Jan Zimmermann

3.0k total citations
64 papers, 1.3k citations indexed

About

Jan Zimmermann is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Jan Zimmermann has authored 64 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Cognitive Neuroscience, 10 papers in Computer Vision and Pattern Recognition and 10 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Jan Zimmermann's work include Neural dynamics and brain function (17 papers), Functional Brain Connectivity Studies (16 papers) and Advanced MRI Techniques and Applications (10 papers). Jan Zimmermann is often cited by papers focused on Neural dynamics and brain function (17 papers), Functional Brain Connectivity Studies (16 papers) and Advanced MRI Techniques and Applications (10 papers). Jan Zimmermann collaborates with scholars based in United States, Germany and Netherlands. Jan Zimmermann's co-authors include Rainer Goebel, Benjamin Y. Hayden, Kâmil Uǧurbil, Essa Yacoub, Federico De Martino, Benjamin R. Eisenreich, Oliver Sawodny, Ralph Grabhorn, Christian Röder and Hyun Soo Park and has published in prestigious journals such as Nature Communications, Journal of Neuroscience and SHILAP Revista de lepidopterología.

In The Last Decade

Jan Zimmermann

59 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jan Zimmermann United States 19 713 255 179 175 117 64 1.3k
Claes von Hofsten Sweden 23 1.1k 1.6× 65 0.3× 56 0.3× 477 2.7× 147 1.3× 55 2.0k
Pei Sun China 20 698 1.0× 214 0.8× 66 0.4× 162 0.9× 232 2.0× 67 1.2k
Takashi Ikeda Japan 20 725 1.0× 45 0.2× 76 0.4× 161 0.9× 122 1.0× 113 1.4k
James Bonaiuto United Kingdom 20 914 1.3× 59 0.2× 30 0.2× 324 1.9× 127 1.1× 48 1.2k
Christopher K. Kovach United States 26 1.8k 2.5× 100 0.4× 62 0.3× 170 1.0× 313 2.7× 57 2.2k
Klaus Kessler United Kingdom 29 1.9k 2.7× 73 0.3× 198 1.1× 737 4.2× 688 5.9× 83 2.8k
Guillaume S. Masson France 28 1.8k 2.5× 93 0.4× 50 0.3× 109 0.6× 109 0.9× 95 2.2k
Kang Cheng Japan 22 1.7k 2.4× 161 0.6× 42 0.2× 266 1.5× 208 1.8× 71 2.4k
Fang Fang China 29 2.7k 3.8× 135 0.5× 110 0.6× 360 2.1× 522 4.5× 139 3.3k
Zhixiang Zhao China 11 626 0.9× 171 0.7× 119 0.7× 130 0.7× 315 2.7× 43 1.1k

Countries citing papers authored by Jan Zimmermann

Since Specialization
Citations

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

Fields of papers citing papers by Jan Zimmermann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jan Zimmermann

This figure shows the co-authorship network connecting the top 25 collaborators of Jan Zimmermann. A scholar is included among the top collaborators of Jan Zimmermann 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 Jan Zimmermann. Jan Zimmermann 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.
Cadario, Romain, Jan Zimmermann, & Bram Van den Bergh. (2025). Beyond Opt-Out: How Presumed-Consent Language Shapes Persuasion. Journal of Marketing. 90(1). 72–90.
2.
Wischnewski, Miles, et al.. (2024). Induced neural phase precession through exogenous electric fields. Nature Communications. 15(1). 1687–1687. 18 indexed citations
3.
Monosov, Ilya E., Jan Zimmermann, Michael J. Frank, Mackenzie Weygandt Mathis, & Justin T. Baker. (2024). Ethological computational psychiatry: Challenges and opportunities. Current Opinion in Neurobiology. 86. 102881–102881. 7 indexed citations
4.
Basso, Michele A., Aaron P. Batista, Steve W. C. Chang, et al.. (2024). The Future of Nonhuman Primate Neuroscience: Peril or Possibilities?. Journal of Neuroscience. 44(37). e1458242024–e1458242024. 2 indexed citations
5.
Heilbronner, Sarah R., et al.. (2024). Neuroimaging of the effects of drug exposure or self-administration in rodents: A systematic review. Neuroscience & Biobehavioral Reviews. 164. 105823–105823. 1 indexed citations
6.
Zimmermann, Jan, et al.. (2023). Self-supervised Secondary Landmark Detection via 3D Representation Learning. International Journal of Computer Vision. 131(8). 1980–1994. 3 indexed citations
7.
Voloh, Benjamin, et al.. (2023). Widespread coding of navigational variables in prefrontal cortex. Current Biology. 33(16). 3478–3488.e3. 17 indexed citations
8.
Richardson, R. H., et al.. (2023). OpenApePose, a database of annotated ape photographs for pose estimation. eLife. 12.
9.
Wolf, B., Jan Zimmermann, Ian Marius Peters, et al.. (2023). From magnetic order to valence-change crossover in EuPd$_2$(Si$_{1-x}$Ge$_x$)$_2$ using He-gas pressure. SHILAP Revista de lepidopterología. 3 indexed citations
10.
Shirinpour, Sina, Oula Puonti, Ting Xu, et al.. (2023). Anatomical details affect electric field predictions for non-invasive brain stimulation in non-human primates. NeuroImage. 279. 120343–120343. 5 indexed citations
11.
Grier, Mark D., Essa Yacoub, Gregor Adriany, et al.. (2022). Ultra-high field (10.5T) diffusion-weighted MRI of the macaque brain. NeuroImage. 255. 119200–119200. 10 indexed citations
12.
Bullock, Daniel, et al.. (2022). The use of chemogenetic actuator ligands in nonhuman primate DREADDs-fMRI. SHILAP Revista de lepidopterología. 4. 100072–100072. 8 indexed citations
13.
Grier, Mark D., Jan Zimmermann, & Sarah R. Heilbronner. (2020). Estimating Brain Connectivity With Diffusion-Weighted Magnetic Resonance Imaging: Promise and Peril. Biological Psychiatry Cognitive Neuroscience and Neuroimaging. 5(9). 846–854. 18 indexed citations
14.
Eisenreich, Benjamin R., et al.. (2020). Automated markerless pose estimation in freely moving macaques with OpenMonkeyStudio. Nature Communications. 11(1). 4560–4560. 127 indexed citations
15.
Zimmermann, Jan, et al.. (2015). Decoding the direction of imagined visual motion using 7 T ultra-high field fMRI. NeuroImage. 125. 61–73. 34 indexed citations
16.
Gross, Jörg, Eva Woelbert, Jan Zimmermann, et al.. (2014). Value Signals in the Prefrontal Cortex Predict Individual Preferences across Reward Categories. Journal of Neuroscience. 34(22). 7580–7586. 42 indexed citations
17.
Heid, Ulrich & Jan Zimmermann. (2012). Usability testing as a tool for e-dictionary design: collocations as a case in point. 661–671. 3 indexed citations
18.
Zimmermann, Jan, Alard Roebroeck, Kâmil Uludaǧ, et al.. (2012). Network-based statistics for a community driven transparent publication process. Frontiers in Computational Neuroscience. 6. 11–11. 5 indexed citations
19.
Mohr, Harald M., et al.. (2011). Body image distortions in bulimia nervosa: Investigating body size overestimation and body size satisfaction by fMRI. NeuroImage. 56(3). 1822–1831. 57 indexed citations
20.
Mohr, Holger, Jan Zimmermann, Christian Röder, et al.. (2009). Separating two components of body image in anorexia nervosa using fMRI. Psychological Medicine. 40(9). 1519–1529. 112 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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