Taomian Mi

1.0k total citations
20 papers, 550 citations indexed

About

Taomian Mi is a scholar working on Neurology, Cognitive Neuroscience and Neurology. According to data from OpenAlex, Taomian Mi has authored 20 papers receiving a total of 550 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Neurology, 10 papers in Cognitive Neuroscience and 6 papers in Neurology. Recurrent topics in Taomian Mi's work include Functional Brain Connectivity Studies (8 papers), Parkinson's Disease Mechanisms and Treatments (7 papers) and Neurological disorders and treatments (6 papers). Taomian Mi is often cited by papers focused on Functional Brain Connectivity Studies (8 papers), Parkinson's Disease Mechanisms and Treatments (7 papers) and Neurological disorders and treatments (6 papers). Taomian Mi collaborates with scholars based in China, Canada and United States. Taomian Mi's co-authors include Piu Chan, Aiping Liu, Martin J. McKeown, Piu Chan, Linlin Gao, Saurabh Garg, Tao Wu, Irene Litvan, Elizabeth Slow and Ronald B. Postuma and has published in prestigious journals such as Neurology, Scientific Reports and Movement Disorders.

In The Last Decade

Taomian Mi

19 papers receiving 548 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Taomian Mi China 11 331 167 131 87 73 20 550
F. Carrillo Spain 12 428 1.3× 177 1.1× 128 1.0× 57 0.7× 34 0.5× 23 621
Scott A. Norris United States 15 275 0.8× 123 0.7× 201 1.5× 69 0.8× 42 0.6× 44 526
Brendan P. Major Australia 14 186 0.6× 183 1.1× 124 0.9× 79 0.9× 73 1.0× 36 517
Florian Amtage Germany 14 354 1.1× 187 1.1× 212 1.6× 75 0.9× 147 2.0× 23 811
Juan C. Cortés United States 8 217 0.7× 121 0.7× 135 1.0× 34 0.4× 106 1.5× 8 499
Nicoló Gabriele Pozzi Italy 16 624 1.9× 165 1.0× 126 1.0× 37 0.4× 98 1.3× 35 820
Mutsumi Iijima Japan 16 387 1.2× 76 0.5× 117 0.9× 21 0.2× 71 1.0× 55 696
Maria Rubega Italy 15 100 0.3× 72 0.4× 311 2.4× 66 0.8× 59 0.8× 40 561
Jee Hyun Ham South Korea 18 522 1.6× 78 0.5× 151 1.2× 93 1.1× 44 0.6× 28 753
Gonzalo J. Revuelta United States 12 227 0.7× 126 0.8× 67 0.5× 27 0.3× 38 0.5× 33 369

Countries citing papers authored by Taomian Mi

Since Specialization
Citations

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

Fields of papers citing papers by Taomian Mi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Taomian Mi

This figure shows the co-authorship network connecting the top 25 collaborators of Taomian Mi. A scholar is included among the top collaborators of Taomian Mi 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 Taomian Mi. Taomian Mi 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.
Liu, Aiping, Yu Li, Taomian Mi, et al.. (2025). High-Order Graphical Topology Analysis of Brain Functional Connectivity Networks Using fMRI. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 33. 1611–1620.
2.
Liu, Aiping, Yu Li, Taomian Mi, et al.. (2023). Homogeneous-Multiset-CCA-Based Brain Covariation and Contravariance Connectivity Network Modeling. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 31. 3556–3565. 1 indexed citations
3.
4.
Mi, Taomian, Wei Zhang, Martin J. McKeown, & Piu Chan. (2021). Impaired Formation and Expression of Goal-Directed and Habitual Control in Parkinson’s Disease. Frontiers in Aging Neuroscience. 13. 734807–734807. 6 indexed citations
5.
Mi, Taomian, et al.. (2021). Altered Functional Segregated Sensorimotor, Associative, and Limbic Cortical-Striatal Connections in Parkinson's Disease: An fMRI Investigation. Frontiers in Neurology. 12. 720293–720293. 8 indexed citations
6.
Li, Yu, Aiping Liu, Taomian Mi, et al.. (2021). Striatal Subdivisions Estimated via Deep Embedded Clustering With Application to Parkinson's Disease. IEEE Journal of Biomedical and Health Informatics. 25(9). 3564–3575. 9 indexed citations
7.
Liu, Aiping, Yu Li, Soojin Lee, et al.. (2021). Galvanic Vestibular Stimulation Improves Subnetwork Interactions in Parkinson’s Disease. Journal of Healthcare Engineering. 2021. 1–11. 8 indexed citations
8.
Mi, Taomian, et al.. (2020). Gait variability is sensitive to detect Parkinson’s disease patients at high fall risk. International Journal of Neuroscience. 132(9). 888–893. 25 indexed citations
9.
Mi, Taomian, Saurabh Garg, Fang Ba, et al.. (2020). Repetitive transcranial magnetic stimulation improves Parkinson’s freezing of gait via normalizing brain connectivity. npj Parkinson s Disease. 6(1). 16–16. 37 indexed citations
10.
11.
Mi, Taomian, Saurabh Garg, Fang Ba, et al.. (2019). High-frequency rTMS over the supplementary motor area improves freezing of gait in Parkinson's disease: a randomized controlled trial. Parkinsonism & Related Disorders. 68. 85–90. 52 indexed citations
12.
Ma, Jinghong, Linlin Gao, Taomian Mi, et al.. (2019). Repetitive Transcranial Magnetic Stimulation Does Not Improve the Sequence Effect in Freezing of Gait. Parkinson s Disease. 2019. 1–8. 23 indexed citations
13.
Cai, Jiayue, Aiping Liu, Taomian Mi, et al.. (2018). Dynamic Graph Theoretical Analysis of Functional Connectivity in Parkinson's Disease: The Importance of Fiedler Value. IEEE Journal of Biomedical and Health Informatics. 23(4). 1720–1729. 45 indexed citations
14.
Gu, Zhuqin, et al.. (2018). Validation of the utility of the Brief Smell Identification Test in Chinese patients with Parkinson’s disease. Journal of Clinical Neuroscience. 60. 68–72. 13 indexed citations
15.
Liu, Aiping, Taomian Mi, Xun Chen, et al.. (2018). Decreased subregional specificity of the putamen in Parkinson's Disease revealed by dynamic connectivity-derived parcellation. NeuroImage Clinical. 20. 1163–1175. 17 indexed citations
16.
Postuma, Ronald B., Werner Poewe, Irene Litvan, et al.. (2018). Validation of the MDS Clinical Diagnostic Criteria for Parkinson’s Disease (S3.001). Neurology. 90(15_supplement). 1 indexed citations
17.
Postuma, Ronald B., Werner Poewe, Irene Litvan, et al.. (2018). Validation of the MDS clinical diagnostic criteria for Parkinson's disease. Movement Disorders. 33(10). 1601–1608. 180 indexed citations
18.
Mi, Taomian, Shanshan Mei, Peipeng Liang, et al.. (2017). Altered resting-state brain activity in Parkinson’s disease patients with freezing of gait. Scientific Reports. 7(1). 16711–16711. 41 indexed citations
19.
Mi, Taomian, Wei Mao, Yanning Cai, et al.. (2017). Primary familial brain calcifications linked with a novel SLC20A2 gene mutation in a Chinese family. Journal of Neurogenetics. 31(3). 149–152. 3 indexed citations
20.
Mi, Taomian, Fei Yu, Xunming Ji, Yongxin Sun, & Dongmei Qu. (2016). The Interventional Effect of Remote Ischemic Preconditioning on Cerebral Small Vessel Disease: A Pilot Randomized Clinical Trial. European Neurology. 76(1-2). 28–34. 45 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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