Guoshi Li

662 total citations
21 papers, 354 citations indexed

About

Guoshi Li is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Sensory Systems. According to data from OpenAlex, Guoshi Li has authored 21 papers receiving a total of 354 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Cognitive Neuroscience, 9 papers in Cellular and Molecular Neuroscience and 7 papers in Sensory Systems. Recurrent topics in Guoshi Li's work include Neural dynamics and brain function (11 papers), Functional Brain Connectivity Studies (7 papers) and Olfactory and Sensory Function Studies (7 papers). Guoshi Li is often cited by papers focused on Neural dynamics and brain function (11 papers), Functional Brain Connectivity Studies (7 papers) and Olfactory and Sensory Function Studies (7 papers). Guoshi Li collaborates with scholars based in United States, China and Puerto Rico. Guoshi Li's co-authors include Thomas A. Cleland, Satish S. Nair, Gregory J. Quirk, Pew‐Thian Yap, Craig S. Henriquez, Flavio Frӧhlich, Dinggang Shen, Denis Paré, Taiju Amano and Y. Chen and has published in prestigious journals such as Journal of Neuroscience, Journal of Neurophysiology and Human Brain Mapping.

In The Last Decade

Guoshi Li

21 papers receiving 351 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Guoshi Li United States 10 250 177 91 39 36 21 354
Chunying Jia United States 7 258 1.0× 252 1.4× 31 0.3× 27 0.7× 31 0.9× 13 503
Brian Theyel United States 6 314 1.3× 219 1.2× 32 0.4× 17 0.4× 41 1.1× 12 443
Linda M. Amarante United States 6 303 1.2× 209 1.2× 27 0.3× 13 0.3× 63 1.8× 7 443
István Kondákor Hungary 19 642 2.6× 312 1.8× 35 0.4× 42 1.1× 12 0.3× 30 789
Stephanie M. Prince United States 3 275 1.1× 264 1.5× 39 0.4× 31 0.8× 8 0.2× 6 534
Alyse M. Thomas United States 8 225 0.9× 274 1.5× 31 0.3× 16 0.4× 30 0.8× 9 545
Carmen Varela United States 11 496 2.0× 420 2.4× 31 0.3× 25 0.6× 27 0.8× 18 604
James Cavanaugh United States 6 636 2.5× 309 1.7× 50 0.5× 56 1.4× 5 0.1× 7 750
Carina R. Oehrn Germany 11 292 1.2× 195 1.1× 16 0.2× 34 0.9× 11 0.3× 26 553

Countries citing papers authored by Guoshi Li

Since Specialization
Citations

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

Fields of papers citing papers by Guoshi Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guoshi Li

This figure shows the co-authorship network connecting the top 25 collaborators of Guoshi Li. A scholar is included among the top collaborators of Guoshi Li 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 Guoshi Li. Guoshi Li 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, Guoshi, Li‐Ming Hsu, Ye Wu, et al.. (2025). Revealing excitation-inhibition imbalance in Alzheimer’s disease using multiscale neural model inversion of resting-state functional MRI. Communications Medicine. 5(1). 17–17. 6 indexed citations
2.
Johnson, Benjamin C., Guoshi Li, Izumi Fukunaga, et al.. (2024). Coherent olfactory bulb gamma oscillations arise from coupling independent columnar oscillators. Journal of Neurophysiology. 131(3). 492–508. 2 indexed citations
3.
Li, Guoshi, et al.. (2023). Accumulation of network redundancy marks the early stage of Alzheimer's disease. Human Brain Mapping. 44(8). 2993–3006. 11 indexed citations
4.
Zhou, Zhen, Guoshi Li, Weiyan Yin, et al.. (2023). Mapping the evolution of regional brain network efficiency and its association with cognitive abilities during the first twenty-eight months of life. Developmental Cognitive Neuroscience. 63. 101284–101284. 5 indexed citations
5.
Li, Guoshi & Pew‐Thian Yap. (2022). From descriptive connectome to mechanistic connectome: Generative modeling in functional magnetic resonance imaging analysis. Frontiers in Human Neuroscience. 16. 940842–940842. 7 indexed citations
6.
Ma, Lei, Chunfeng Lian, Daeseung Kim, et al.. (2022). Bidirectional prediction of facial and bony shapes for orthognathic surgical planning. Medical Image Analysis. 83. 102644–102644. 10 indexed citations
7.
Li, Guoshi, Yujie Liu, Yanting Zheng, et al.. (2021). Multiscale neural modeling of resting-state fMRI reveals executive-limbic malfunction as a core mechanism in major depressive disorder. NeuroImage Clinical. 31. 102758–102758. 18 indexed citations
8.
Li, Guoshi, Craig S. Henriquez, & Flavio Frӧhlich. (2020). Unified thalamic model generates multiple distinct oscillations with state-dependent entrainment by stimulation. UNC Libraries. 2 indexed citations
9.
Li, Guoshi & Thomas A. Cleland. (2020). A coupled-oscillator model of olfactory bulb gamma oscillations. UNC Libraries. 2 indexed citations
10.
Li, Guoshi, Yujie Liu, Yanting Zheng, et al.. (2019). Large‐scale dynamic causal modeling of major depressive disorder based on resting‐state functional magnetic resonance imaging. Human Brain Mapping. 41(4). 865–881. 58 indexed citations
11.
Li, Guoshi, Yujie Liu, Yanting Zheng, et al.. (2019). Identification of Abnormal Circuit Dynamics in Major Depressive Disorder via Multiscale Neural Modeling of Resting-State fMRI. Lecture notes in computer science. 11766. 682–690. 3 indexed citations
12.
Li, Guoshi & Thomas A. Cleland. (2018). Generative Biophysical Modeling of Dynamical Networks in the Olfactory System. Methods in molecular biology. 1820. 265–288. 3 indexed citations
13.
Li, Guoshi, Craig S. Henriquez, & Flavio Frӧhlich. (2018). Rhythmic modulation of thalamic oscillations depends on intrinsic cellular dynamics. Journal of Neural Engineering. 16(1). 16013–16013. 7 indexed citations
14.
Li, Guoshi & Thomas A. Cleland. (2017). A coupled-oscillator model of olfactory bulb gamma oscillations. PLoS Computational Biology. 13(11). e1005760–e1005760. 25 indexed citations
15.
Li, Guoshi, Craig S. Henriquez, & Flavio Frӧhlich. (2017). Unified thalamic model generates multiple distinct oscillations with state-dependent entrainment by stimulation. PLoS Computational Biology. 13(10). e1005797–e1005797. 25 indexed citations
16.
Li, Guoshi & Thomas A. Cleland. (2013). A Two-Layer Biophysical Model of Cholinergic Neuromodulation in Olfactory Bulb. Journal of Neuroscience. 33(7). 3037–3058. 51 indexed citations
17.
Sethupathy, Praveen, Daniel B. Rubin, Guoshi Li, & Thomas A. Cleland. (2013). A model of electrophysiological heterogeneity in periglomerular cells. Frontiers in Computational Neuroscience. 7. 49–49. 8 indexed citations
18.
Li, Guoshi, Taiju Amano, Denis Paré, & Satish S. Nair. (2011). Impact of infralimbic inputs on intercalated amygdala neurons: A biophysical modeling study. Learning & Memory. 18(4). 226–240. 31 indexed citations
19.
Li, Guoshi, Satish S. Nair, & Gregory J. Quirk. (2008). A Biologically Realistic Network Model of Acquisition and Extinction of Conditioned Fear Associations in Lateral Amygdala Neurons. Journal of Neurophysiology. 101(3). 1629–1646. 65 indexed citations
20.
Li, Guoshi, Gregory J. Quirk, & Satish S. Nair. (2007). Modeling Acquisition and Extinction of Conditioned Fear in LA Neurons using Learning Algorithm. Proceedings of the ... American Control Conference. 552–557. 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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