Alexander G. Huth

6.7k total citations · 3 hit papers
36 papers, 3.4k citations indexed

About

Alexander G. Huth is a scholar working on Cognitive Neuroscience, Artificial Intelligence and Experimental and Cognitive Psychology. According to data from OpenAlex, Alexander G. Huth has authored 36 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Cognitive Neuroscience, 9 papers in Artificial Intelligence and 5 papers in Experimental and Cognitive Psychology. Recurrent topics in Alexander G. Huth's work include Neural dynamics and brain function (13 papers), Functional Brain Connectivity Studies (9 papers) and Face Recognition and Perception (8 papers). Alexander G. Huth is often cited by papers focused on Neural dynamics and brain function (13 papers), Functional Brain Connectivity Studies (9 papers) and Face Recognition and Perception (8 papers). Alexander G. Huth collaborates with scholars based in United States, United Kingdom and Japan. Alexander G. Huth's co-authors include Jack L. Gallant, Shinji Nishimoto, Frédéric E. Theunissen, Thomas L. Griffiths, An T. Vu, Liberty S. Hamilton, Christof Koch, Tolga Çukur, Jonathan Malmaud and Anwar O. Núñez-Elizalde and has published in prestigious journals such as Nature, Nature Communications and Neuron.

In The Last Decade

Alexander G. Huth

35 papers receiving 3.3k citations

Hit Papers

Natural speech reveals th... 2012 2026 2016 2021 2016 2012 2023 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alexander G. Huth United States 20 2.7k 540 446 402 332 36 3.4k
Mariano Sigman Argentina 31 3.1k 1.1× 623 1.2× 446 1.0× 370 0.9× 350 1.1× 59 4.3k
Hiroyuki Sogo Japan 6 1.9k 0.7× 788 1.5× 476 1.1× 160 0.4× 477 1.4× 28 2.8k
Hedderik van Rijn Netherlands 36 2.8k 1.0× 921 1.7× 458 1.0× 491 1.2× 698 2.1× 174 3.9k
Guy Lories Belgium 10 1.9k 0.7× 774 1.4× 531 1.2× 221 0.5× 449 1.4× 21 2.9k
Sean M. Polyn United States 18 3.5k 1.3× 425 0.8× 334 0.7× 381 0.9× 394 1.2× 34 3.9k
John T. Serences United States 47 8.2k 3.1× 1.1k 2.0× 515 1.2× 170 0.4× 292 0.9× 115 8.7k
Thomas H. B. FitzGerald United Kingdom 30 3.3k 1.2× 738 1.4× 628 1.4× 323 0.8× 186 0.6× 45 4.3k
Peter Kok Netherlands 26 3.5k 1.3× 706 1.3× 423 0.9× 127 0.3× 190 0.6× 56 4.0k
David J. Freedman United States 35 4.9k 1.8× 549 1.0× 379 0.8× 464 1.2× 375 1.1× 65 6.0k
Stephen José Hanson United States 26 1.6k 0.6× 304 0.6× 216 0.5× 673 1.7× 359 1.1× 70 3.0k

Countries citing papers authored by Alexander G. Huth

Since Specialization
Citations

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

Fields of papers citing papers by Alexander G. Huth

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alexander G. Huth. 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 Alexander G. Huth. The network helps show where Alexander G. Huth may publish in the future.

Co-authorship network of co-authors of Alexander G. Huth

This figure shows the co-authorship network connecting the top 25 collaborators of Alexander G. Huth. A scholar is included among the top collaborators of Alexander G. Huth 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 Alexander G. Huth. Alexander G. Huth 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.
Tang, Jerry & Alexander G. Huth. (2025). Semantic language decoding across participants and stimulus modalities. Current Biology. 35(5). 1023–1032.e6.
2.
Huth, Alexander G., et al.. (2024). Occipital-temporal cortical tuning to semantic and affective features of natural images predicts associated behavioral responses. Nature Communications. 15(1). 5531–5531. 4 indexed citations
3.
LeBel, Amanda, et al.. (2023). A natural language fMRI dataset for voxelwise encoding models. Scientific Data. 10(1). 555–555. 16 indexed citations
4.
Huth, Alexander G., et al.. (2023). Phonemic segmentation of narrative speech in human cerebral cortex. Nature Communications. 14(1). 4309–4309. 7 indexed citations
5.
Jain, Shailee, Vy A. Vo, Leila Wehbe, & Alexander G. Huth. (2023). Computational Language Modeling and the Promise of In Silico Experimentation. SHILAP Revista de lepidopterología. 5(1). 80–106. 16 indexed citations
6.
Tang, Jerry, Amanda LeBel, Shailee Jain, & Alexander G. Huth. (2023). Semantic reconstruction of continuous language from non-invasive brain recordings. Nature Neuroscience. 26(5). 858–866. 151 indexed citations breakdown →
7.
Huth, Alexander G., et al.. (2022). Predictive Coding or Just Feature Discovery? An Alternative Account of Why Language Models Fit Brain Data. SHILAP Revista de lepidopterología. 5(1). 1–16. 22 indexed citations
8.
Huth, Alexander G., et al.. (2021). Attentional Modulation of Hierarchical Speech Representations in a Multitalker Environment. Cerebral Cortex. 31(11). 4986–5005. 11 indexed citations
9.
Huth, Alexander G., Natalia Y. Bilenko, Fatma Deniz, et al.. (2021). Visual and linguistic semantic representations are aligned at the border of human visual cortex. Nature Neuroscience. 24(11). 1628–1636. 78 indexed citations
10.
Jain, Shailee, et al.. (2020). Interpretable multi-timescale models for predicting fMRI responses to continuous natural speech. Neural Information Processing Systems. 33. 13738–13749. 1 indexed citations
11.
Deniz, Fatma, Anwar O. Núñez-Elizalde, Alexander G. Huth, & Jack L. Gallant. (2019). The Representation of Semantic Information Across Human Cerebral Cortex During Listening Versus Reading Is Invariant to Stimulus Modality. Journal of Neuroscience. 39(39). 7722–7736. 110 indexed citations
12.
Turek, Javier S., et al.. (2019). A single-layer RNN can approximate stacked and bidirectional RNNs, and topologies in between. 1 indexed citations
13.
Jain, Shailee & Alexander G. Huth. (2018). Incorporating Context into Language Encoding Models for fMRI. Neural Information Processing Systems. 31. 6628–6637. 9 indexed citations
14.
Wehbe, Leila, et al.. (2018). BOLD predictions: automated simulation of fMRI experiments. 1 indexed citations
15.
Nishimoto, Shinji, Alexander G. Huth, Natalia Y. Bilenko, & Jack L. Gallant. (2017). Eye movement-invariant representations in the human visual system. Journal of Vision. 17(1). 11–11. 13 indexed citations
16.
Çukur, Tolga, Alexander G. Huth, Shinji Nishimoto, & Jack L. Gallant. (2016). Functional Subdomains within Scene-Selective Cortex: Parahippocampal Place Area, Retrosplenial Complex, and Occipital Place Area. Journal of Neuroscience. 36(40). 10257–10273. 28 indexed citations
17.
Huth, Alexander G., et al.. (2016). Natural speech reveals the semantic maps that tile human cerebral cortex. Nature. 532(7600). 453–458. 836 indexed citations breakdown →
18.
Çukur, Tolga, Alexander G. Huth, Shinji Nishimoto, & Jack L. Gallant. (2013). Functional Subdomains within Human FFA. Journal of Neuroscience. 33(42). 16748–16766. 43 indexed citations
19.
Hamilton, Liberty S., et al.. (2013). Optogenetic Activation of an Inhibitory Network Enhances Feedforward Functional Connectivity in Auditory Cortex. Neuron. 80(4). 1066–1076. 66 indexed citations
20.
Milosavljevic, Milica, Jonathan Malmaud, Alexander G. Huth, Christof Koch, & Antonio Rangel. (2010). The Drift Diffusion Model can account for the accuracy and reaction time of value-based choices under high and low time pressure. Judgment and Decision Making. 5(6). 437–449. 232 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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