Thomas Hannagan

899 total citations
21 papers, 495 citations indexed

About

Thomas Hannagan is a scholar working on Cognitive Neuroscience, Developmental and Educational Psychology and Artificial Intelligence. According to data from OpenAlex, Thomas Hannagan has authored 21 papers receiving a total of 495 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Cognitive Neuroscience, 9 papers in Developmental and Educational Psychology and 7 papers in Artificial Intelligence. Recurrent topics in Thomas Hannagan's work include Reading and Literacy Development (9 papers), Neural Networks and Applications (5 papers) and Multisensory perception and integration (5 papers). Thomas Hannagan is often cited by papers focused on Reading and Literacy Development (9 papers), Neural Networks and Applications (5 papers) and Multisensory perception and integration (5 papers). Thomas Hannagan collaborates with scholars based in France, United States and Spain. Thomas Hannagan's co-authors include Jonathan Grainger, Stanislas Dehaene, Laurent Cohen, Ghislaine Dehaene‐Lambertz, Amir Amedi, James S. Magnuson, Jonathan Grainger, Maria Ktori, Kimihiro Nakamura and Felipe Pegado and has published in prestigious journals such as Proceedings of the National Academy of Sciences, PLoS ONE and Trends in Cognitive Sciences.

In The Last Decade

Thomas Hannagan

21 papers receiving 485 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Thomas Hannagan France 14 312 247 145 111 68 21 495
Fabien Mathy France 11 252 0.8× 192 0.8× 137 0.9× 73 0.7× 118 1.7× 47 521
Bernard Ans France 8 303 1.0× 313 1.3× 50 0.3× 108 1.0× 133 2.0× 15 482
Benjamin D. Zinszer United States 14 305 1.0× 142 0.6× 85 0.6× 23 0.2× 53 0.8× 36 443
Jenelle Feather United States 7 349 1.1× 107 0.4× 75 0.5× 35 0.3× 19 0.3× 16 430
Alessandro Guida France 12 273 0.9× 104 0.4× 147 1.0× 133 1.2× 23 0.3× 33 403
Joshua Snell France 16 721 2.3× 772 3.1× 175 1.2× 132 1.2× 164 2.4× 44 922
René Carré France 8 266 0.9× 342 1.4× 192 1.3× 112 1.0× 100 1.5× 32 516
Benjamin Gagl Austria 13 357 1.1× 315 1.3× 73 0.5× 79 0.7× 74 1.1× 22 528
T. Preece United Kingdom 3 522 1.7× 234 0.9× 152 1.0× 40 0.4× 108 1.6× 5 603
Qilin Xue China 5 143 0.5× 237 1.0× 80 0.6× 344 3.1× 47 0.7× 7 494

Countries citing papers authored by Thomas Hannagan

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Hannagan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thomas Hannagan

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas Hannagan. A scholar is included among the top collaborators of Thomas Hannagan 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 Thomas Hannagan. Thomas Hannagan 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.
Brodbeck, Christian, Thomas Hannagan, & James S. Magnuson. (2025). Recurrent neural networks as neuro-computational models of human speech recognition. PLoS Computational Biology. 21(7). e1013244–e1013244. 1 indexed citations
2.
Magnuson, James S., et al.. (2024). Lexical Feedback in the Time-Invariant String Kernel (TISK) Model of Spoken Word Recognition. Journal of Cognition. 7(1). 38–38. 2 indexed citations
3.
Gripon, Vincent, et al.. (2022). Rethinking Weight Decay for Efficient Neural Network Pruning. Journal of Imaging. 8(3). 64–64. 15 indexed citations
4.
Hannagan, Thomas, et al.. (2021). Emergence of a compositional neural code for written words: Recycling of a convolutional neural network for reading. Proceedings of the National Academy of Sciences. 118(46). 21 indexed citations
5.
Hannagan, Thomas, Andreas Nieder, Pooja Viswanathan, & Stanislas Dehaene. (2018). A random-matrix theory of the number sense. Philosophical Transactions of the Royal Society B Biological Sciences. 373(1740). 20170253–20170253. 14 indexed citations
6.
Hannagan, Thomas, Amir Amedi, Laurent Cohen, Ghislaine Dehaene‐Lambertz, & Stanislas Dehaene. (2015). Origins of the specialization for letters and numbers in ventral occipitotemporal cortex. Trends in Cognitive Sciences. 19(7). 374–382. 156 indexed citations
7.
Ktori, Maria, et al.. (2014). On the time-course of adjacent and non-adjacent transposed-letter priming. Journal of Cognitive Psychology. 26(5). 491–505. 20 indexed citations
8.
Pegado, Felipe, Kimihiro Nakamura, & Thomas Hannagan. (2014). How does literacy break mirror invariance in the visual system?. Frontiers in Psychology. 5. 703–703. 28 indexed citations
9.
Hannagan, Thomas, Johannes C. Ziegler, Stéphane Dufau, Joël Fagot, & Jonathan Grainger. (2014). Deep Learning of Orthographic Representations in Baboons. PLoS ONE. 9(1). e84843–e84843. 14 indexed citations
10.
Grainger, Jonathan & Thomas Hannagan. (2014). What is special about orthographic processing?. Written Language & Literacy. 17(2). 225–252. 28 indexed citations
11.
Hannagan, Thomas & Jonathan Grainger. (2013). Learning diagnostic features: The delta rule does Bubbles. Journal of Vision. 13(8). 17–17. 6 indexed citations
12.
Hannagan, Thomas, et al.. (2013). Learning Spatial Invariance with the Trace Rule in Nonuniform Distributions. Neural Computation. 25(5). 1261–1276. 3 indexed citations
13.
Hannagan, Thomas & Jonathan Grainger. (2013). The Lazy Visual Word Form Area: Computational Insights into Location-Sensitivity. PLoS Computational Biology. 9(10). e1003250–e1003250. 3 indexed citations
14.
Dandurand, Frédéric, Thomas Hannagan, & Jonathan Grainger. (2013). Computational models of location-invariant orthographic processing. Connection Science. 25(1). 1–26. 13 indexed citations
15.
Hannagan, Thomas, James S. Magnuson, & Jonathan Grainger. (2013). Spoken word recognition without a TRACE. Frontiers in Psychology. 4. 563–563. 61 indexed citations
16.
Ziegler, Johannes C., Thomas Hannagan, Stéphane Dufau, et al.. (2013). Transposed-Letter Effects Reveal Orthographic Processing in Baboons. Psychological Science. 24(8). 1609–1611. 27 indexed citations
17.
Hannagan, Thomas, et al.. (2012). Deciphering CAPTCHAs: What a Turing Test Reveals about Human Cognition. PLoS ONE. 7(3). e32121–e32121. 20 indexed citations
18.
Hannagan, Thomas & Jonathan Grainger. (2012). Protein Analysis Meets Visual Word Recognition: A Case for String Kernels in the Brain. Cognitive Science. 36(4). 575–606. 27 indexed citations
19.
Dandurand, Frédéric, Thomas Hannagan, & Jonathan Grainger. (2010). Neural networks for word recognition: Is a hidden layer necessary?. eScholarship (California Digital Library). 32(32). 1 indexed citations
20.
Hannagan, Thomas, Emmanuel Dupoux, & Anne Christophe. (2010). Holographic String Encoding. Cognitive Science. 35(1). 79–118. 23 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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