Sukbin Lim

585 total citations
14 papers, 304 citations indexed

About

Sukbin Lim is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Electrical and Electronic Engineering. According to data from OpenAlex, Sukbin Lim has authored 14 papers receiving a total of 304 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Cognitive Neuroscience, 8 papers in Cellular and Molecular Neuroscience and 7 papers in Electrical and Electronic Engineering. Recurrent topics in Sukbin Lim's work include Neural dynamics and brain function (13 papers), Advanced Memory and Neural Computing (7 papers) and Neuroscience and Neural Engineering (4 papers). Sukbin Lim is often cited by papers focused on Neural dynamics and brain function (13 papers), Advanced Memory and Neural Computing (7 papers) and Neuroscience and Neural Engineering (4 papers). Sukbin Lim collaborates with scholars based in United States, China and South Korea. Sukbin Lim's co-authors include Mark S. Goldman, John Rinzel, David J. Freedman, Nicolas Brunel, David L. Sheinberg, Jillian L. McKee, Yali Amit, Alexander A. Chubykin, Emre Aksay and Qixin Yang and has published in prestigious journals such as Neuron, Journal of Neuroscience and Nature Neuroscience.

In The Last Decade

Sukbin Lim

13 papers receiving 299 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sukbin Lim United States 8 267 138 85 47 42 14 304
Fleur Zeldenrust Netherlands 9 213 0.8× 156 1.1× 105 1.2× 37 0.8× 33 0.8× 20 283
Cristina Savin United States 12 286 1.1× 150 1.1× 104 1.2× 66 1.4× 29 0.7× 33 362
Sadra Sadeh United Kingdom 12 339 1.3× 267 1.9× 61 0.7× 30 0.6× 29 0.7× 20 398
Everton J. Agnes United Kingdom 7 351 1.3× 264 1.9× 219 2.6× 58 1.2× 29 0.7× 10 430
Michael E. Rule United Kingdom 9 307 1.1× 179 1.3× 49 0.6× 43 0.9× 17 0.4× 17 356
Christian Pozzorini Switzerland 6 253 0.9× 143 1.0× 102 1.2× 37 0.8× 95 2.3× 10 328
Skander Mensi Switzerland 6 299 1.1× 168 1.2× 123 1.4× 41 0.9× 104 2.5× 10 324
Gabriel Koch Ocker United States 9 389 1.5× 243 1.8× 99 1.2× 31 0.7× 80 1.9× 16 434
Junying Ma China 4 295 1.1× 233 1.7× 83 1.0× 21 0.4× 27 0.6× 7 388
Laure Buhry France 8 209 0.8× 125 0.9× 63 0.7× 36 0.8× 36 0.9× 14 249

Countries citing papers authored by Sukbin Lim

Since Specialization
Citations

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

Fields of papers citing papers by Sukbin Lim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sukbin Lim

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

All Works

14 of 14 papers shown
1.
2.
Lim, Sukbin, et al.. (2024). Sensory-memory interactions via modular structure explain errors in visual working memory. eLife. 13. 1 indexed citations
3.
Chen, Shirui, Qixin Yang, & Sukbin Lim. (2023). Efficient inference of synaptic plasticity rule with Gaussian process regression. iScience. 26(3). 106182–106182. 2 indexed citations
4.
Lim, Sukbin, et al.. (2022). Unsupervised learning for robust working memory. PLoS Computational Biology. 18(5). e1009083–e1009083. 2 indexed citations
5.
Lim, Sukbin, et al.. (2021). Visual Familiarity Induced 5-Hz Oscillations and Improved Orientation and Direction Selectivities in V1. Journal of Neuroscience. 41(12). 2656–2667. 12 indexed citations
6.
Lim, Sukbin. (2021). Hebbian learning revisited and its inference underlying cognitive function. Current Opinion in Behavioral Sciences. 38. 96–102. 6 indexed citations
7.
Lim, Sukbin. (2019). Mechanisms underlying sharpening of visual response dynamics with familiarity. eLife. 8. 9 indexed citations
8.
Lim, Sukbin, et al.. (2017). Population-scale organization of cerebellar granule neuron signaling during a visuomotor behavior. Scientific Reports. 7(1). 16240–16240. 13 indexed citations
9.
Lim, Sukbin, Jillian L. McKee, Yali Amit, et al.. (2015). Inferring learning rules from distributions of firing rates in cortical neurons. Nature Neuroscience. 18(12). 1804–1810. 60 indexed citations
10.
Lim, Sukbin & Mark S. Goldman. (2014). Balanced Cortical Microcircuitry for Spatial Working Memory Based on Corrective Feedback Control. Journal of Neuroscience. 34(20). 6790–6806. 33 indexed citations
11.
Lim, Sukbin & Mark S. Goldman. (2013). Balanced cortical microcircuitry for maintaining information in working memory. Nature Neuroscience. 16(9). 1306–1314. 127 indexed citations
12.
Lim, Sukbin & Mark S. Goldman. (2012). Balanced cortical microcircuitry for maintaining short-term memory. BMC Neuroscience. 13(S1). 3 indexed citations
13.
Lim, Sukbin & Mark S. Goldman. (2011). Noise Tolerance of Attractor and Feedforward Memory Models. Neural Computation. 24(2). 332–390. 15 indexed citations
14.
Lim, Sukbin & John Rinzel. (2009). Noise-induced transitions in slow wave neuronal dynamics. Journal of Computational Neuroscience. 28(1). 1–17. 21 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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