Publications

★   S. Li, N. Liu, X. Zhang, D. Zhou and D. Cai, “Determination of effective synaptic conductances using somatic voltage

      clamp”, PLoS Comput. Biol., accepted, 2019.

 

★   Z.J. Xu, J. Crodelle, D. Zhou and D. Cai, “Maximum entropy principle analysis in network systems with short-time

      recordings”, Phys. Rev. E, 99 (2), 022409, 2019. ( PDF )

 

★   Z.J. Xu, D. Zhou and D. Cai, “Dynamical and coupling structure of pulse-coupled networks in maximum entropy

      analysis”, Entropy, 21 76, 2019. ( PDF )

 

★   Q.L. Gu, S. Li, W.P. Dai, D. Zhou and D. Cai, Balanced active core in heterogeneous neuronal networks”, Front.

      Comput. Neurosci., 12, 109, 2019. ( PDF )

 

★   W.P. Dai, D. Zhou, D.W. McLaughlin and D. Cai, “Mechanisms underlying contrast-dependent orientation

      selectivity in mouse V1”, Proc. Natl. Acad. Sci., USA, 115 (45), 11619-11624, 2018. ( PDF )  ( Code )

 

★   S. Li, Y. Xiao, D. Zhou and D. Cai, “Causal inference in nonlinear systems: Granger causality versus time-delayed 

      mutual information”, Phys. Rev. E, 97 (5), 052216, 2018. ( PDF ) ( Code )

 

★   Q.L. Gu, Z.K. Tian, G. Kovacic, D. Zhou and D. Cai, The dynamics of balanced spiking neuronal networks under

      Poisson drive is not chaotic”, Front. Comput. Neurosci., 12, 47, 2018. ( PDF )

 

★   B. Min, D. Zhou and D. Cai, “Effects of firing variability on network structures with spike-timing dependent plasticity”, 

      Front. Comput. Neurosci., 12, 1, 2018. ( PDF )

 

★   Y. Zhang, Y. Xiao, D. Zhou and D. Cai, “Spike-triggered regression for synaptic connectivity reconstruction in neuronal

      networks”, Front. Comput. Neurosci., 11, 101, 2017. ( PDF ) ( Code )

 

★   S. Li, J. Xu, G. Chen, L. Lin, D. Zhou and D. Cai, “The characterization of  hippocampal theta-driving neurons—a

      time delayed mutual information approach”, Sci. Rep., 7, 5637, 2017. ( PDF )

 

★   Z.J. Xu, G. Bi, D. Zhou and D. Cai, “A dynamical state underlying the second order maximum entropy principle in

      neuronal networks”, Comm. Math. Sci., 15 (3), 665-692, 2017. ( PDF )

 

★   V.J. Barranca, G. Kovacic, D. Zhou and D. Cai, “Improved compressive sensing of natural scenes using localized

      random sampling”, Sci. Rep., 6, 31976, 2016. ( PDF )

 

★   S.W. Jiang, H. Lu, D. Zhou, and D. Cai, “Stochastic linearization of turbulent dynamics of dispersive waves in

      equilibrium and  non-equilibrium state”, New J. Phys., 18 (8), 083028, 2016. ( PDF )

 

★   V.J. Barranca, D. Zhou and D. Cai, “Compressive sensing reconstruction of feed-forward connectivity in

      pulse-coupled nonlinear networks”, Phys. Rev. E, 93 (6), 060201 (Rapid Communication), 2016. ( PDF )

 

★   Y. Zhang, Y. Xiao, D. Zhou and D. Cai, “Granger causality analysis with nonuniform sampling and its application to

      pulse-coupled nonlinear dynamics”, Phys. Rev. E, 93 (4), 042217, 2016. ( PDF )

 

★   V.J. Barranca, G. Kovacic, D. Zhou and D. Cai, “Efficient image processing via compressive sensing of integrate-and-

      fire neuronal network dynamics”, Neurocomputing, 171, 1313-1322, 2016. ( PDF )

 

★   V.J. Barranca, D. Zhou and D. Cai, “Low-rank network decomposition reveals structural characteristics of small-world 

      networks”, Phys. Rev. E, 92 (6), 062822, 2015. ( PDF )

 

★   V.J. Barranca, D. Zhou and D. Cai, “A novel characterization of amalgamated networks in natural systems”, Sci. Rep., 

      5, 10611, 2015. ( PDF )

 

★   S. Li, D. Zhou and D. Cai, Analysis of the dendritic integration of excitatory and inhibitory inputs using cable

      models, Comm. Math. Sci., 13 (2), 565-575, 2015. ( PDF )

 

★   V.J. Barranca, G. Kovacic, D. Zhou and D. Cai, “Network dynamics for optimal compressive-sensing input-signal

      recovery”, Phys. Rev. E, 90 (4), 042908, 2014. ( PDF )

 

★   S. Li, N. Liu, X. Zhang, D. Zhou and D. Cai, “Bilinearity in Spatiotemporal integration of synaptic inputs”, PLoS 

      Comput. Biol., 10 (12), e1004014, 2014. ( PDF )

 

★   S.W. Jiang, H. Lu, D. Zhou, and D. Cai, “Renormalized dispersion relations of β-Fermi-Pasta-Ulam chains in 

      equilibrium and nonequilibrium states”, Phys. Rev. E, 90 (3), 032925, 2014. ( PDF )

 

★   D. Zhou, Y. Zhang, Y. Xiao and D. Cai, “Analysis of sampling artifacts on the Granger causality analysis for topology 

      extraction of neuronal dynamics”, Front. Comput. Neurosci., 8, 75, 2014. ( PDF )

 

★   V.J. Barranca, G. Kovacic, D. Zhou and D. Cai, “Sparsity and compressed coding in sensory systems”, PLoS Comput.

      Biol., 10 (8), e1003793, 2014. ( PDF )

 

★   D. Zhou, Y. Zhang, Y. Xiao and D. Cai, “Reliability of the Granger causality inference”, New J. Phys., 16 (4), 043016, 

      2014. ( PDF )

 

  J. Zhang, D. Zhou, D. Cai and A.V. Rangan, “A coarse-grained framework for spiking neuronal networks: between 

       homogeneity and synchrony”, J. Comput. Neurosci., 37 (1), 81-104, 2014. ( PDF )

 

★   D. Zhou, Y. Xiao, Y. Zhang, Z. Xu and D. Cai, “Granger causality network reconstruction of conductance-based 

      integrate-and-fire neuronal systems”, PLoS ONE, 9 (2), e87636, 2014. ( PDF ) ( Code )

 

  J. Zhang, K. Newhall, D. Zhou and A.V Rangan, “Distribution of correlated spiking events in a population-based 

      approach for integrate-and-fire networks”, J. Comput. Neurosci., 36 (2), 279-295, 2014. ( PDF )

 

  D. Zhou, Y. Xiao, Y. Zhang, Z. Xu and D. Cai, “Causal and structural connectivity of pulse-coupled nonlinear 

       networks”, Phys. Rev. Lett, 111 (5), 054102, 2013. ( PDF ) ( Code )

 

  D. Zhou, A.V. Rangan, D.W. McLaughlin and D. Cai, “Spatiotemporal dynamics of neuronal population response in

       the primary visual cortex”, Proc. Natl. Acad. Sci., USA, 110 (23), 9517-9522, 2013. ( PDF )

 

  D. Zhou, S. Li, X. Zhang and D. Cai, “Phenomenological incorporation of nonlinear dendritic integration using 

       integrate-and-fire neuronal frameworks”, PLoS ONE, 8 (1), e53508, 2013. ( PDF )

 

  Y. Sun, A.V. Rangan, D. Zhou and D. Cai, “Coarse-grained event tree analysis for quantifying Hodgkin-Huxley 

       neuronal network dynamics”, J. Comput. Neurosci., 32 (1), 55-72, 2012. ( PDF )

 

  Y. Sun, D. Zhou, A.V. Rangan and D. Cai, “Pseudo-Lyapunov exponents and predictability of Hodgkin-Huxley

       Neuronal network dynamics”, J. Comput. Neurosci., 28 (2), 247-266, 2010. ( PDF )

 

★   D. Zhou, Y. Sun, A.V. Rangan and D. Cai, “Spectrum of Lyapunov exponents of non-smooth dynamical systems of 

      integrate-and-fire type”, J. Comput. Neurosci., 28 (2), 229-245, 2010. ( PDF )

 

★   K.A. Newhall, G. Kovacic, P.R. Kramer, D. Zhou, A.V. Rangan and D. Cai, “Dynamics of current-based, Poisson 

      driven, integrate-and-fire neuronal networks”, Comm. Math. Sci., 8 (2), 541-600, 2010. ( PDF )

 

★   D. Zhou, A.V. Rangan, Y. Sun and D. Cai, “Network-induced chaos in integrate-and-fire neuronal ensembles”, Phys. 

      Rev. E, 80 (3), 031918, 2009. ( PDF )

 

  Y. Sun, D. Zhou, A.V. Rangan and D. Cai, “Library-based numerical reduction of the Hodgkin–Huxley neuron for 

       network simulation”, J. Comput. Neurosci., 27 (3), 369-390, 2009. ( PDF )

 

  D. Zhou, A. Shi and P. Zhang, “Numerical simulation of phase separation coupled with crystallization”, J. Chem. Phys., 

       129 (15), 154901, 2008. ( PDF )

 

  D. Zhou, P. Zhang and W. E, “Modified models of polymer phase separation”, Phys. Rev. E, 73 (6), 061801, 2006.  

       ( PDF )

 

 

 

( correspondence author )

Douglas Zhou (周栋焯)

Professor

Institute of Natural Sciences and School of Mathematical Sciences

Shanghai Jiao Tong University, Shanghai, China

 

 

Office:    Pao Yue-Kong Library,Room 523

Tel:         86-21-54747359

Fax:        86-21-54747359

Email:    zdz{At}sjtu{dot}edu{dot}cn