Ben Eppinger

2.6k total citations
42 papers, 1.7k citations indexed

About

Ben Eppinger is a scholar working on Cognitive Neuroscience, General Decision Sciences and Developmental and Educational Psychology. According to data from OpenAlex, Ben Eppinger has authored 42 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Cognitive Neuroscience, 16 papers in General Decision Sciences and 8 papers in Developmental and Educational Psychology. Recurrent topics in Ben Eppinger's work include Neural and Behavioral Psychology Studies (32 papers), Decision-Making and Behavioral Economics (16 papers) and Neural dynamics and brain function (9 papers). Ben Eppinger is often cited by papers focused on Neural and Behavioral Psychology Studies (32 papers), Decision-Making and Behavioral Economics (16 papers) and Neural dynamics and brain function (9 papers). Ben Eppinger collaborates with scholars based in Germany, Canada and United States. Ben Eppinger's co-authors include Jutta Kray, Shu Li, Axel Mecklinger, Dorothea Hämmerer, Leigh E. Nystrom, Jonathan D. Cohen, Hauke R. Heekeren, Andrea Reiter, Nicolas W. Schuck and Oliver P. John and has published in prestigious journals such as Nature Communications, Journal of Neuroscience and PLoS ONE.

In The Last Decade

Ben Eppinger

41 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ben Eppinger Germany 22 1.3k 380 300 217 196 42 1.7k
Roland G. Benoit Germany 18 1.6k 1.3× 1.0k 2.6× 236 0.8× 497 2.3× 297 1.5× 28 2.4k
Koji Jimura Japan 25 2.1k 1.6× 526 1.4× 257 0.9× 158 0.7× 238 1.2× 64 2.6k
Sebastian Gluth Switzerland 18 883 0.7× 234 0.6× 466 1.6× 61 0.3× 118 0.6× 39 1.3k
Maël Lebreton France 20 1.3k 1.0× 389 1.0× 338 1.1× 145 0.7× 210 1.1× 40 1.9k
Catalina J. Hooper United States 8 643 0.5× 377 1.0× 171 0.6× 233 1.1× 135 0.7× 8 1.3k
Noah A. Shamosh United States 7 590 0.5× 482 1.3× 274 0.9× 144 0.7× 226 1.2× 7 1.2k
Miriam Gade Germany 19 1.7k 1.3× 614 1.6× 179 0.6× 566 2.6× 196 1.0× 37 1.9k
Karolina M. Lempert United States 16 549 0.4× 385 1.0× 348 1.2× 54 0.2× 153 0.8× 29 1.1k
Sebastian Musslick United States 14 799 0.6× 339 0.9× 223 0.7× 109 0.5× 166 0.8× 37 1.4k
Corianne Rogalsky United States 18 1.5k 1.2× 501 1.3× 144 0.5× 483 2.2× 290 1.5× 40 1.8k

Countries citing papers authored by Ben Eppinger

Since Specialization
Citations

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

Fields of papers citing papers by Ben Eppinger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ben Eppinger

This figure shows the co-authorship network connecting the top 25 collaborators of Ben Eppinger. A scholar is included among the top collaborators of Ben Eppinger 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 Ben Eppinger. Ben Eppinger 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.
Eppinger, Ben, et al.. (2024). Observational reinforcement learning in children and young adults. npj Science of Learning. 9(1). 18–18. 1 indexed citations
2.
Eppinger, Ben, et al.. (2023). Diminished State Space Theory of Human Aging. Perspectives on Psychological Science. 20(2). 325–339. 3 indexed citations
3.
Germain, Nathalie, et al.. (2022). Changes in the Prevalence of Thin Bodies Bias Young Women’s Judgments About Body Size. Psychological Science. 33(8). 1212–1225. 10 indexed citations
4.
Eppinger, Ben, et al.. (2022). Need for cognition does not account for individual differences in metacontrol of decision making. Scientific Reports. 12(1). 8240–8240. 1 indexed citations
5.
Otto, A. Ross, et al.. (2021). Seizing the opportunity: Lifespan differences in the effects of the opportunity cost of time on cognitive control. Cognition. 216. 104863–104863. 12 indexed citations
6.
Reiter, Andrea, Shinsuke Suzuki, John P. O’Doherty, Shu Li, & Ben Eppinger. (2019). Risk contagion by peers affects learning and decision-making in adolescents.. Journal of Experimental Psychology General. 148(9). 1494–1504. 31 indexed citations
7.
Heekeren, Hauke R., et al.. (2018). Developmental differences in the neural dynamics of observational learning. Neuropsychologia. 119. 12–23. 14 indexed citations
8.
Kroemer, Nils B., Ying Lee, Shakoor Pooseh, et al.. (2018). L-DOPA reduces model-free control of behavior by attenuating the transfer of value to action. NeuroImage. 186. 113–125. 38 indexed citations
9.
Eppinger, Ben, et al.. (2017). Electrophysiological correlates reflect the integration of model-based and model-free decision information. Cognitive Affective & Behavioral Neuroscience. 17(2). 406–421. 23 indexed citations
10.
Bos, Wouter van den, Rasmus Bruckner, Matthew R. Nassar, Rui Mata, & Ben Eppinger. (2017). Computational neuroscience across the lifespan: Promises and pitfalls. Developmental Cognitive Neuroscience. 33. 42–53. 20 indexed citations
11.
Nassar, Matthew R., Rasmus Bruckner, Joshua I. Gold, et al.. (2016). Age differences in learning emerge from an insufficient representation of uncertainty in older adults. Nature Communications. 7(1). 11609–11609. 65 indexed citations
12.
Nassar, Matthew R., Rasmus Bruckner, & Ben Eppinger. (2016). What do we GANE with age?. Behavioral and Brain Sciences. 39. e218–e218. 2 indexed citations
13.
Eppinger, Ben, Hauke R. Heekeren, & Shu Li. (2015). Age-related prefrontal impairments implicate deficient prediction of future reward in older adults. Neurobiology of Aging. 36(8). 2380–2390. 28 indexed citations
14.
Eppinger, Ben, Nicolas W. Schuck, Leigh E. Nystrom, & Jonathan D. Cohen. (2013). Reduced Striatal Responses to Reward Prediction Errors in Older Compared with Younger Adults. Journal of Neuroscience. 33(24). 9905–9912. 98 indexed citations
15.
Eppinger, Ben, et al.. (2013). Of goals and habits: age-related and individual differences in goal-directed decision-making. Frontiers in Neuroscience. 7. 253–253. 92 indexed citations
16.
Eppinger, Ben, Leigh E. Nystrom, & Jonathan D. Cohen. (2012). Reduced Sensitivity to Immediate Reward during Decision-Making in Older than Younger Adults. PLoS ONE. 7(5). e36953–e36953. 102 indexed citations
17.
Hämmerer, Dorothea & Ben Eppinger. (2012). Dopaminergic and prefrontal contributions to reward-based learning and outcome monitoring during child development and aging.. Developmental Psychology. 48(3). 862–874. 61 indexed citations
18.
Eppinger, Ben, Dorothea Hämmerer, & Shu Li. (2011). Neuromodulation of reward‐based learning and decision making in human aging. Annals of the New York Academy of Sciences. 1235(1). 1–17. 157 indexed citations
19.
Eppinger, Ben, et al.. (2007). Better or worse than expected? Aging, learning, and the ERN. Neuropsychologia. 46(2). 521–539. 203 indexed citations
20.
Kray, Jutta & Ben Eppinger. (2006). Effects of associative learning on age differences in task-set switching. Acta Psychologica. 123(3). 187–203. 33 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Roland G. Benoit Breakdown of academic impact, for papers by Koji Jimura Breakdown of academic impact, for papers by Sebastian Gluth Breakdown of academic impact, for papers by Maël Lebreton Breakdown of academic impact, for papers by Catalina J. Hooper Breakdown of academic impact, for papers by Noah A. Shamosh Breakdown of academic impact, for papers by Miriam Gade Breakdown of academic impact, for papers by Karolina M. Lempert Breakdown of academic impact, for papers by Sebastian Musslick Breakdown of academic impact, for papers by Corianne Rogalsky
Rankless by CCL
2026