Neural dynamics and brain function (62 papers) and Neural and Behavioral Psychology Studies (42 papers). David Melcher is often cited by papers focused on Visual perception and processing mechanisms (97 papers), Neural dynamics and brain function (62 papers) and Neural and Behavioral Psychology Studies (42 papers). David Melcher collaborates with scholars based in Italy, United States and United Arab Emirates. David Melcher's co-authors include Andreas Wutz, Carol L. Colby, Luca Ronconi, Maria Concetta Morrone, Francesca Bacci, Eileen Kowler, Manuela Piazza, Alessio Fracasso, Jason Samaha and David Alais and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Neuron.

In The Last Decade

David Melcher

134 papers receiving 3.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David Melcher Italy 33 3.3k 730 559 288 269 138 3.8k
Werner X. Schneider Germany 31 3.9k 1.2× 751 1.0× 541 1.0× 496 1.7× 89 0.3× 76 4.4k
Frederick A. A. Kingdom Canada 31 3.2k 1.0× 509 0.7× 581 1.0× 963 3.3× 257 1.0× 145 3.8k
Jacqueline Gottlieb United States 34 4.5k 1.4× 847 1.2× 427 0.8× 422 1.5× 70 0.3× 56 5.5k
John T. Serences United States 47 8.2k 2.5× 1.1k 1.5× 409 0.7× 515 1.8× 97 0.4× 115 8.7k
Hans Strasburger Germany 24 2.3k 0.7× 351 0.5× 407 0.7× 283 1.0× 70 0.3× 77 3.0k
Susana T. L. Chung United States 33 3.1k 0.9× 444 0.6× 301 0.5× 319 1.1× 132 0.5× 149 4.0k
Árni Kristjánsson Iceland 37 3.6k 1.1× 1.0k 1.4× 671 1.2× 408 1.4× 113 0.4× 173 4.2k
Bruno G. Breitmeyer United States 40 6.5k 2.0× 1.3k 1.8× 467 0.8× 665 2.3× 206 0.8× 131 7.1k
Allison B. Sekuler Canada 42 4.5k 1.4× 1.1k 1.5× 962 1.7× 553 1.9× 65 0.2× 149 5.0k
Massimo Turatto Italy 33 2.7k 0.8× 699 1.0× 198 0.4× 360 1.3× 303 1.1× 96 3.2k

Countries citing papers authored by David Melcher

Since Specialization
Citations

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

Fields of papers citing papers by David Melcher

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Melcher

This figure shows the co-authorship network connecting the top 25 collaborators of David Melcher. A scholar is included among the top collaborators of David Melcher 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 David Melcher. David Melcher 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.
Melcher, David, et al.. (2024). Presaccadic preview shapes postsaccadic processing more where perception is poor. Proceedings of the National Academy of Sciences. 121(37). e2411293121–e2411293121. 2 indexed citations
2.
Melcher, David, et al.. (2023). The effect of familiarity on behavioral oscillations in face perception. Scientific Reports. 13(1). 10145–10145.
3.
Ronconi, Luca, et al.. (2023). Distinct Cortical Networks Subserve Spatio-temporal Sampling in Vision through Different Oscillatory Rhythms. Journal of Cognitive Neuroscience. 36(4). 572–589. 12 indexed citations
4.
Melcher, David, et al.. (2023). Aperiodic and Periodic EEG predict performance in a double-flash fusion task. Journal of Vision. 23(9). 5054–5054. 1 indexed citations
5.
Melcher, David, et al.. (2023). Electrophysiological signatures of visual temporal processing deficits in developmental dyslexia. Psychophysiology. 61(2). e14447–e14447. 5 indexed citations
6.
Melcher, David, et al.. (2022). Evidence for a theta‐band behavioural oscillation in rapid face detection. European Journal of Neuroscience. 56(7). 5033–5046. 3 indexed citations
7.
Ronconi, Luca, et al.. (2021). Shared resources between visual attention and visual working memory are allocated through rhythmic sampling. European Journal of Neuroscience. 55(11-12). 3040–3053. 19 indexed citations
8.
Huber‐Huber, Christoph & David Melcher. (2021). The behavioural preview effect with faces is susceptible to statistical regularities: Evidence for predictive processing across the saccade. Scientific Reports. 11(1). 942–942. 7 indexed citations
9.
Ronconi, Luca, David Melcher, Markus Junghöfer, Carsten H. Wolters, & Niko A. Busch. (2020). Testing the effect of tACS over parietal cortex in modulating endogenous alpha rhythm and temporal integration windows in visual perception. European Journal of Neuroscience. 55(11-12). 3438–3450. 17 indexed citations
10.
Melcher, David, Christoph Huber‐Huber, & Andreas Wutz. (2020). Enumerating the forest before the trees: The time courses of estimation-based and individuation-based numerical processing. Attention Perception & Psychophysics. 83(3). 1215–1229. 7 indexed citations
11.
Fabius, Jasper H., Alessio Fracasso, David Acunzo, Stefan Van der Stigchel, & David Melcher. (2020). Low-Level Visual Information Is Maintained across Saccades, Allowing for a Postsaccadic Handoff between Visual Areas. Journal of Neuroscience. 40(49). 9476–9486. 18 indexed citations
12.
Melcher, David, et al.. (2018). Endogenous attention modulates the temporal window of integration. Attention Perception & Psychophysics. 80(5). 1214–1228. 21 indexed citations
13.
Melcher, David, et al.. (2018). Different effects of spatial and temporal attention on the integration and segregation of stimuli in time. Attention Perception & Psychophysics. 81(2). 433–441. 16 indexed citations
14.
Buonocore, Antimo, Alessio Fracasso, & David Melcher. (2017). Pre-saccadic perception: Separate time courses for enhancement and spatial pooling at the saccade target. PLoS ONE. 12(6). e0178902–e0178902. 15 indexed citations
15.
Subramanian, Ramanathan, D. Shankar, Nicu Sebe, & David Melcher. (2014). Emotion modulates eye movement patterns and subsequent memory for the gist and details of movie scenes. Journal of Vision. 14(3). 31–31. 31 indexed citations
16.
Bapi, Raju S., et al.. (2014). Accounting for subjective time expansion based on a decision, rather than perceptual, mechanism. Journal of Vision. 14(10). 1150–1150. 1 indexed citations
17.
Corbett, Jennifer E. & David Melcher. (2013). Summary statistics support spatiotemporal stability.. Journal of Vision. 13(9). 1043–1043. 1 indexed citations
18.
Dempere‐Marco, Laura, David Melcher, & Gustavo Deco. (2012). Effective Visual Working Memory Capacity: An Emergent Effect from the Neural Dynamics in an Attractor Network. PLoS ONE. 7(8). e42719–e42719. 24 indexed citations
19.
Melcher, David, Thomas V. Papathomas, & Zoltán Vidnyánszky. (2005). Implicit Attentional Selection of Bound Visual Features. Neuron. 46(5). 723–729. 80 indexed citations
20.
Kovács, György, et al.. (2005). Hemifield-contingent face aftereffects. Perception. 34. 0–0.

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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