Martin N. Hebart

4.5k total citations
63 papers, 2.2k citations indexed

About

Martin N. Hebart is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Martin N. Hebart has authored 63 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Cognitive Neuroscience, 18 papers in Computer Vision and Pattern Recognition and 7 papers in Artificial Intelligence. Recurrent topics in Martin N. Hebart's work include Face Recognition and Perception (29 papers), Neural dynamics and brain function (22 papers) and Visual Attention and Saliency Detection (14 papers). Martin N. Hebart is often cited by papers focused on Face Recognition and Perception (29 papers), Neural dynamics and brain function (22 papers) and Visual Attention and Saliency Detection (14 papers). Martin N. Hebart collaborates with scholars based in Germany, United States and Netherlands. Martin N. Hebart's co-authors include John–Dylan Haynes, Chris I. Baker, Philipp Sterzer, Thomas B. Christophel, Timo Stein, Radoslaw Martin Cichy, Tobias H. Donner, Charles Zheng, Francisco Pereira and Kiley Seymour and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Neuroscience and Nature Neuroscience.

In The Last Decade

Martin N. Hebart

55 papers receiving 2.2k citations

Peers

Martin N. Hebart

ECP

CVPR

Marieke Mur United Kingdom

Jasmine Boshyan United States

Avniel Singh Ghuman United States

Andrew C. Connolly United States

Christopher Baldassano United States

Yoni Pertzov Israel

Hamed Nili United Kingdom

Julie D. Golomb United States

Weiwei Zhang United States

Arjen Alink Germany

Marieke Mur United Kingdom

Martin N. Hebart

1.8k ×1.0

325 ×1.0

ECP

285 ×1.2

294 ×1.6

CVPR

115 ×0.8

Citations per year, relative to Martin N. Hebart Martin N. Hebart (= 1×) peers Marieke Mur

Countries citing papers authored by Martin N. Hebart

Since Specialization

Citations

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

Fields of papers citing papers by Martin N. Hebart

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Martin N. Hebart. 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 Martin N. Hebart. The network helps show where Martin N. Hebart may publish in the future.

Co-authorship network of co-authors of Martin N. Hebart

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

All Works

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20 of 20 papers shown

Hebart, Martin N., et al.. (2025). Identifying and characterizing scene representations relevant for categorization behavior. Imaging Neuroscience. 3.

Hebart, Martin N., et al.. (2025). How to sample the world for understanding the visual system.

Güçlü, Umut, et al.. (2025). Dimensions underlying the representational alignment of deep neural networks with humans. Nature Machine Intelligence. 7(6). 848–859. 5 indexed citations

Seeliger, Katja & Martin N. Hebart. (2024). What comparing deep neural networks can teach us about human vision. Nature Machine Intelligence. 6(2). 122–123.

Baker, Chris I., et al.. (2024). Distributed representations of behaviour-derived object dimensions in the human visual system. Nature Human Behaviour. 8(11). 2179–2193. 14 indexed citations

Dima, Diana C., Martin N. Hebart, & Leyla Işık. (2023). A data-driven investigation of human action representations. Scientific Reports. 13(1). 5171–5171. 4 indexed citations

Borghesani, Valentina, et al.. (2023). The Three Terms Task - an open benchmark to compare human and artificial semantic representations. Scientific Data. 10(1). 117–117. 2 indexed citations

Hebart, Martin N., Lina Teichmann, Charles Zheng, et al.. (2023). THINGS-data, a multimodal collection of large-scale datasets for investigating object representations in human brain and behavior. eLife. 12. 51 indexed citations

Hebart, Martin N., et al.. (2023). The features underlying the memorability of objects. Science Advances. 9(17). eadd2981–eadd2981. 29 indexed citations

10.

Grootswagers, Tijl, et al.. (2022). Human EEG recordings for 1,854 concepts presented in rapid serial visual presentation streams. Scientific Data. 9(1). 3–3. 32 indexed citations

11.

Hebart, Martin N., et al.. (2022). Feature-reweighted representational similarity analysis: A method for improving the fit between computational models, brains, and behavior. NeuroImage. 257. 119294–119294. 23 indexed citations

12.

Cichy, Radoslaw Martin, et al.. (2022). The Spatiotemporal Neural Dynamics of Object Recognition for Natural Images and Line Drawings. Journal of Neuroscience. 43(3). 484–500. 10 indexed citations

13.

Hebart, Martin N., et al.. (2021). The organizational principles of de-differentiated topographic maps in somatosensory cortex. eLife. 10. 11 indexed citations

14.

Robinson, Amanda K., et al.. (2021). THINGS-EEG: Human electroencephalography recordings from 50 subjects for 22,248 images from 1,854 object concepts. OSF Preprints (OSF Preprints). 1 indexed citations

15.

Hebart, Martin N., Charles Zheng, Francisco Pereira, & Chris I. Baker. (2020). Revealing the multidimensional mental representations of natural objects underlying human similarity judgements. Nature Human Behaviour. 4(11). 1173–1185. 129 indexed citations

16.

Bönstrup, Marlene, Iñaki Iturrate, Martin N. Hebart, Nitzan Censor, & Leonardo G. Cohen. (2020). Mechanisms of offline motor learning at a microscale of seconds in large-scale crowdsourced data. npj Science of Learning. 5(1). 7–7. 54 indexed citations

17.

Hebart, Martin N., et al.. (2019). THINGS object concept and object image database. OSF Preprints (OSF Preprints). 1 indexed citations

18.

Hebart, Martin N., et al.. (2018). The representational dynamics of task and object processing in humans. eLife. 7. 106 indexed citations

19.

Hebart, Martin N. & Chris I. Baker. (2016). Facing up to stereotypes. Nature Neuroscience. 19(6). 763–764. 1 indexed citations

20.

Böhmer, Wendelin, et al.. (2016). Interaction of Instrumental and Goal-Directed Learning Modulates Prediction Error Representations in the Ventral Striatum. Journal of Neuroscience. 36(50). 12650–12660. 7 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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