Ming Bo Cai

1.0k total citations · 1 hit paper
17 papers, 481 citations indexed

About

Ming Bo Cai is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Artificial Intelligence. According to data from OpenAlex, Ming Bo Cai has authored 17 papers receiving a total of 481 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Cognitive Neuroscience, 5 papers in Experimental and Cognitive Psychology and 3 papers in Artificial Intelligence. Recurrent topics in Ming Bo Cai's work include Neural dynamics and brain function (7 papers), Functional Brain Connectivity Studies (7 papers) and Visual perception and processing mechanisms (3 papers). Ming Bo Cai is often cited by papers focused on Neural dynamics and brain function (7 papers), Functional Brain Connectivity Studies (7 papers) and Visual perception and processing mechanisms (3 papers). Ming Bo Cai collaborates with scholars based in United States, China and Japan. Ming Bo Cai's co-authors include Yael Niv, Nicolas W. Schuck, Robert C. Wilson, David M. Eagleman, Chess Stetson, Wei Ji, Jonathan W. Pillow, Eric Eaton, Boyu Wang and Cameron T. Ellis and has published in prestigious journals such as Neuron, Neuropsychologia and Frontiers in Psychology.

In The Last Decade

Ming Bo Cai

15 papers receiving 473 citations

Hit Papers

align trajectories

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.

Human Orbitofrontal Cortex Represents a Cognitive Map of State Space

2016 328 citations Nicolas W. Schuck, Ming Bo Cai et al. Neuron profile →

Peers

Ming Bo Cai

CN

ECP

AI

CMN

SP

Seongmin A. Park United States

Mona M. Garvert Germany

Alon Baram United Kingdom

Vikranth R. Bejjanki United States

Braden A. Purcell United States

Vincent Adam United Kingdom

Travis Meyer United States

Sander Bosch Netherlands

Thomas C. Sprague United States

Kinjan Parikh United States

Seongmin A. Park United States

Ming Bo Cai

329 ×0.8

CN

67 ×0.8

ECP

77 ×1.1

AI

43 ×0.7

CMN

60 ×1.6

SP

Citations per year, relative to Ming Bo Cai Ming Bo Cai (= 1×) peers Seongmin A. Park

Countries citing papers authored by Ming Bo Cai

Since Specialization

Citations

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

Fields of papers citing papers by Ming Bo Cai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming Bo Cai

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

All Works

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17 of 17 papers shown

1.

Song, Mingyu, et al.. (2022). Humans combine value learning and hypothesis testing strategically in multi-dimensional probabilistic reward learning. PLoS Computational Biology. 18(11). e1010699–e1010699. 5 indexed citations

2.

Song, Mingyu, Yael Niv, & Ming Bo Cai. (2021). Using Recurrent Neural Networks to Understand Human Reward Learning. eScholarship (California Digital Library). 43(43). 3 indexed citations

3.

Song, Mingyu, Yael Niv, & Ming Bo Cai. (2020). Learning what is relevant for rewards via value-based serial hypothesis testing.. Cognitive Science. 2 indexed citations

4.

Cai, Ming Bo, Michael Shvartsman, Anqi Wu, Hejia Zhang, & Xia Zhu. (2020). Incorporating structured assumptions with probabilistic graphical models in fMRI data analysis. Neuropsychologia. 144. 107500–107500. 5 indexed citations

5.

Ellis, Cameron T., Christopher Baldassano, Anna C. Schapiro, Ming Bo Cai, & Jonathan D. Cohen. (2020). Facilitating open-science with realistic fMRI simulation: validation and application. PeerJ. 8. e8564–e8564. 14 indexed citations

6.

Wang, Boyu, et al.. (2019). Transfer Learning via Minimizing the Performance Gap Between Domains. Neural Information Processing Systems. 32. 10644–10654. 18 indexed citations

7.

Cai, Ming Bo, Nicolas W. Schuck, Jonathan W. Pillow, & Yael Niv. (2019). Representational structure or task structure? Bias in neural representational similarity analysis and a Bayesian method for reducing bias. PLoS Computational Biology. 15(5). e1006299–e1006299. 28 indexed citations

8.

Song, Mingyu, Ming Bo Cai, & Yael Niv. (2019). Learning what is relevant for rewards via serial hypothesis testing.

9.

Maior, Horia A., et al.. (2019). fNIRS and Neurocinematics. Lincoln Repository (University of Lincoln). 1–6. 3 indexed citations

10.

Cai, Ming Bo, Nicolas W. Schuck, Michael Anderson, Jonathan W. Pillow, & Yael Niv. (2017). Should you trust your RSA result? A Bayesian method for reducing bias in neural representational similarity analysis.. Journal of Vision. 17(10). 571–571.

11.

Schuck, Nicolas W., Ming Bo Cai, Robert C. Wilson, & Yael Niv. (2016). Human Orbitofrontal Cortex Represents a Cognitive Map of State Space. Neuron. 91(6). 1402–1412. 328 indexed citations breakdown →

12.

Baldwin, Philip R., Ming Bo Cai, Ricky R. Savjani, et al.. (2016). Real time functional MRI training to decrease motion in imaging studies: Lack of significant improvement. Bulletin of the Menninger Clinic. 80(4). 348–356. 2 indexed citations

13.

Cai, Ming Bo & David M. Eagleman. (2015). Duration estimates within a modality are integrated sub-optimally. Frontiers in Psychology. 6. 1041–1041. 7 indexed citations

14.

Cai, Ming Bo, David M. Eagleman, & Wei Ji. (2015). Perceived duration is reduced by repetition but not by high-level expectation. Journal of Vision. 15(13). 19–19. 27 indexed citations

15.

Cai, Ming Bo, et al.. (2015). Driver Fatigue Detection System Based on DM3730. The Open Automation and Control Systems Journal. 7(1). 1191–1196. 2 indexed citations

16.

Cai, Ming Bo, Chess Stetson, & David M. Eagleman. (2012). A Neural Model for Temporal Order Judgments and Their Active Recalibration: A Common Mechanism for Space and Time?. Frontiers in Psychology. 3. 470–470. 31 indexed citations

17.

Cai, Ming Bo, et al.. (2010). A NOVEL APPROACH TO ACTIVATION DETECTION IN fMRI BASED ON EMPIRICAL MODE DECOMPOSITION. Journal of Integrative Neuroscience. 9(4). 407–427. 6 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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