Ming Hsu

6.4k total citations · 1 hit paper
67 papers, 2.9k citations indexed

About

Ming Hsu is a scholar working on Cognitive Neuroscience, General Decision Sciences and Economics and Econometrics. According to data from OpenAlex, Ming Hsu has authored 67 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Cognitive Neuroscience, 21 papers in General Decision Sciences and 10 papers in Economics and Econometrics. Recurrent topics in Ming Hsu's work include Neural and Behavioral Psychology Studies (30 papers), Decision-Making and Behavioral Economics (21 papers) and Psychology of Moral and Emotional Judgment (16 papers). Ming Hsu is often cited by papers focused on Neural and Behavioral Psychology Studies (30 papers), Decision-Making and Behavioral Economics (21 papers) and Psychology of Moral and Emotional Judgment (16 papers). Ming Hsu collaborates with scholars based in United States, China and Switzerland. Ming Hsu's co-authors include Colin F. Camerer, Ian Krajbich, Lusha Zhu, Min Jeong Kang, George Loewenstein, Samuel M. McClure, Joseph Tao‐yi Wang, Steven R. Quartz, Kenji Kobayashi and Mauricio R. Delgado and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Ming Hsu

64 papers receiving 2.8k citations

Hit Papers

The Wick in the Candle of Learning 2009 2026 2014 2020 2009 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ming Hsu United States 26 1.6k 808 611 523 434 67 2.9k
Benedetto De Martino United Kingdom 22 2.1k 1.4× 589 0.7× 1.1k 1.7× 380 0.7× 262 0.6× 34 3.4k
Peter Sokol‐Hessner United States 16 1.3k 0.8× 655 0.8× 491 0.8× 436 0.8× 322 0.7× 27 2.4k
Johannes Hewig Germany 34 2.0k 1.3× 955 1.2× 360 0.6× 537 1.0× 348 0.8× 113 3.1k
Christopher Y. Olivola United States 22 1.4k 0.9× 1.5k 1.8× 331 0.5× 639 1.2× 1.0k 2.4× 41 3.3k
Douglas H. Wedell United States 29 798 0.5× 527 0.7× 996 1.6× 498 1.0× 369 0.9× 90 2.7k
Rui Mata Switzerland 32 1.1k 0.7× 599 0.7× 1.2k 2.0× 519 1.0× 386 0.9× 88 3.4k
Eldad Yechiam Israel 32 1.2k 0.8× 474 0.6× 1.3k 2.2× 282 0.5× 409 0.9× 93 3.4k
Bernd Figner Netherlands 20 1.2k 0.7× 875 1.1× 726 1.2× 492 0.9× 364 0.8× 58 3.1k
Terry Lohrenz United States 25 1.3k 0.8× 476 0.6× 269 0.4× 449 0.9× 309 0.7× 50 2.5k
Joseph T. McGuire United States 14 2.4k 1.5× 755 0.9× 729 1.2× 435 0.8× 198 0.5× 29 3.3k

Countries citing papers authored by Ming Hsu

Since Specialization
Citations

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

Fields of papers citing papers by Ming Hsu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming Hsu

This figure shows the co-authorship network connecting the top 25 collaborators of Ming Hsu. A scholar is included among the top collaborators of Ming Hsu 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 Ming Hsu. Ming Hsu 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
2.
Moxon, Karen A., Jack J. Lin, Edward F. Chang, et al.. (2025). Distributed Intracranial Activity Underlying Human Decision-making Behavior. Journal of Neuroscience. 45(15). e0572242024–e0572242024. 3 indexed citations
3.
Elliott, Matthew, et al.. (2025). Introducing the Glutamate-Amplifies-Noradrenergic-Effects (GANE) Model to the Neurocognitive Study of Emotion-Related Impulsivity. Clinical Psychological Science. 13(4). 810–834. 1 indexed citations
4.
Lee, Sangil, et al.. (2024). Distinguishing deception from its confounds by improving the validity of fMRI-based neural prediction. Proceedings of the National Academy of Sciences. 121(50). e2412881121–e2412881121. 3 indexed citations
5.
Horen, Femke van, et al.. (2023). From scanner to court: A neuroscientifically informed “reasonable person” test of trademark infringement. Science Advances. 9(6). eabo1095–eabo1095. 2 indexed citations
6.
Hunter, Lindsay E., Elana Meer, Claire M. Gillan, Ming Hsu, & Nathaniel D. Daw. (2021). Increased and biased deliberation in social anxiety. Nature Human Behaviour. 6(1). 146–154. 30 indexed citations
7.
Kobayashi, Kenji & Ming Hsu. (2019). Common neural code for reward and information value. Proceedings of the National Academy of Sciences. 116(26). 13061–13066. 80 indexed citations
8.
Gao, Xiaoxue, Hongbo Yu, Ignacio Sáez, et al.. (2018). Distinguishing neural correlates of context-dependent advantageous- and disadvantageous-inequity aversion. Proceedings of the National Academy of Sciences. 115(33). E7680–E7689. 74 indexed citations
9.
Seaman, Kendra Leigh, Teresa M. Karrer, Jaime J. Castrellon, et al.. (2018). Subjective value representations during effort, probability and time discounting across adulthood. Social Cognitive and Affective Neuroscience. 13(5). 449–459. 63 indexed citations
10.
Castrellon, Jaime J., Kendra Leigh Seaman, Jennifer L. Crawford, et al.. (2018). Individual Differences in Dopamine Are Associated with Reward Discounting in Clinical Groups But Not in Healthy Adults. Journal of Neuroscience. 39(2). 321–332. 25 indexed citations
11.
Lui, Ming & Ming Hsu. (2018). Viewing sexual images is associated with reduced physiological arousal response to gambling loss. PLoS ONE. 13(4). e0195748–e0195748. 4 indexed citations
12.
Kobayashi, Kenji & Ming Hsu. (2017). Neural Mechanisms of Updating under Reducible and Irreducible Uncertainty. Journal of Neuroscience. 37(29). 6972–6982. 33 indexed citations
13.
Seaman, Kendra Leigh, Marissa A. Gorlick, Kruti M. Vekaria, et al.. (2016). Adult age differences in decision making across domains: Increased discounting of social and health-related rewards.. Psychology and Aging. 31(7). 737–746. 62 indexed citations
14.
Chark, Robin, et al.. (2016). Computational substrates of social norm enforcement by unaffected third parties. NeuroImage. 129. 95–104. 33 indexed citations
15.
García-García, Manuel, Ming Hsu, & William Hedgcock. (2015). Advancing Connections Between Neuromarketing Academics and Industry. ACR North American Advances. 1 indexed citations
16.
Bertoux, Maxime, Florián Cova, Mathias Pessiglione, et al.. (2014). Behavioral variant frontotemporal dementia patients do not succumb to the Allais paradox. Frontiers in Neuroscience. 8. 287–287. 5 indexed citations
17.
Sáez, Ignacio, et al.. (2014). From genes to behavior: placing cognitive models in the context of biological pathways. Frontiers in Neuroscience. 8. 336–336. 9 indexed citations
18.
Hsu, Ming, Ian Krajbich, Chen Zhao, & Colin F. Camerer. (2009). Neural Response to Reward Anticipation under Risk Is Nonlinear in Probabilities. Journal of Neuroscience. 29(7). 2231–2237. 184 indexed citations
19.
Hsu, Ming, et al.. (2008). The Right and the Good: Distributive Justice and Neural Encoding of Equity and Efficiency. Science. 320(5879). 1092–1095. 235 indexed citations
20.
Hsu, Ming. (2004). Ambiguity Aversion in the Brain. 1 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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