Guohong Cui

5.2k total citations · 3 hit papers
28 papers, 2.7k citations indexed

About

Guohong Cui is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience and Molecular Biology. According to data from OpenAlex, Guohong Cui has authored 28 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Cellular and Molecular Neuroscience, 12 papers in Cognitive Neuroscience and 8 papers in Molecular Biology. Recurrent topics in Guohong Cui's work include Photoreceptor and optogenetics research (7 papers), Neuroscience and Neuropharmacology Research (7 papers) and Neural dynamics and brain function (5 papers). Guohong Cui is often cited by papers focused on Photoreceptor and optogenetics research (7 papers), Neuroscience and Neuropharmacology Research (7 papers) and Neural dynamics and brain function (5 papers). Guohong Cui collaborates with scholars based in United States, China and Portugal. Guohong Cui's co-authors include David M. Lovinger, Rui M. Costa, Michael Pham, Sang Beom Jun, Steven S. Vogel, Xin Jin, Jingheng Zhou, Yulong Li, Dayu Lin and Jiesi Feng and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Neuron.

In The Last Decade

Guohong Cui

25 papers receiving 2.6k citations

Hit Papers

Concurrent activation of striatal direct and indirect pat... 2013 2026 2017 2021 2013 2019 2020 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Guohong Cui United States 18 1.5k 1.0k 773 422 298 28 2.7k
Emily Ferenczi United States 17 2.2k 1.4× 1.4k 1.4× 662 0.9× 143 0.3× 197 0.7× 29 3.6k
Yajun Zhang United States 17 1.4k 0.9× 406 0.4× 1.0k 1.3× 133 0.3× 244 0.8× 34 2.4k
François Georges France 34 2.6k 1.7× 1.1k 1.1× 1.1k 1.4× 381 0.9× 338 1.1× 50 3.6k
Christophe D. Proulx Canada 16 1.7k 1.1× 1.0k 1.0× 707 0.9× 202 0.5× 293 1.0× 24 2.7k
Veronica A. Alvarez United States 35 3.1k 2.0× 1.1k 1.1× 2.0k 2.6× 295 0.7× 228 0.8× 65 4.5k
Tommaso Patriarchi United States 27 1.7k 1.1× 736 0.7× 1.4k 1.9× 154 0.4× 121 0.4× 48 2.8k
Sang Beom Jun South Korea 22 1.5k 1.0× 767 0.7× 468 0.6× 341 0.8× 111 0.4× 73 2.5k
Yuanye Ma China 24 738 0.5× 1.3k 1.3× 384 0.5× 96 0.2× 67 0.2× 148 2.5k
Balázs Lendvai Hungary 22 1.3k 0.9× 543 0.5× 1.0k 1.3× 74 0.2× 90 0.3× 72 2.2k
Kebreten F. Manaye United States 31 1.6k 1.1× 1.1k 1.0× 771 1.0× 847 2.0× 360 1.2× 55 3.7k

Countries citing papers authored by Guohong Cui

Since Specialization
Citations

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

Fields of papers citing papers by Guohong Cui

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guohong Cui

This figure shows the co-authorship network connecting the top 25 collaborators of Guohong Cui. A scholar is included among the top collaborators of Guohong Cui 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 Guohong Cui. Guohong Cui 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.
Li, Ji‐Cheng, Jingheng Zhou, Bo He, et al.. (2025). Differential synaptic depression mediates the therapeutic effect of deep brain stimulation. Nature Neuroscience. 28(12). 2575–2587.
2.
Papaneri, Amy B., Guohong Cui, & Shih‐Heng Chen. (2025). Next-Generation Nucleic Acid-Based Diagnostics for Viral Pathogens: Lessons Learned from the SARS-CoV-2 Pandemic. Microorganisms. 13(8). 1905–1905. 1 indexed citations
3.
Li, Chia, Claire Gao, Laura E. Mickelsen, et al.. (2025). A hypothalamic circuit that modulates feeding and parenting behaviours. Nature. 645(8082). 981–990. 4 indexed citations
4.
Feng, Jiesi, Hui Dong, Julieta E. Lischinsky, et al.. (2024). Monitoring norepinephrine release in vivo using next-generation GRABNE sensors. Neuron. 112(12). 1930–1942.e6. 29 indexed citations
5.
Zhou, Jingheng, Ji‐Cheng Li, Amy B. Papaneri, & Guohong Cui. (2023). AJ76 and UH232 as potential agents for diagnosing early-stage Parkinson's disease. Neuropharmacology. 226. 109397–109397.
6.
Oyarzabal, Esteban A., Li‐Ming Hsu, Manasmita Das, et al.. (2022). Chemogenetic stimulation of tonic locus coeruleus activity strengthens the default mode network. Science Advances. 8(17). eabm9898–eabm9898. 49 indexed citations
7.
Sciolino, Natale R., Christopher M. Mazzone, Leslie R. Wilson, et al.. (2022). Natural locus coeruleus dynamics during feeding. Science Advances. 8(33). eabn9134–eabn9134. 26 indexed citations
8.
Chao, Tzu-Hao Harry, et al.. (2022). Simultaneous recording of neuronal and vascular activity in the rodent brain using fiber-photometry. STAR Protocols. 3(3). 101497–101497. 5 indexed citations
9.
Zhang, Weiting, Tzu-Hao Harry Chao, Yue Yang, et al.. (2022). Spectral fiber photometry derives hemoglobin concentration changes for accurate measurement of fluorescent sensor activity. Cell Reports Methods. 2(7). 100243–100243. 34 indexed citations
10.
Zhou, Jingheng, et al.. (2021). Dopamine Neuron Challenge Test for early detection of Parkinson’s disease. npj Parkinson s Disease. 7(1). 116–116. 13 indexed citations
11.
Mazzone, Christopher M., Chia Li, Fangmiao Sun, et al.. (2020). High-fat food biases hypothalamic and mesolimbic expression of consummatory drives. Nature Neuroscience. 23(10). 1253–1266. 118 indexed citations
12.
Sun, Fangmiao, Jingheng Zhou, Bing Dai, et al.. (2020). Next-generation GRAB sensors for monitoring dopaminergic activity in vivo. Nature Methods. 17(11). 1156–1166. 291 indexed citations breakdown →
13.
Cui, Guohong, et al.. (2020). 食物探索の持続的調節は迷走神経介在ドーパミンニューロン活性に依存する【JST・京大機械翻訳】. Neuron. 106(5). 778–788. 14 indexed citations
14.
Li, Chunxiao, Li Cui, Yimin Yang, et al.. (2019). Gut Microbiota Differs Between Parkinson’s Disease Patients and Healthy Controls in Northeast China. Frontiers in Molecular Neuroscience. 12. 171–171. 125 indexed citations
15.
Feng, Jiesi, Changmei Zhang, Julieta E. Lischinsky, et al.. (2019). A Genetically Encoded Fluorescent Sensor for Rapid and Specific In Vivo Detection of Norepinephrine. Neuron. 102(4). 745–761.e8. 357 indexed citations breakdown →
16.
Kupferschmidt, David A., Konrad Juczewski, Guohong Cui, Kari A. Johnson, & David M. Lovinger. (2017). Parallel, but Dissociable, Processing in Discrete Corticostriatal Inputs Encodes Skill Learning. Neuron. 96(2). 476–489.e5. 120 indexed citations
17.
Cui, Guohong, Sang Beom Jun, Guoxiang Luo, et al.. (2014). Deep brain optical measurements of cell type–specific neural activity in behaving mice. Nature Protocols. 9(6). 1213–1228. 98 indexed citations
18.
Sgobio, Carmelo, David A. Kupferschmidt, Guohong Cui, et al.. (2014). Optogenetic Measurement of Presynaptic Calcium Transients Using Conditional Genetically Encoded Calcium Indicator Expression in Dopaminergic Neurons. PLoS ONE. 9(10). e111749–e111749. 20 indexed citations
19.
Cui, Guohong, Xiaowei Ren, Liuzhen Wu, Ji‐Sheng Han, & Cai‐Lian Cui. (2004). Electroacupuncture Facilitates Recovery of Male Sexual Behavior in Morphine Withdrawal Rats. Neurochemical Research. 29(2). 397–401. 17 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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