Jan Drugowitsch

3.9k total citations · 1 hit paper
55 papers, 1.9k citations indexed

About

Jan Drugowitsch is a scholar working on Cognitive Neuroscience, Artificial Intelligence and General Decision Sciences. According to data from OpenAlex, Jan Drugowitsch has authored 55 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Cognitive Neuroscience, 18 papers in Artificial Intelligence and 7 papers in General Decision Sciences. Recurrent topics in Jan Drugowitsch's work include Neural dynamics and brain function (29 papers), Neural and Behavioral Psychology Studies (13 papers) and Visual perception and processing mechanisms (12 papers). Jan Drugowitsch is often cited by papers focused on Neural dynamics and brain function (29 papers), Neural and Behavioral Psychology Studies (13 papers) and Visual perception and processing mechanisms (12 papers). Jan Drugowitsch collaborates with scholars based in United States, Switzerland and France. Jan Drugowitsch's co-authors include Alexandre Pouget, Rubén Moreno‐Bote, Ádám Kepecs, Anne K. Churchland, Michael N. Shadlen, Satohiro Tajima, Étienne Koechlin, Gregory C. DeAngelis, Dora E. Angelaki and Valentin Wyart and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Jan Drugowitsch

53 papers receiving 1.9k citations

Hit Papers

Confidence and certainty:... 2016 2026 2019 2022 2016 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Confidence and certainty: distinct probabilistic quantities for different goals
    2016 301 citations Alexandre Pouget, Jan Drugowitsch et al. Nature Neuroscience profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jan Drugowitsch United States 21 1.4k 336 234 229 218 55 1.9k
Alireza Soltani United States 19 1.3k 0.9× 314 0.9× 217 0.9× 105 0.5× 155 0.7× 44 1.6k
Eric Brown United States 7 1.3k 1.0× 286 0.9× 213 0.9× 164 0.7× 137 0.6× 7 1.9k
Jochen Ditterich United States 23 2.0k 1.5× 203 0.6× 257 1.1× 96 0.4× 156 0.7× 42 2.3k
Rubén Moreno‐Bote Spain 26 2.3k 1.6× 172 0.5× 668 2.9× 219 1.0× 143 0.7× 62 2.6k
Jamie D. Roitman United States 17 2.3k 1.7× 181 0.5× 541 2.3× 185 0.8× 206 0.9× 26 2.9k
Timothy D. Hanks United States 14 1.8k 1.3× 163 0.5× 443 1.9× 84 0.4× 167 0.8× 21 2.1k
Hang Zhang China 16 1.1k 0.8× 139 0.4× 101 0.4× 221 1.0× 302 1.4× 85 1.9k
Anne Collins United States 28 2.6k 1.9× 295 0.9× 372 1.6× 310 1.4× 710 3.3× 62 3.5k
Valentin Wyart France 27 3.0k 2.2× 208 0.6× 188 0.8× 130 0.6× 698 3.2× 55 3.3k
Hyojung Seo United States 20 2.0k 1.4× 125 0.4× 437 1.9× 159 0.7× 173 0.8× 32 2.3k

Countries citing papers authored by Jan Drugowitsch

Since Specialization
Citations

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

Fields of papers citing papers by Jan Drugowitsch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jan Drugowitsch

This figure shows the co-authorship network connecting the top 25 collaborators of Jan Drugowitsch. A scholar is included among the top collaborators of Jan Drugowitsch 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 Drugowitsch. Jan Drugowitsch 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.
Okubo, Tatsuo S., et al.. (2025). Multimodal cue integration and learning in a neural representation of head direction. Nature Neuroscience. 28(8). 1729–1740.
2.
Qiao, Zheng, et al.. (2025). An opponent striatal circuit for distributional reinforcement learning. Nature. 639(8055). 717–726. 3 indexed citations
3.
Rouault, Marion, et al.. (2022). Controllability boosts neural and cognitive signatures of changes-of-mind in uncertain environments. eLife. 11. 8 indexed citations
4.
Drugowitsch, Jan, et al.. (2021). A large majority of awake hippocampal sharp-wave ripples feature spatial trajectories with momentum. Neuron. 110(4). 722–733.e8. 14 indexed citations
5.
Chambon, Valérian, et al.. (2021). Interacting with volatile environments stabilizes hidden-state inference and its brain signatures. Nature Communications. 12(1). 2228–2228. 19 indexed citations
6.
Bill, Johannes, et al.. (2021). Human visual motion perception shows hallmarks of Bayesian structural inference. Scientific Reports. 11(1). 3714–3714. 32 indexed citations
7.
Bill, Johannes, et al.. (2020). Hierarchical structure is employed by humans during visual motion perception. Proceedings of the National Academy of Sciences. 117(39). 24581–24589. 15 indexed citations
8.
Neubarth, Nicole, Alan J. Emanuel, Annie Handler, et al.. (2020). Meissner corpuscles and their spatially intermingled afferents underlie gentle touch perception. Science. 368(6497). 89 indexed citations
9.
Moreno‐Bote, Rubén, et al.. (2020). Heuristics and optimal solutions to the breadth–depth dilemma. Proceedings of the National Academy of Sciences. 117(33). 19799–19808. 10 indexed citations
10.
Drugowitsch, Jan, et al.. (2019). Learning optimal decisions with confidence. Proceedings of the National Academy of Sciences. 116(49). 24872–24880. 38 indexed citations
11.
Moreno‐Bote, Rubén, et al.. (2019). Family of closed-form solutions for two-dimensional correlated diffusion processes. Physical review. E. 100(3). 32132–32132. 8 indexed citations
12.
Drugowitsch, Jan, Valentin Wyart, Anne-Dominique Devauchelle, & Étienne Koechlin. (2016). Computational Precision of Mental Inference as Critical Source of Human Choice Suboptimality. Neuron. 92(6). 1398–1411. 108 indexed citations
13.
Drugowitsch, Jan, Gregory C. DeAngelis, Dora E. Angelaki, & Alexandre Pouget. (2015). Tuning the speed-accuracy trade-off to maximize reward rate in multisensory decision-making. eLife. 4. e06678–e06678. 47 indexed citations
14.
Moreno‐Bote, Rubén & Jan Drugowitsch. (2015). Causal Inference and Explaining Away in a Spiking Network. Scientific Reports. 5(1). 17531–17531. 22 indexed citations
15.
Drugowitsch, Jan, Rubén Moreno‐Bote, & Alexandre Pouget. (2014). Optimal decision-making with time-varying evidence reliability. Neural Information Processing Systems. 27. 748–756. 8 indexed citations
16.
Drugowitsch, Jan, Rubén Moreno‐Bote, Anne K. Churchland, Michael N. Shadlen, & Alexandre Pouget. (2012). The Cost of Accumulating Evidence in Perceptual Decision Making. Journal of Neuroscience. 32(11). 3612–3628. 341 indexed citations
17.
Drugowitsch, Jan. (2008). Design and Analysis of Learning Classifier Systems: A Probabilistic Approach (Studies in Computational Intelligence). Springer eBooks. 268–268. 18 indexed citations
18.
Drugowitsch, Jan, et al.. (2007). A principled foundation for LCS. 2675–2680. 1 indexed citations
19.
Drugowitsch, Jan, et al.. (2007). A formal framework and extensions for function approximation in learning classifier systems. Machine Learning. 70(1). 45–88. 19 indexed citations
20.
Drugowitsch, Jan, et al.. (2007). Mixing independent classifiers. Pure (University of Bath). 1596–1603. 8 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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