Jinggui Song

639 total citations
35 papers, 438 citations indexed

About

Jinggui Song is a scholar working on Neurology, Cellular and Molecular Neuroscience and Molecular Biology. According to data from OpenAlex, Jinggui Song has authored 35 papers receiving a total of 438 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Neurology, 11 papers in Cellular and Molecular Neuroscience and 10 papers in Molecular Biology. Recurrent topics in Jinggui Song's work include Neuroinflammation and Neurodegeneration Mechanisms (8 papers), Neuroscience and Neuropharmacology Research (7 papers) and Neurogenesis and neuroplasticity mechanisms (7 papers). Jinggui Song is often cited by papers focused on Neuroinflammation and Neurodegeneration Mechanisms (8 papers), Neuroscience and Neuropharmacology Research (7 papers) and Neurogenesis and neuroplasticity mechanisms (7 papers). Jinggui Song collaborates with scholars based in China, United States and Malaysia. Jinggui Song's co-authors include Wenqiang Li, Zhaohui Zhang, Yusheng Li, Yuming Xu, Ping Zhang, Zhaohui Zhang, Lina Wu, Lin Zhao, Ping Zhang and Fuping Zhang and has published in prestigious journals such as Journal of Neuroscience, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Jinggui Song

32 papers receiving 430 citations

Peers

Jinggui Song

NEURO

CMN

EPIDE

Sanrong Wang China

Chunfeng Tan United States

Ruslan Kuts Israel

Claudia Espinosa‐García United States

Pedro Porto Alegre Baptista Brazil

John Kealy Ireland

Victor Li United States

Shunmei Lu China

Victor Zibara Lebanon

Sanrong Wang China

Jinggui Song

187 ×1.1

NEURO

79 ×0.7

73 ×0.9

CMN

32 ×0.5

50 ×0.8

EPIDE

Citations per year, relative to Jinggui Song Jinggui Song (= 1×) peers Sanrong Wang

Countries citing papers authored by Jinggui Song

Since Specialization

Citations

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

Fields of papers citing papers by Jinggui Song

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jinggui Song

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

All Works

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20 of 20 papers shown

Hao, Lei, Fuping Zhang, M. Tao, et al.. (2025). Overexpression of S100B promotes depressive-like behaviors in stroke-induced rats by modulating the PI3K/AKT/NF-κB pathway. Behavioural Brain Research. 488. 115597–115597.

Liu, Huanhuan, Yuxin Chen, Fuping Zhang, et al.. (2025). rTMS ameliorates CUMS-induced anxiety-depression-like behaviour and cognitive dysfunction in rats by modulating the COX-2/PGE2 signalling pathway. Journal of Psychiatric Research. 186. 116–128. 3 indexed citations

Zhao, Zongya, Mingjie Zhu, Junming Wang, et al.. (2025). Predicting Treatment Response of Repetitive Transcranial Magnetic Stimulation in Major Depressive Disorder Using an Explainable Machine Learning Model Based on Electroencephalography and Clinical Features. Biological Psychiatry Cognitive Neuroscience and Neuroimaging. 10(6). 656–665. 2 indexed citations

Zhang, Xinyue, Huanhuan Liu, Yunfei Zhang, et al.. (2025). HMGB1/RAGE signaling mediates the activation of microglia and participates in depressive-like behaviors and cognitive deficits in rats after ischemia-reperfusion. Behavioural Brain Research. 492. 115662–115662.

Zhao, Zongya, Junming Wang, Yongtao Xu, et al.. (2024). Common and differential EEG microstate of major depressive disorder patients with and without response to rTMS treatment. Journal of Affective Disorders. 367. 777–787. 11 indexed citations

Liu, Huanhuan, Yunfei Zhang, Kun Li, et al.. (2024). CRHR1 antagonist alleviated depression-like behavior by downregulating p62 in a rat model of post-stroke depression. Experimental Neurology. 378. 114822–114822. 9 indexed citations

Ran, Hao, Tong Zhao, Xinxin Lu, et al.. (2024). CUMS induces depressive-like behaviors and cognition impairment by activating the ERS-NLRP3 signaling pathway in mice. Journal of Affective Disorders. 369. 547–558. 4 indexed citations

Zhang, Xinyue, Lina Yang, Xuejiao Jin, et al.. (2024). DAPK1 mediates cognitive dysfunction and neuronal apoptosis in PSD rats through the ERK/CREB/BDNF signaling pathway. Behavioural Brain Research. 471. 115064–115064. 5 indexed citations

Chen, Tengfei, et al.. (2022). Repetitive Transcranial Magnetic Stimulation Improves Depression-like Behavior in Rats by Promoting Neural Stem Cell Proliferation and Differentiation. Neuroscience. 524. 1–10. 5 indexed citations

10.

Zhang, Fuping, Huanhuan Liu, Xinhui Jiang, et al.. (2022). CRS induces depression-like behavior after MCAO in rats possibly by activating p38 MAPK. Behavioural Brain Research. 437. 114104–114104. 8 indexed citations

11.

Zhang, Fuping, Le Niu, Xiaonan Wang, et al.. (2022). High-frequency repetitive transcranial magnetic stimulation mitigates depression-like behaviors in CUMS-induced rats via FGF2/FGFR1/p-ERK signaling pathway. Brain Research Bulletin. 183. 94–103. 12 indexed citations

12.

Zhang, Feng, et al.. (2022). White matter hyperintensities and post-stroke depression: A systematic review and meta-analysis. Journal of Affective Disorders. 320. 370–380. 10 indexed citations

13.

Yang, Yongfeng, Xue Li, Yue Cui, et al.. (2022). Reduced Gray Matter Volume in Orbitofrontal Cortex Across Schizophrenia, Major Depressive Disorder, and Bipolar Disorder: A Comparative Imaging Study. Frontiers in Neuroscience. 16. 919272–919272. 21 indexed citations

14.

Hou, Xiaoli, Huanhuan Liu, Xinhui Jiang, et al.. (2021). CDDO-Im exerts antidepressant-like effects via the Nrf2/ARE pathway in a rat model of post-stroke depression. Brain Research Bulletin. 173. 74–81. 14 indexed citations

15.

Li, Xiaodan, et al.. (2019). Decreased Npas4 expression in patients with post-stroke depression. SHILAP Revista de lepidopterología. 7(2). 101–108. 3 indexed citations

16.

Zhao, Lin, Xiaodan Li, Juan Li, et al.. (2018). rTMS ameliorated depressive-like behaviors by restoring HPA axis balance and prohibiting hippocampal neuron apoptosis in a rat model of depression. Psychiatry Research. 269. 126–133. 47 indexed citations

17.

Zhao, Lin, et al.. (2016). Relationship between 5-HTTLPR polymorphism and post-stroke depression. Genetics and Molecular Research. 15(1). 18 indexed citations

18.

Zhang, Zhaohui, et al.. (2013). Hippocampal expression of aryl hydrocarbon receptor nuclear translocator 2 and neuronal PAS domain protein 4 in a rat model of depression. Neurological Sciences. 35(2). 277–282. 27 indexed citations

19.

Zhang, Zhaohui, et al.. (2012). Aberrant Apolipoprotein E Expression and Cognitive Dysfunction in Patients with Poststroke Depression. Genetic Testing and Molecular Biomarkers. 17(1). 47–51. 19 indexed citations

20.

Zhang, Zhaohui, Lina Wu, Jinggui Song, & Wenqiang Li. (2012). Correlations between cognitive impairment and brain-derived neurotrophic factor expression in the hippocampus of post-stroke depression rats. Molecular Medicine Reports. 6(4). 889–893. 33 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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