Udo Boehm

1.2k total citations
19 papers, 530 citations indexed

About

Udo Boehm is a scholar working on Cognitive Neuroscience, General Decision Sciences and Experimental and Cognitive Psychology. According to data from OpenAlex, Udo Boehm has authored 19 papers receiving a total of 530 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Cognitive Neuroscience, 5 papers in General Decision Sciences and 4 papers in Experimental and Cognitive Psychology. Recurrent topics in Udo Boehm's work include Neural dynamics and brain function (6 papers), Decision-Making and Behavioral Economics (5 papers) and Neural and Behavioral Psychology Studies (5 papers). Udo Boehm is often cited by papers focused on Neural dynamics and brain function (6 papers), Decision-Making and Behavioral Economics (5 papers) and Neural and Behavioral Psychology Studies (5 papers). Udo Boehm collaborates with scholars based in Netherlands, Australia and United States. Udo Boehm's co-authors include Eric‐Jan Wagenmakers, Dóra Matzke, Maarten Marsman, Hedderik van Rijn, Leendert van Maanen, Birte U. Forstmann, Helen Steingroever, Quentin F. Gronau, Alexander Ly and Alexandra Sarafoglou and has published in prestigious journals such as NeuroImage, Scientific Reports and Psychological Methods.

In The Last Decade

Udo Boehm

19 papers receiving 523 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Udo Boehm Netherlands 10 299 121 91 80 66 19 530
Tom Lodewyckx Belgium 4 213 0.7× 139 1.1× 78 0.9× 124 1.6× 99 1.5× 5 572
André Aßfalg Germany 8 232 0.8× 99 0.8× 73 0.8× 24 0.3× 88 1.3× 19 396
Andrei Teodorescu Israel 10 336 1.1× 85 0.7× 114 1.3× 13 0.2× 57 0.9× 12 442
Elisabet Tubau Spain 11 182 0.6× 53 0.4× 144 1.6× 88 1.1× 68 1.0× 28 410
Lee Averell Australia 5 222 0.7× 71 0.6× 64 0.7× 17 0.2× 81 1.2× 7 459
Steven Miletić Netherlands 12 266 0.9× 59 0.5× 63 0.7× 24 0.3× 43 0.7× 26 385
Mario Fifić United States 12 403 1.3× 142 1.2× 44 0.5× 20 0.3× 114 1.7× 20 544
Nina R. Arnold Germany 10 236 0.8× 137 1.1× 42 0.5× 17 0.2× 54 0.8× 14 331
Kobe Desender Belgium 17 633 2.1× 139 1.1× 152 1.7× 15 0.2× 31 0.5× 32 772
Jonathan Malmaud United States 6 431 1.4× 137 1.1× 220 2.4× 10 0.1× 42 0.6× 7 758

Countries citing papers authored by Udo Boehm

Since Specialization
Citations

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

Fields of papers citing papers by Udo Boehm

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Udo Boehm

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

All Works

19 of 19 papers shown
1.
Ly, Alexander, Udo Boehm, Peter Grünwald, Aaditya Ramdas, & Don van Ravenzwaaij. (2025). A Tutorial on Safe Anytime-Valid Inference: Practical Maximally Flexible Sampling Designs for Experiments Based on e-Values. Research portal (Tilburg University). 1 indexed citations
2.
Boehm, Udo, et al.. (2023). Inclusion Bayes factors for mixed hierarchical diffusion decision models.. Psychological Methods. 29(4). 625–655. 6 indexed citations
3.
Boehm, Udo, et al.. (2022). Efficient numerical approximation of a non-regular Fokker–Planck equation associated with first-passage time distributions. BIT Numerical Mathematics. 62(4). 1355–1382. 2 indexed citations
4.
Boehm, Udo, Dóra Matzke, Joel M. Cooper, et al.. (2021). Correction to: Real-time prediction of short-timescale fluctuations in cognitive workload. Cognitive Research Principles and Implications. 6(1). 62–62. 1 indexed citations
5.
Boehm, Udo, Maarten Marsman, Han L. J. van der Maas, & Gunter Maris. (2021). An Attention-Based Diffusion Model for Psychometric Analyses. Psychometrika. 86(4). 938–972. 3 indexed citations
6.
Boehm, Udo, Dóra Matzke, Joel M. Cooper, et al.. (2021). Real-time prediction of short-timescale fluctuations in cognitive workload. Cognitive Research Principles and Implications. 6(1). 30–30. 9 indexed citations
7.
Retzler, Chris, et al.. (2021). Prior information use and response caution in perceptual decision-making: No evidence for a relationship with autistic-like traits. Quarterly Journal of Experimental Psychology. 74(11). 1953–1965. 4 indexed citations
8.
Boehm, Udo, et al.. (2021). Fast solutions for the first-passage distribution of diffusion models with space-time-dependent drift functions and time-dependent boundaries. Journal of Mathematical Psychology. 105. 102613–102613. 7 indexed citations
9.
Manning, Catherine, Eric‐Jan Wagenmakers, Anthony M. Norcia, Gaia Scerif, & Udo Boehm. (2020). Perceptual Decision-Making in Children: Age-Related Differences and EEG Correlates. Computational Brain & Behavior. 4(1). 53–69. 14 indexed citations
10.
Ly, Alexander, Angelika Marlene Stefan, Johnny van Doorn, et al.. (2020). The Bayesian Methodology of Sir Harold Jeffreys as a Practical Alternative to the P Value Hypothesis Test. Computational Brain & Behavior. 3(2). 153–161. 21 indexed citations
11.
Boehm, Udo, Leendert van Maanen, Nathan J. Evans, Scott Brown, & Eric‐Jan Wagenmakers. (2019). A theoretical analysis of the reward rate optimality of collapsing decision criteria. Attention Perception & Psychophysics. 82(3). 1520–1534. 6 indexed citations
12.
Boehm, Udo, Maarten Marsman, Dóra Matzke, & Eric‐Jan Wagenmakers. (2018). On the importance of avoiding shortcuts in applying cognitive models to hierarchical data. Behavior Research Methods. 50(4). 1614–1631. 48 indexed citations
13.
Boehm, Udo, Jeffrey Annis, Michael J. Frank, et al.. (2018). Estimating across-trial variability parameters of the Diffusion Decision Model: Expert advice and recommendations. Journal of Mathematical Psychology. 87. 46–75. 68 indexed citations
14.
Gronau, Quentin F., Alexandra Sarafoglou, Dóra Matzke, et al.. (2017). A tutorial on bridge sampling. Journal of Mathematical Psychology. 81. 80–97. 163 indexed citations
15.
Evans, Nathan J., Guy E. Hawkins, Udo Boehm, Eric‐Jan Wagenmakers, & Scott Brown. (2017). The computations that support simple decision-making: A comparison between the diffusion and urgency-gating models. Scientific Reports. 7(1). 16433–16433. 31 indexed citations
16.
Boehm, Udo, Helen Steingroever, & Eric‐Jan Wagenmakers. (2017). Using Bayesian regression to test hypotheses about relationships between parameters and covariates in cognitive models. Behavior Research Methods. 50(3). 1248–1269. 15 indexed citations
17.
Matzke, Dóra, Udo Boehm, & Joachim Vandekerckhove. (2017). Bayesian inference for psychology, part III: Parameter estimation in nonstandard models. Psychonomic Bulletin & Review. 25(1). 77–101. 21 indexed citations
18.
Boehm, Udo, Guy E. Hawkins, Scott Brown, Hedderik van Rijn, & Eric‐Jan Wagenmakers. (2015). Of monkeys and men: Impatience in perceptual decision-making. Psychonomic Bulletin & Review. 23(3). 738–749. 21 indexed citations
19.
Boehm, Udo, Leendert van Maanen, Birte U. Forstmann, & Hedderik van Rijn. (2014). Trial-by-trial fluctuations in CNV amplitude reflect anticipatory adjustment of response caution. NeuroImage. 96. 95–105. 89 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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