Qing Lü

4.2k total citations
200 papers, 2.8k citations indexed

About

Qing Lü is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Qing Lü has authored 200 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 124 papers in Cognitive Neuroscience, 60 papers in Experimental and Cognitive Psychology and 50 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Qing Lü's work include Functional Brain Connectivity Studies (122 papers), Mental Health Research Topics (53 papers) and Neural dynamics and brain function (44 papers). Qing Lü is often cited by papers focused on Functional Brain Connectivity Studies (122 papers), Mental Health Research Topics (53 papers) and Neural dynamics and brain function (44 papers). Qing Lü collaborates with scholars based in China, Bangladesh and Chile. Qing Lü's co-authors include Zhijian Yao, Rui Yan, Jiaolong Qin, Maobin Wei, Shui Tian, Hao Tang, Haiyan Liu, Jiabo Shi, Li Wang and Beijian Huang and has published in prestigious journals such as Advanced Materials, Journal of Neuroscience and SHILAP Revista de lepidopterología.

In The Last Decade

Qing Lü

182 papers receiving 2.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Qing Lü China 26 1.6k 763 673 397 294 200 2.8k
Zhiyun Jia China 27 1.4k 0.9× 476 0.6× 1.1k 1.7× 478 1.2× 307 1.0× 117 3.0k
Kazuyuki Nakagome Japan 34 1.9k 1.2× 715 0.9× 470 0.7× 843 2.1× 310 1.1× 150 3.8k
Xinyu Hu China 26 1.1k 0.7× 453 0.6× 485 0.7× 337 0.8× 413 1.4× 69 2.0k
John D. Port United States 32 778 0.5× 218 0.3× 436 0.6× 503 1.3× 575 2.0× 114 3.2k
Yang Zheng China 28 865 0.6× 367 0.5× 215 0.3× 285 0.7× 112 0.4× 122 2.3k
Crystal Cooper United States 20 1.0k 0.7× 378 0.5× 621 0.9× 314 0.8× 108 0.4× 39 1.7k
Yongqiang Yu China 27 857 0.6× 260 0.3× 458 0.7× 290 0.7× 65 0.2× 135 2.0k
Guy Leschziner United Kingdom 29 1.3k 0.8× 733 1.0× 142 0.2× 596 1.5× 138 0.5× 94 3.0k
Tommaso Scarabino Italy 28 1.2k 0.7× 240 0.3× 836 1.2× 438 1.1× 88 0.3× 85 2.7k
Fengmei Lu China 24 1.2k 0.8× 441 0.6× 476 0.7× 303 0.8× 109 0.4× 77 1.7k

Countries citing papers authored by Qing Lü

Since Specialization
Citations

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

Fields of papers citing papers by Qing Lü

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qing Lü

This figure shows the co-authorship network connecting the top 25 collaborators of Qing Lü. A scholar is included among the top collaborators of Qing Lü 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 Qing Lü. Qing Lü 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.
Wang, Ting, Xue Li, Zhongpeng Dai, et al.. (2025). Genetically Informed Disassortative Brain Morphometric Similarities Revealing Suicide Risk in Bipolar Disorder. Biological Psychiatry Cognitive Neuroscience and Neuroimaging.
2.
Xia, Yi, Jingting Yang, Xue Chen, et al.. (2025). A Coding SNP in GmPM30 Enhances Soybean Salinity Tolerance and Yield through the GmLEA1‐GmPM30‐GmLEC1 Module. Advanced Science. 12(44). e09391–e09391. 2 indexed citations
3.
Zhou, Jinjun, et al.. (2025). Meta-guided dual path convolutional neural network for depression diagnosis with functional MR images. Neurocomputing. 649. 130790–130790.
4.
5.
Shao, Junneng, Xinyi Wang, Xue Li, et al.. (2024). Individual suicide risk factors with resting-state brain functional connectivity patterns in bipolar disorder patients based on latent Dirichlet allocation model. Progress in Neuro-Psychopharmacology and Biological Psychiatry. 135. 111117–111117. 1 indexed citations
6.
Hua, Lingling, Rui Yan, Zhongpeng Dai, et al.. (2024). Aberrant high-beta band functional connectivity during reward processing in melancholic major depressive disorder: An MEG study. NeuroImage Clinical. 43. 103666–103666. 3 indexed citations
7.
8.
Dai, Zhongpeng, Wei Zhang, Hongliang Zhou, et al.. (2024). Gamma oscillations of visual cortex underlying emotion and cognition deficits associated with suicide attempt in major depressive disorder. Nature Mental Health. 2(8). 924–934. 3 indexed citations
9.
10.
Zhao, Shuai, Yu Zhang, Xiaoqin Wang, et al.. (2023). Gray matter reduction is associated with cognitive dysfunction in depressed patients comorbid with subclinical hypothyroidism. Frontiers in Aging Neuroscience. 15. 1106792–1106792. 7 indexed citations
11.
Shao, Junneng, Jiaolong Qin, Huan Wang, et al.. (2023). Capturing the Individual Deviations From Normative Models of Brain Structure for Depression Diagnosis and Treatment. Biological Psychiatry. 95(5). 403–413. 11 indexed citations
12.
Tao, Pengyu, Zhongpeng Dai, Junneng Shao, et al.. (2022). Gamma band VMPFC-PreCG.L connection variation after the onset of negative emotional stimuli can predict mania in depressive patients. Journal of Psychiatric Research. 158. 165–171. 2 indexed citations
13.
Shao, Junneng, Yujie Zhang, Xue Li, et al.. (2022). Shared and disease-sensitive dysfunction across bipolar and unipolar disorder during depressive episodes: a transdiagnostic study. Neuropsychopharmacology. 47(11). 1922–1930. 8 indexed citations
14.
Zhang, Siqi, Chunyan Cao, Andrew J. Quinn, et al.. (2021). Dynamic analysis on simultaneous iEEG-MEG data via hidden Markov model. NeuroImage. 233. 117923–117923. 13 indexed citations
15.
Tian, Shui, Rongxin Zhu, Mohammad Ridwan Chattun, et al.. (2021). Temporal dynamics alterations of spontaneous neuronal activity in anterior cingulate cortex predict suicidal risk in bipolar II patients. Brain Imaging and Behavior. 15(5). 2481–2491. 21 indexed citations
16.
Shen, Yujia, Caihong Dong, Huijing Xiang, et al.. (2021). Engineering Oxygen‐Irrelevant Radical Nanogenerator for Hypoxia‐Independent Magnetothermodynamic Tumor Nanotherapy. Small Methods. 5(4). e2001087–e2001087. 22 indexed citations
17.
Dai, Zhongpeng, Shui Tian, Rui Yan, et al.. (2020). Gradually evaluating of suicidal risk in depression by semi-supervised cluster analysis on resting-state fMRI. Brain Imaging and Behavior. 15(4). 2149–2158. 14 indexed citations
18.
Wang, Jiayu, Yujian Shi, Tao Sun, et al.. (2019). Germline mutation landscape of Chinese patients with familial breast/ovarian cancer in a panel of 22 susceptibility genes. Cancer Medicine. 8(5). 2074–2084. 17 indexed citations
19.
Bi, Kun, Shui Tian, Xiaoxue Liu, et al.. (2018). An enriched granger causal model allowing variable static anatomical constraints. NeuroImage Clinical. 21. 101592–101592. 6 indexed citations
20.
Lü, Qing, et al.. (2017). Evaluation of Cuff-Induced Skeletal Muscle Microvascular Perfusion of Lower Extremity by ASL and IVIM MRI Techniques. 311. 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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