Lilla Magyari

1.5k total citations
22 papers, 850 citations indexed

About

Lilla Magyari is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Developmental and Educational Psychology. According to data from OpenAlex, Lilla Magyari has authored 22 papers receiving a total of 850 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Cognitive Neuroscience, 8 papers in Experimental and Cognitive Psychology and 7 papers in Developmental and Educational Psychology. Recurrent topics in Lilla Magyari's work include Neurobiology of Language and Bilingualism (7 papers), Child and Animal Learning Development (6 papers) and Language, Metaphor, and Cognition (6 papers). Lilla Magyari is often cited by papers focused on Neurobiology of Language and Bilingualism (7 papers), Child and Animal Learning Development (6 papers) and Language, Metaphor, and Cognition (6 papers). Lilla Magyari collaborates with scholars based in Netherlands, Hungary and Germany. Lilla Magyari's co-authors include Marcel Bastiaansen, Stephen C. Levinson, Jan P. de Ruiter, Peter Hagoort, Sara Bögels, Johannes Vorwerk, Carsten H. Wolters, Robert Oostenveld, Maria Carla Piastra and D. van den Brink and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and NeuroImage.

In The Last Decade

Lilla Magyari

22 papers receiving 829 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lilla Magyari Netherlands 12 524 281 227 191 161 22 850
Elliot Murphy United Kingdom 16 306 0.6× 121 0.4× 179 0.8× 109 0.6× 68 0.4× 44 637
Edward Kako United States 10 260 0.5× 289 1.0× 387 1.7× 159 0.8× 65 0.4× 13 752
Marie Coppola United States 18 588 1.1× 507 1.8× 1.3k 5.6× 585 3.1× 113 0.7× 48 1.7k
Christian Forkstam Netherlands 15 739 1.4× 138 0.5× 415 1.8× 47 0.2× 94 0.6× 22 967
Tineke M. Snijders Netherlands 14 593 1.1× 103 0.4× 278 1.2× 48 0.3× 63 0.4× 26 740
Karin Stromswold United States 10 701 1.3× 173 0.6× 779 3.4× 143 0.7× 86 0.5× 24 1.1k
Kerry Ledoux United States 13 491 0.9× 146 0.5× 314 1.4× 60 0.3× 33 0.2× 20 625
Jörg Bahlmann Germany 18 1.4k 2.6× 293 1.0× 789 3.5× 92 0.5× 257 1.6× 23 1.7k
Hugh W. Buckingham United States 16 636 1.2× 325 1.2× 400 1.8× 120 0.6× 85 0.5× 60 827
Julia Uddén Netherlands 15 544 1.0× 95 0.3× 296 1.3× 37 0.2× 96 0.6× 23 714

Countries citing papers authored by Lilla Magyari

Since Specialization
Citations

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

Fields of papers citing papers by Lilla Magyari

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lilla Magyari

This figure shows the co-authorship network connecting the top 25 collaborators of Lilla Magyari. A scholar is included among the top collaborators of Lilla Magyari 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 Lilla Magyari. Lilla Magyari 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.
Magyari, Lilla, et al.. (2024). Neural evidence for referential understanding of object words in dogs. Current Biology. 34(8). 1750–1754.e4. 7 indexed citations
2.
Tóth, Brigitta, Ferenc Honbolygó, Orsolya Szalárdy, et al.. (2023). Speech prosody supports speaker selection and auditory stream segregation in a multi-talker situation. Brain Research. 1805. 148246–148246. 2 indexed citations
3.
Fugazza, Claudia, et al.. (2023). Investigating responses to object-labels in the domestic dog (Canis familiaris). Scientific Reports. 13(1). 3150–3150. 5 indexed citations
4.
Magyari, Lilla, Csaba Pléh, & Bálint Forgács. (2022). The Hungarian hubris syndrome. PLoS ONE. 17(8). e0273226–e0273226. 2 indexed citations
5.
Magyari, Lilla, et al.. (2022). Differences in dogs’ event-related potentials in response to human and dog vocal stimuli; a non-invasive study. Royal Society Open Science. 9(4). 211769–211769. 10 indexed citations
6.
Fugazza, Claudia, et al.. (2021). Rapid learning of object names in dogs. Scientific Reports. 11(1). 2222–2222. 26 indexed citations
7.
Magyari, Lilla, et al.. (2021). Neural processes underlying statistical learning for speech segmentation in dogs. Current Biology. 31(24). 5512–5521.e5. 20 indexed citations
8.
Magyari, Lilla, Anne Mangen, Anežka Kuzmičová, Arthur M. Jacobs, & Jana Lüdtke. (2020). Eye movements and mental imagery during reading of literary texts with different narrative styles. SHILAP Revista de lepidopterología. 13(3). 18 indexed citations
9.
Vorwerk, Johannes, Robert Oostenveld, Maria Carla Piastra, Lilla Magyari, & Carsten H. Wolters. (2018). The FieldTrip-SimBio pipeline for EEG forward solutions. BioMedical Engineering OnLine. 17(1). 37–37. 103 indexed citations
10.
Magyari, Lilla, Jan P. de Ruiter, & Stephen C. Levinson. (2017). Temporal Preparation for Speaking in Question-Answer Sequences. Frontiers in Psychology. 8. 211–211. 28 indexed citations
11.
Bögels, Sara, Lilla Magyari, & Stephen C. Levinson. (2015). Neural signatures of response planning occur midway through an incoming question in conversation. Scientific Reports. 5(1). 12881–12881. 106 indexed citations
12.
Vega, Manuel de, et al.. (2015). Brain dynamics in the comprehension of action-related language. A time-frequency analysis of mu rhythms. NeuroImage. 109. 50–62. 49 indexed citations
13.
Bögels, Sara, Lilla Magyari, & Stephen C. Levinson. (2014). Neural correlates of speech preparation in interactive turn-taking: An early start?. Max Planck Digital Library. 2 indexed citations
14.
Magyari, Lilla, Marcel Bastiaansen, Jan P. de Ruiter, & Stephen C. Levinson. (2014). Early Anticipation Lies behind the Speed of Response in Conversation. Journal of Cognitive Neuroscience. 26(11). 2530–2539. 112 indexed citations
15.
Bögels, Sara, Lilla Magyari, & Stephen C. Levinson. (2013). EEG correlates of processes related to turn-taking in an interactive quiz paradigm. Max Planck Digital Library. 1 indexed citations
16.
Vorwerk, Johannes, et al.. (2013). The fieldtrip-simbio pipeline for finite element EEG forward computations in MATLAB: Validation and application. MPG.PuRe (Max Planck Society). 6 indexed citations
17.
Wang, Lin, Ole Jensen, D. van den Brink, et al.. (2012). Beta oscillations relate to the N400m during language comprehension. Human Brain Mapping. 33(12). 2898–2912. 114 indexed citations
18.
Magyari, Lilla & Jan P. de Ruiter. (2012). Prediction of Turn-Ends Based on Anticipation of Upcoming Words. Frontiers in Psychology. 3. 376–376. 71 indexed citations
19.
Magyari, Lilla, et al.. (2011). Neuronal correlates of anticipation related to turn-taking in conversations. International Journal of Clinical Pharmacology and Therapeutics. 32(7). 376–8. 1 indexed citations
20.
Magyari, Lilla & Jan P. de Ruiter. (2008). Timing in conversation: the anticipation of turn endings. Max Planck Institute for Plasma Physics. 139–146. 6 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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