Greta Tuckute

1.2k total citations · 1 hit paper
19 papers, 454 citations indexed

About

Greta Tuckute is a scholar working on Cognitive Neuroscience, Artificial Intelligence and Social Psychology. According to data from OpenAlex, Greta Tuckute has authored 19 papers receiving a total of 454 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Cognitive Neuroscience, 6 papers in Artificial Intelligence and 3 papers in Social Psychology. Recurrent topics in Greta Tuckute's work include Topic Modeling (6 papers), Neurobiology of Language and Bilingualism (6 papers) and Neural dynamics and brain function (4 papers). Greta Tuckute is often cited by papers focused on Topic Modeling (6 papers), Neurobiology of Language and Bilingualism (6 papers) and Neural dynamics and brain function (4 papers). Greta Tuckute collaborates with scholars based in United States, Denmark and Switzerland. Greta Tuckute's co-authors include Evelina Fedorenko, Idan Blank, Martin Schrimpf, Nancy Kanwisher, Carina Kauf, Joshua B. Tenenbaum, Eghbal A. Hosseini, Shriya S. Srinivasan, Robert Barry and Hope Kean and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and Annual Review of Neuroscience.

In The Last Decade

Greta Tuckute

16 papers receiving 446 citations

Hit Papers

The neural architecture of language: Integrative modeling... 2021 2026 2022 2024 2021 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Greta Tuckute United States 9 298 135 79 62 57 19 454
Charlotte Caucheteux France 5 240 0.8× 131 1.0× 40 0.5× 43 0.7× 35 0.6× 6 365
Rajan Bhattacharyya United States 8 324 1.1× 65 0.5× 67 0.8× 73 1.2× 44 0.8× 27 415
Hyeon‐Ae Jeon South Korea 10 270 0.9× 26 0.2× 91 1.2× 48 0.8× 54 0.9× 25 380
Rosario Tomasello Germany 13 332 1.1× 55 0.4× 65 0.8× 174 2.8× 128 2.2× 27 475
Charles M. Wharton United States 8 272 0.9× 83 0.6× 132 1.7× 46 0.7× 91 1.6× 9 447
Amy Price United States 6 375 1.3× 16 0.1× 106 1.3× 92 1.5× 51 0.9× 8 431
Jesse J. Bengson United States 12 534 1.8× 38 0.3× 44 0.6× 49 0.8× 85 1.5× 19 595
Malte R. Henningsen‐Schomers Germany 8 293 1.0× 34 0.3× 74 0.9× 139 2.2× 114 2.0× 10 393
Sung-Joo Lim United States 10 346 1.2× 33 0.2× 111 1.4× 19 0.3× 162 2.8× 15 454
William G. Coon United States 15 424 1.4× 22 0.2× 71 0.9× 29 0.5× 70 1.2× 21 503

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
1.
Kay, Kendrick, Jacob S. Prince, Greta Tuckute, et al.. (2025). Disentangling signal and noise in neural responses through generative modeling. PLoS Computational Biology. 21(7). e1012092–e1012092.
2.
Tuckute, Greta, Kyle Mahowald, Phillip Isola, et al.. (2025). Intrinsically memorable words have unique associations with their meanings.. Journal of Experimental Psychology General. 154(8). 2059–2075.
3.
Tuckute, Greta, et al.. (2025). The LLM Language Network: A Neuroscientific Approach for Identifying Causally Task-Relevant Units. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 10887–10911. 2 indexed citations
4.
Li, Jian, Greta Tuckute, Evelina Fedorenko, et al.. (2024). JOSA: Joint surface-based registration and atlas construction of brain geometry and function. Medical Image Analysis. 98. 103292–103292. 1 indexed citations
5.
Tuckute, Greta, et al.. (2024). Driving and suppressing the human language network using large language models. Nature Human Behaviour. 8(3). 544–561. 30 indexed citations
6.
Tuckute, Greta, Nancy Kanwisher, & Evelina Fedorenko. (2024). Language in Brains, Minds, and Machines. Annual Review of Neuroscience. 47(1). 277–301. 13 indexed citations
7.
Kauf, Carina, Greta Tuckute, Roger Lévy, Jacob Andreas, & Evelina Fedorenko. (2023). Lexical-Semantic Content, Not Syntactic Structure, Is the Main Contributor to ANN-Brain Similarity of fMRI Responses in the Language Network. SHILAP Revista de lepidopterología. 5(1). 7–42. 10 indexed citations
8.
Tuckute, Greta, Jenelle Feather, Dana Boebinger, & Josh H. McDermott. (2023). Many but not all deep neural network audio models capture brain responses and exhibit correspondence between model stages and brain regions. PLoS Biology. 21(12). e3002366–e3002366. 16 indexed citations
9.
Tuckute, Greta, et al.. (2023). WhisBERT: Multimodal Text-Audio Language Modeling on 100M Words. 225–230. 2 indexed citations
10.
Tuckute, Greta, et al.. (2023). Driving and suppressing the human language network using large language models. 1 indexed citations
11.
Lipkin, Benjamin, Greta Tuckute, Josef Affourtit, et al.. (2022). Probabilistic atlas for the language network based on precision fMRI data from >800 individuals. Scientific Data. 9(1). 529–529. 67 indexed citations
12.
Tuckute, Greta, Alexander Paunov, Hope Kean, et al.. (2022). Frontal language areas do not emerge in the absence of temporal language areas: A case study of an individual born without a left temporal lobe. Neuropsychologia. 169. 108184–108184. 12 indexed citations
15.
Schrimpf, Martin, Idan Blank, Greta Tuckute, et al.. (2021). The neural architecture of language: Integrative modeling converges on predictive processing. Proceedings of the National Academy of Sciences. 118(45). 241 indexed citations breakdown →
16.
Tuckute, Greta, et al.. (2021). Real-Time Decoding of Attentional States Using Closed-Loop EEG Neurofeedback. Neural Computation. 33(4). 967–1004. 11 indexed citations
17.
Srinivasan, Shriya S., et al.. (2020). Agonist-antagonist myoneural interface amputation preserves proprioceptive sensorimotor neurophysiology in lower limbs. Science Translational Medicine. 12(573). 34 indexed citations
18.
Grubb, Søren, Linn Salto Mamsen, Greta Tuckute, et al.. (2019). Comparison of Cultured Human Cardiomyocyte Clusters Obtained from Embryos/Fetuses or Derived from Human Embryonic Stem Cells. Stem Cells and Development. 28(9). 608–619. 3 indexed citations
19.
Tuckute, Greta, et al.. (2019). Single-Trial Decoding of Scalp EEG under Natural Conditions. Computational Intelligence and Neuroscience. 2019. 1–11. 8 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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