Cheng Ly

624 total citations
33 papers, 399 citations indexed

About

Cheng Ly is a scholar working on Cognitive Neuroscience, Statistical and Nonlinear Physics and Cellular and Molecular Neuroscience. According to data from OpenAlex, Cheng Ly has authored 33 papers receiving a total of 399 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Cognitive Neuroscience, 18 papers in Statistical and Nonlinear Physics and 11 papers in Cellular and Molecular Neuroscience. Recurrent topics in Cheng Ly's work include Neural dynamics and brain function (26 papers), stochastic dynamics and bifurcation (18 papers) and Advanced Memory and Neural Computing (9 papers). Cheng Ly is often cited by papers focused on Neural dynamics and brain function (26 papers), stochastic dynamics and bifurcation (18 papers) and Advanced Memory and Neural Computing (9 papers). Cheng Ly collaborates with scholars based in United States, France and Canada. Cheng Ly's co-authors include Daniel Tranchina, Bard Ermentrout, Brent Doiron, Jason W. Middleton, Seth H. Weinberg, Tamar Melman, Alison L. Barth, Shree Hari Gautam, Woodrow L. Shew and Wilten Nicola and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Journal of Neurophysiology.

In The Last Decade

Cheng Ly

32 papers receiving 389 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Cheng Ly United States	12	297	193	145	98	68	33	399
Yasuhiro Tsubo Japan	11	364 1.2×	203 1.1×	176 1.2×	130 1.3×	74 1.1×	19	477
Idan Segev Israel	2	378 1.3×	156 0.8×	244 1.7×	74 0.8×	104 1.5×	3	505
Hiroyuki Mino Japan	9	273 0.9×	161 0.8×	122 0.8×	39 0.4×	33 0.5×	27	364
Alla Borisyuk United States	11	170 0.6×	92 0.5×	120 0.8×	47 0.5×	23 0.3×	27	311
Santi Chillemi Spain	12	185 0.6×	132 0.7×	131 0.9×	74 0.8×	23 0.3×	45	360
Ziying Fu China	12	165 0.6×	92 0.5×	69 0.5×	54 0.6×	29 0.4×	53	402
Michael Vanier United States	5	185 0.6×	95 0.5×	150 1.0×	94 1.0×	48 0.7×	5	354
Lubomir Kostal Czechia	13	311 1.0×	157 0.8×	223 1.5×	33 0.3×	90 1.3×	44	456
Cristina Soto-Treviño United States	7	411 1.4×	180 0.9×	290 2.0×	126 1.3×	41 0.6×	9	493
Zuzanna Piwkowska France	10	425 1.4×	143 0.7×	327 2.3×	23 0.2×	111 1.6×	17	492

Countries citing papers authored by Cheng Ly

Since Specialization

Citations

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

Fields of papers citing papers by Cheng Ly

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cheng Ly

This figure shows the co-authorship network connecting the top 25 collaborators of Cheng Ly. A scholar is included among the top collaborators of Cheng Ly 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 Cheng Ly. Cheng Ly 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

Gautam, Shree Hari, et al.. (2023). Odor modality is transmitted to cortical brain regions from the olfactory bulb. Journal of Neurophysiology. 130(5). 1226–1242.

Ly, Cheng, et al.. (2022). The Effects of Background Noise on a Biophysical Model of Olfactory Bulb Mitral Cells. Bulletin of Mathematical Biology. 84(10). 107–107. 3 indexed citations

Ly, Cheng & Seth H. Weinberg. (2022). Automaticity in ventricular myocyte cell pairs with ephaptic and gap junction coupling. Chaos An Interdisciplinary Journal of Nonlinear Science. 32(3). 33123–33123. 8 indexed citations

Ly, Cheng, et al.. (2021). A Competition of Critics in Human Decision-Making. SHILAP Revista de lepidopterología. 5(1). 81–81. 1 indexed citations

Gautam, Shree Hari, et al.. (2021). Differences in olfactory bulb mitral cell spiking with ortho- and retronasal stimulation revealed by data-driven models. PLoS Computational Biology. 17(9). e1009169–e1009169. 3 indexed citations

Ly, Cheng, et al.. (2021). Odor-evoked increases in olfactory bulb mitral cell spiking variability. iScience. 24(9). 102946–102946. 4 indexed citations

Ly, Cheng, et al.. (2019). Efficient calculation of heterogeneous non-equilibrium statistics in coupled firing-rate models. SHILAP Revista de lepidopterología. 9(1). 2–2. 2 indexed citations

Reynolds, Christian A., et al.. (2019). Development of a decerebrate model for investigating mechanisms mediating viscero-sympathetic reflexes in the spinalized rat. American Journal of Physiology-Heart and Circulatory Physiology. 316(6). H1332–H1340. 6 indexed citations

Ly, Cheng & Seth H. Weinberg. (2018). Analysis of heterogeneous cardiac pacemaker tissue models and traveling wave dynamics. Journal of Theoretical Biology. 459. 18–35. 5 indexed citations

10.

Ly, Cheng, et al.. (2018). Investigating the Correlation–Firing Rate Relationship in Heterogeneous Recurrent Networks. SHILAP Revista de lepidopterología. 8(1). 8–8. 7 indexed citations

11.

Ly, Cheng & Gary Marsat. (2017). Variable synaptic strengths controls the firing rate distribution in feedforward neural networks. Journal of Computational Neuroscience. 44(1). 75–95. 3 indexed citations

12.

Ly, Cheng, et al.. (2017). Practical approximation method for firing-rate models of coupled neural networks with correlated inputs. Physical review. E. 96(2). 22413–22413. 3 indexed citations

13.

Ly, Cheng. (2015). Firing rate dynamics in recurrent spiking neural networks with intrinsic and network heterogeneity. Journal of Computational Neuroscience. 39(3). 311–327. 11 indexed citations

14.

Ly, Cheng, Jason W. Middleton, & Brent Doiron. (2012). Cellular and Circuit Mechanisms Maintain Low Spike Co-Variability and Enhance Population Coding in Somatosensory Cortex. Frontiers in Computational Neuroscience. 6. 7–7. 29 indexed citations

15.

Ly, Cheng, Tamar Melman, Alison L. Barth, & Bard Ermentrout. (2010). Phase-resetting curve determines how BK currents affect neuronal firing. Journal of Computational Neuroscience. 30(2). 211–223. 23 indexed citations

16.

Ly, Cheng & Bard Ermentrout. (2010). Coupling regularizes individual units in noisy populations. Physical Review E. 81(1). 11911–11911. 15 indexed citations

17.

Ly, Cheng & Bard Ermentrout. (2010). Analytic approximations of statistical quantities and response of noisy oscillators. Physica D Nonlinear Phenomena. 240(8). 719–731. 12 indexed citations

18.

Ly, Cheng & Brent Doiron. (2009). Divisive Gain Modulation with Dynamic Stimuli in Integrate-and-Fire Neurons. PLoS Computational Biology. 5(4). e1000365–e1000365. 20 indexed citations

19.

Ly, Cheng & Bard Ermentrout. (2008). Synchronization dynamics of two coupled neural oscillators receiving shared and unshared noisy stimuli. Journal of Computational Neuroscience. 26(3). 425–443. 42 indexed citations

20.

Ly, Cheng, et al.. (2006). Population density methods for stochastic neurons with realistic synaptic kinetics: Firing rate dynamics and fast computational methods. Network Computation in Neural Systems. 17(4). 373–418. 40 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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