Matthias Nau

63 total papers · 1.3k total citations
17 papers, 520 citations indexed

About

Matthias Nau is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Computer Vision and Pattern Recognition. According to data from OpenAlex, Matthias Nau has authored 17 papers receiving a total of 520 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Cognitive Neuroscience, 3 papers in Cellular and Molecular Neuroscience and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Matthias Nau's work include Neural dynamics and brain function (11 papers), Memory and Neural Mechanisms (9 papers) and Face Recognition and Perception (3 papers). Matthias Nau is often cited by papers focused on Neural dynamics and brain function (11 papers), Memory and Neural Mechanisms (9 papers) and Face Recognition and Perception (3 papers). Matthias Nau collaborates with scholars based in Germany, Norway and United States. Matthias Nau's co-authors include Christian F. Doeller, Tobias Navarro Schröder, Jacob L. S. Bellmund, Markus Frey, Franco Pestilli, Thomas Naselaris, Yihan Wu, Emily Allen, Jacob S. Prince and Logan T. Dowdle and has published in prestigious journals such as Nature Communications, Nature Neuroscience and NeuroImage.

In The Last Decade

Matthias Nau

15 papers receiving 517 citations

Hit Papers

A massive 7T fMRI dataset... 2021 2026 2022 2024 2021 50 100 150 200

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Matthias Nau 420 83 81 46 42 17 520
Benedikt Ehinger 398 0.9× 60 0.7× 94 1.2× 13 0.3× 46 1.1× 24 588
Jack Ryan 433 1.0× 73 0.9× 67 0.8× 24 0.5× 70 1.7× 15 591
R. M. Pritchard 410 1.0× 82 1.0× 60 0.7× 19 0.4× 14 0.3× 13 557
Aiden E. G. F. Arnold 389 0.9× 44 0.5× 33 0.4× 27 0.6× 92 2.2× 13 518
Arash Yazdanbakhsh 527 1.3× 59 0.7× 59 0.7× 31 0.7× 40 1.0× 39 596
Denis Sheynikhovich 323 0.8× 155 1.9× 27 0.3× 47 1.0× 37 0.9× 19 451
Lukas Kunz 459 1.1× 209 2.5× 21 0.3× 27 0.6× 27 0.6× 26 615
Katherine R. Sherrill 418 1.0× 134 1.6× 16 0.2× 16 0.3× 61 1.5× 10 476
Daniel N. Barry 463 1.1× 185 2.2× 21 0.3× 25 0.5× 63 1.5× 18 596
Serra E. Favila 535 1.3× 165 2.0× 14 0.2× 35 0.8× 59 1.4× 9 581

Countries citing papers authored by Matthias Nau

Since Specialization
Citations

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

Fields of papers citing papers by Matthias Nau

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthias Nau

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

All Works

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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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