Publications

Journal Articles, Manuscripts, and Reports

Journal Articles

  1. Wang B, Chen K, Luo S, Xiao Y, Li S*, Zhou D. Anatomical connectivity reconstruction of biological neuronal networks using Granger causality. Neural Networks. 2025.
  2. Li G, Li S*, Wang X-J*. A hierarchy of time constants and reliable signal propagation in the marmoset cerebral cortex. Nature Communications. 21(1), 16:11640, 2025.
  3. Wang Z, McLaughlin D, Zhou D*, Li S*. Overcoming the space clamp effect: Reliable recovery of local and effective synaptic conductances of neurons. Proceedings of the National Academy of Sciences of the United States of America (PNAS). 122(40), e2512294122, 2025.
  4. Wang Z, Qian D, Li S*, Lu W*, Zhou D*. Adaptive cholinergic feedback network oscillations: insights into striatal beta oscillations and circuit dynamics. Cognitive Neurodynamics. 19:117, 2025.
  5. Du X, Crodelle J, Barranca V, Li S*, Shi Y, Gao S*, Zhou D*. Biophysical modeling and experimental analysis of the dynamics of C. elegans body-Wall muscle cells. PLOS Computational Biology. 21(1), e1012318, 2025.
  6. Du X, Tian Z, Li S*, Zhou D*. A generalized spiking locally competitive algorithm for multiple optimization problems. Neurocomputing. 624, 1293925, 2025.
  7. Liu C, Ma J, Li S*, Zhou D*. Dendritic integration inspired artificial neural networks capture data correlation. the Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS). 2024.
  8. Mei J, Chen K, Xiao Y, Li S*, Zhou D*. The asymptotic behavior of conditional granger causality with respect to sampling interval. CSIAM Transactions on Life Sciences. 1(1), 22-43, 2024.
  9. Tian Z, Chen K, Li S*, McLaughlin D*, Zhou D*. Causal connectivity measures for pulse-output network reconstruction: analysis and applications. Proceedings of the National Academy of Sciences of the United States of America (PNAS). 121 (14) e2305297121，2024.
  10. Li S*, McLaughlin D*, Zhou D*. Mathematical modeling and analysis of spatial neuron dynamics: dendritic integration and beyond. Communications on Pure and Applied Mathematics (CPAM). 76(1), 114-162, 2023.
  11. Qian D, Li W, Xue J, Wu Y, Wang Z, Shi T, Li S, Yang J, Qiu S, Wang S, Wang Q, Yuan T, Zhou D*, Lu W*. A striatal SOM-driven ChAT-iMSN loop generates beta oscillations and produces motor deficits. Cell Reports. 40(3), 111111, 2022.
  12. Marius’t Hart, B, ..., Li S, ..., Viegen, T. Neuromatch Academy: a 3-week, online summer school in computational neuroscience. Journal of Open Source Education. 5(49), 118, 2022.
  13. Li S*, Wang X-J*. Hierarchical timescales in the neocortex: mathematical mechanism and biological insights. Proceedings of the National Academy of Sciences of the United States of America (PNAS). 119, 6, e2110274119, 2022.
  14. Song Y, Zhou D*, Li S*. Maximum entropy principle underlies wiring length distribution in brain networks. Cerebral Cortex. 31: 4628–4641, 2021.
  15. Viegen T, ..., Li S, ... Peters M. Neuromatch academy: teaching computational neuroscience with global accessibility. Trends in Cognitive Sciences, 25(7), 535-538, 2021.
  16. Li S, Liu N, Zhang X*, McLaughlin D*, Zhou D*, Cai D. Dendritic computation captured by an effective point neuron model. Proceedings of the National Academy of Sciences of the United States of America (PNAS), 116, 39, 15244-15252, 2019.
  17. Li S, Liu N, Li Y, Zhang X*, Zhou D*, Cai D. Determination of effective synaptic conductances using somatic voltage clamp. PLoS Computational Biology, 15, 3, e1006871, 2019.
  18. Gu Q, Xiao Y, Li S*, Zhou D*. The emergence of spatially periodic diffusive waves in small-world neuronal networks. Physical Review E, 100, 042401, 2019.
  19. Xiao Y*, Li S*, Zhou D*. Representing conditional Granger causality by vector auto-regressive parameters. Communications in Mathematical Sciences, 17(5), 1353–1386, 2019.
  20. Dai W*, Li S*, Zhou D*. Fast algorithms for simulation of neuronal dynamics based on the bilinear dendritic integration rule. Communications in Mathematical Sciences, 17(5), 1313–1331, 2019.
  21. Gu Q, Li S*, Dai W, Zhou D*, Cai D. Balanced active core in heterogeneous neuronal networks. Frontiers in Computational Neuroscience. 2, 109, 2019.
  22. Li S, Xiao Y, Zhou D*, Cai D. Causal inference in nonlinear systems: Granger causality versus time-delayed mutual information. Physical Review E, 97, 052216, 2018. [Code]
  23. Li S, Xu J, Chen G, Lin L*, Zhou D*, Cai D*. The characterization of hippocampal theta-driving neurons -- a time-delayed mutual information approach. Scientific Reports, 7, 5637, 2017.
  24. Li S, Zhou D*, Cai D*. Analysis of the dendritic integration of excitatory and inhibitory inputs from cable models. Communications in Mathematical Sciences, 13, 565-575, 2015.
  25. Li S, Liu N, Zhang X, Zhou D*, Cai D*. Bilinearity in spatiotemporal integration of synaptic inputs. PLoS Computational Biology, 10, e1004014, 2014.
  26. Zhou D, Li S, Zhang X, Cai D*. Phenomenological incorporation of nonlinear dendritic integration using integrate-and-fire neuronal frameworks. PLoS One, e53508, 2013.

Book Chapters

  1. Li S, Zhang X. Dendritic signal integration. A chapter in Neuroscience (4th edition) edited by Jisheng Han, Mu-ming Poo and Yi Rao, 2022. (in Chinese)
  2. Li S, Zhang X. Synaptic signal integration. A chapter in Neural Circuits and Brain Diseases edited by Yizheng Wang and Yin Mao, in press. (in Chinese)
  3. Li S. Modeling single neuron dynamics. A chapter in Neuroinformatics and Modeling of Neurological Function edited by Zi-Gang Huang, in progress. (in Chinese)

Ph.D. Thesis

  1. Theoretical modeling and analysis of neuronal dendritic integration. (in Chinese)