Greta Tuckute

1.2k citations
19 papers · 454 indexed · 1 hit paper · h-index 9
Topics
Topic Modeling (6 papers)Neurobiology of Language and Bilingualism (6 papers)Neural dynamics and brain function (4 papers)

In The Last Decade

Greta Tuckute

16 papers receiving 446 citations

Hit Papers

The neural architecture of language: Integrative modeling...2021202620222024202150100150200

Peers

Greta Tuckute
Comparison fields: 5 of 73
  • Cognitive Neuroscience 298
  • Artificial Intelligence 135
  • Developmental and Educational Psychology 79
  • Social Psychology 62
  • Experimental and Cognitive Psychology 57
Replace Charlotte Caucheteux with:
Charlotte Caucheteux France
Rosario Tomasello Germany
Anna A. Ivanova United States
Samuel Planton France
Terri L. Scott United States
Josef Affourtit United States
Malte R. Henningsen‐Schomers Germany
Dustin Stansbury United States
Hyeon‐Ae Jeon South Korea
Gary Tajchman United States
Greta Tuckute relative to Charlotte Caucheteux France Charlotte Caucheteux's profile →
Citations per field
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Charlotte Caucheteux · 1×
Citations per year

Countries citing papers authored by Greta Tuckute

Since Specialization
Citations

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

Fields of papers citing papers by Greta Tuckute

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Greta Tuckute

This figure shows the co-authorship network connecting the top 25 collaborators of Greta Tuckute. A scholar is included among the top collaborators of Greta Tuckute 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 Greta Tuckute. Greta Tuckute is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
#WorkIndexed citations
1 0
2 0
3 2
4 30
5 1
6 13
7 10
8 16
9 2
10 1
11 67
12 12
13 3
14 0
15
The neural architecture of language: Integrative modeling converges on predictive processingbreakdown →
241
16 11
17 34
18 3
19 8

About Greta Tuckute

Greta Tuckute is a scholar working on Cognitive Neuroscience, Artificial Intelligence and Signal Processing, having authored 19 papers that have together received 454 indexed citations. Recurring topics across this work include Topic Modeling (6 papers), Neurobiology of Language and Bilingualism (6 papers) and Neural dynamics and brain function (4 papers). The work is most often cited by research in Cognitive Neuroscience (298 citations), Health Informatics (9 citations) and Developmental and Educational Psychology (79 citations). Greta Tuckute has collaborated with scholars based in United States, Denmark and Switzerland. Frequent co-authors include Evelina Fedorenko, Martin Schrimpf, Idan Blank, Nancy Kanwisher, Carina Kauf, Eghbal A. Hosseini, Joshua B. Tenenbaum, Zachary Mineroff, Shriya S. Srinivasan and Robert Barry. Their work appears in journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and Annual Review of Neuroscience.

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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