Mingzhou Ding

21.8k total citations · 4 hit papers
226 papers, 15.2k citations indexed

About

Mingzhou Ding is a scholar working on Cognitive Neuroscience, Statistical and Nonlinear Physics and Computer Networks and Communications. According to data from OpenAlex, Mingzhou Ding has authored 226 papers receiving a total of 15.2k indexed citations (citations by other indexed papers that have themselves been cited), including 158 papers in Cognitive Neuroscience, 48 papers in Statistical and Nonlinear Physics and 30 papers in Computer Networks and Communications. Recurrent topics in Mingzhou Ding's work include Neural dynamics and brain function (118 papers), Functional Brain Connectivity Studies (59 papers) and EEG and Brain-Computer Interfaces (51 papers). Mingzhou Ding is often cited by papers focused on Neural dynamics and brain function (118 papers), Functional Brain Connectivity Studies (59 papers) and EEG and Brain-Computer Interfaces (51 papers). Mingzhou Ding collaborates with scholars based in United States, China and India. Mingzhou Ding's co-authors include Steven L. Bressler, Govindan Rangarajan, Mukeshwar Dhamala, Yonghong Chen, J. A. Scott Kelso, Wilson Truccolo, Viktor Jirsa, Edward Ott, Richard Nakamura and Celso Grebogi and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and Journal of Neuroscience.

In The Last Decade

Mingzhou Ding

221 papers receiving 14.8k citations

Hit Papers

Beta oscillations in a la... 2001 2026 2009 2017 2004 2001 2008 2017 250 500 750

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Mingzhou Ding 9.9k 3.1k 2.0k 1.6k 1.1k 226 15.2k
Jacques Martinerie 12.9k 1.3× 1.3k 0.4× 1.1k 0.6× 2.6k 1.7× 924 0.8× 101 14.8k
Viktor Jirsa 13.3k 1.4× 2.1k 0.7× 1.7k 0.9× 2.4k 1.5× 882 0.8× 274 15.4k
Dante R. Chialvo 7.3k 0.7× 2.6k 0.8× 1.4k 0.7× 1.6k 1.0× 713 0.7× 129 11.9k
Leon Glass 7.9k 0.8× 5.5k 1.8× 5.2k 2.6× 1.5k 1.0× 709 0.6× 232 26.6k
Klaus Lehnertz 12.2k 1.2× 1.9k 0.6× 1.4k 0.7× 2.8k 1.8× 644 0.6× 213 15.1k
Gustavo Deco 20.0k 2.0× 1.7k 0.5× 1.2k 0.6× 3.5k 2.2× 2.4k 2.2× 529 24.0k
Michael Breakspear 16.3k 1.7× 1.4k 0.5× 1.1k 0.5× 2.1k 1.4× 3.2k 2.9× 258 20.7k
Henning U. Voss 3.8k 0.4× 1.0k 0.3× 854 0.4× 1.1k 0.7× 913 0.8× 138 10.2k
Mario Chávez 3.2k 0.3× 5.3k 1.7× 3.1k 1.6× 754 0.5× 658 0.6× 103 12.3k
Walter J. Freeman 7.8k 0.8× 1.6k 0.5× 961 0.5× 2.8k 1.8× 702 0.6× 198 11.4k

Countries citing papers authored by Mingzhou Ding

Since Specialization
Citations

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

Fields of papers citing papers by Mingzhou Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mingzhou Ding

This figure shows the co-authorship network connecting the top 25 collaborators of Mingzhou Ding. A scholar is included among the top collaborators of Mingzhou Ding 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 Mingzhou Ding. Mingzhou Ding 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.
Yan, Xuedong, et al.. (2025). Decoding Visual Spatial Attention Control. eNeuro. 12(3). ENEURO.0512–24.2025.
2.
Zhao, Qing, et al.. (2023). Imaging the neural substrate of trigeminal neuralgia pain using deep learning. Frontiers in Human Neuroscience. 17. 1144159–1144159. 5 indexed citations
3.
Mangun, George R., et al.. (2022). Top-down control of the left visual field bias in cued visual spatial attention. Cerebral Cortex. 33(9). 5097–5107. 4 indexed citations
4.
Keil, Andreas, Edward M. Bernat, Michael X Cohen, et al.. (2022). Recommendations and publication guidelines for studies using frequency domain and time‐frequency domain analyses of neural time series. Psychophysiology. 59(5). e14052–e14052. 68 indexed citations
5.
Liu, Yuelu, et al.. (2021). Decoding Neural Representations of Affective Scenes in Retinotopic Visual Cortex. Cerebral Cortex. 31(6). 3047–3063. 22 indexed citations
6.
Clancy, Kevin J., et al.. (2021). Transcranial stimulation of alpha oscillations up-regulates the default mode network. Proceedings of the National Academy of Sciences. 119(1). 43 indexed citations
7.
Hong, Xiangfei, Fuzhong Yang, Jijun Wang, et al.. (2021). Conflict Processing in Schizophrenia: Dissociable neural mechanisms revealed by the N2 and frontal midline theta. Neuropsychologia. 155. 107791–107791. 4 indexed citations
8.
Liu, Yuelu, et al.. (2020). Fear conditioning prompts sparser representations of conditioned threat in primary visual cortex. Social Cognitive and Affective Neuroscience. 15(9). 950–964. 13 indexed citations
9.
Clancy, Kevin J., et al.. (2020). Posttraumatic Stress Disorder Is Associated with α Dysrhythmia across the Visual Cortex and the Default Mode Network. eNeuro. 7(4). ENEURO.0053–20.2020. 30 indexed citations
10.
Arnold, Thomas, et al.. (2020). Functional Connectome Analyses Reveal the Human Olfactory Network Organization. eNeuro. 7(4). ENEURO.0551–19.2020. 28 indexed citations
11.
Kluger, Benzi M., Qing Zhao, Jared J. Tanner, et al.. (2019). Structural brain correlates of fatigue in older adults with and without Parkinson's disease. NeuroImage Clinical. 22. 101730–101730. 29 indexed citations
12.
Zhang, Yi, Qiang Li, Xiaotong Wen, et al.. (2016). Granger causality reveals a dominant role of memory circuit in chronic opioid dependence. Addiction Biology. 22(4). 1068–1080. 26 indexed citations
13.
Huang, Haiqing & Mingzhou Ding. (2015). Linking Functional Connectivity and Structural Connectivity Quantitatively: A Comparison of Methods. Brain Connectivity. 6(2). 99–108. 62 indexed citations
14.
Ding, Mingzhou & Dennis L. Glanzman. (2011). The dynamic brain : an exploration of neuronal variability and its functional significance. Oxford University Press eBooks. 13 indexed citations
15.
Jiao, Qing, Jun Ding, Guangming Lu, et al.. (2011). Increased Activity Imbalance in Fronto-Subcortical Circuits in Adolescents with Major Depression. PLoS ONE. 6(9). e25159–e25159. 67 indexed citations
16.
Guo, Shuixia, Jianhua Wu, Mingzhou Ding, & Jianfeng Feng. (2008). Uncovering Interactions in the Frequency Domain. PLoS Computational Biology. 4(5). e1000087–e1000087. 56 indexed citations
17.
Şeref, Onur, Claudio Cifarelli, O. Erhun Kundakcioglu, Pãnos M. Pardalos, & Mingzhou Ding. (2007). Detecting Categorical Discrimination in a Visuomotor Task Using Selective Support Vector Machines.. 580–590.
18.
Rangarajan, G. & Mingzhou Ding. (2003). Processes with long-range correlations : theory and applications. Springer eBooks. 88 indexed citations
19.
Ding, Mingzhou. (1998). Long Memory Processes (1/f^α type) in Human Coordination. APS March Meeting Abstracts. 9 indexed citations
20.
Ding, Mingzhou, Celso Grebogi, Edward Ott, Timothy Sauer, & James A. Yorke. (1993). Plateau onset for correlation dimension: When does it occur?. Physical Review Letters. 70(25). 3872–3875. 126 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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