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发表论文目录
作者:数学建模与神经计算 发布日期:2019-1-3
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1997年
(1) 刘深泉,陆启韶,用Fife量级求解eikonal方程.物理学报.1997年.Vol.46.1457-1463
1998年
(1) 刘深泉,陆启韶,激发介质中螺旋波的波尖运动.物理学报.1998年.Vol.47.1058-1063
1999年
(1) Shenquan Liu, Qishao Lu, The motion of organization center of scroll waves in excitable media with single diffusion. Applied Mathematics and Mechanics, Vol.20, No.4 1999, 418-425
(2) 刘深泉,陆启韶, 各向异性相态场模型的Gibbs-Thompson关系.应用数学学报,1999年.Vol.22, 107-114.
2002年
(1) 刘深泉,心脏节律的神经细胞模型,医用生物力学,2002年,Vol.17(3):169-173.
2003年
(1) 刘深泉,范涛,心脏表面的动作电位,医用生物力学,2003年,Vol.18(4):222-225.
2004年
(1) 刘深泉.L.Song,龙虾胃肠神经系统的数值分析,生物物理学报,2004年,Vol.20(3):217-224
(2) Liu Shenquan, Structure of wave front and organization center in excitable media, Applied Mathematics and Mechanics, 2004, Vol.25(8):911-916.
2005年
(1) Shenquan Liu and Tao Fan Qishao Lu,The Spike Order of the Winnerless Competition (WLC) Model and Its Application to the Inhibition Neural System,International Journal of Nonlinear Sciences and Numerical Simulation, 2005,Vol.6(2):133-138
(2) Shenquan Liu, Le Song. The curvature relation of wave front and wave changing under external stimulus, Applied Mathematics and Mechanics, 2005, Vol.26 (7):911-916

2005年

(1) 严传魁,刘深泉.动态IP3-Ca振荡模型的数值分析,生物物理学报,2005,Vol.21(5): 339-344
2006年
(1) 刘深泉,海若螺平衡囊神经系统的混沌特性,医用生物力学,2006年,Vol.21(1):38-42
2007年
(1) Yan Chuankui, Liu Shenquan. Transitional function of DG to CA3 in the hippocampus, Progress in Natural Science, 2007,Vol. 17(12): 1436-1444
(2) 刘深泉,张万琴,甲壳类动物胃肠神经系统的数值分析,医用生物力学,2007, Vol.22(1):1-8.
2008年
(1) Yan Chuankui, Liu Shenquan, A Stochastic Resonance Memory Mechanism of Hippocampus. Advances in Cognitive Neurodynamics ICCN 2007, part I,2008,103-107
(2) Liu Shenquan, Chen Shuchun and Wang Rubin. WLC Analysis of Lamprey Neural System Advances in Cognitive Neurodynamics ICCN 2007, part III, 2008, 559-563
(3)  陆启韶,刘深泉,刘锋,王青云,侯中怀,郑艳红,生物神经网络系统动力学与功能研究, 力学进展 2008, 38 (6): 766-793
2009年
(1) 谢彬,刘深泉,李炎烽,陈树春.生物神经系统的编码特性和小世界特性.生物数学学报,2009,24(3):507-512
(2) 黄江涛,刘深泉,马在光. 视皮层中神经元的同步发放现象.中国生物医学工程学报,2009,Vol.28(2):238-2243
2010年
(1) 张同斌,刘深泉,孟翔翔. 肿瘤血管新生的数学模拟.生物数学学报.2010,25(2):1-11
(2) 汪雷,刘深泉.大脑中神经回路的电位发放比较, 动力学与控制学报,2010, Vol.8(3):1-7
(3) 刘利华,刘深泉.海马CA1锥体神经元放电波形的数值研究.北京生物医学工程. 2010, 29(3):256-260
2011年
(1) WANG Lei, LIU Shenquan. Neural circuit and its functional roles in cerebellar cortex. Neuroscience Bulletin, 2011 June 1, 2011, 27(3):173-184
(2) Lei WANG, Shenquan LIU Shanxing Ou  Numerical simulation of neuronal spike patterns in a retinal network model, Neural Regeneration Research. Volume 6, Issue 16, June 2011 :1254-1260
(3) Lixia Duan,Zhuoqin Yang,Shenquan Liu,Dunwei Gong Neurological Sciences Bursting and two-parameter bifurcation in the Chay neuronal model.Discrete and continuous dynamical systems. SERIES B. Volume 16, Number 2, September 2011:445 - 456
(4) Rong Jiang,Qiang Liu,Quan Liu,Shenquan Liu. A proposal for the morphological classification and nomenclature of neurons. Neural Regeneration Research. Volume 6 Issue 25, 2011:1925-1930
(5) 马丹,刘深泉,汪雷.两房室神经元模型的分岔现象,北京生物医学工程, 2011,30(6):567-573
2012年

(1) Xuanliang LIU, Shenquan LIU. Codimension-two bifurcation analysis in two dimensional Hindmarsh Rose model. Nonlinear Dynamic (2012)67:847-857
(2) Yu Chao Zengxin Han Wencong Zeng Shenquan Liu. Morphology cluster and prediction of growth of human brain pyramidal neurons. Neural Regeneration Research. Volume 7 Issue 1, 2012:36-40
(3) Wang L, Liu S, Zhang J, Zeng Y .Burst firing transitions in two-compartment pyramidal neuron induced by the perturbation of membrane capacitance. Neurological Sciences. 2012 June; 33(3):595-604
(4) Wang L, Liu S, Zhang J, Zeng Y. Temperature-dependent transitions of burst firing patterns in a model pyramidal neuron. Neurophysiology: Vol.44, Issue 4 (2012), 265-273.
2013年

(1) Lei Wang, Shenquan Liu, Yanjun Zeng (China): Diversity of firing patterns in a two-compartment model neuron: using internal time delay as an independent variable, Neural Network World , Vol.23, No.3,2013: 243-254.
(2 )Lei Wang, Shenquan Liu, Linlin Zhang, Yanjun Zeng. Dynamical properties of firing patterns in ELL pyramidal neuron under external electric field stimulus. Neurological Sciences, (2013) 34:1517-1522
(3) W. Ye, S.Q. Liu, Y.J. Zeng Peculiarities of the Tail-Withdrawal Reflex Circuit in Aplysia: a Model Study. Neurophysiology, Vol.45(5/6), 2013:379-387.
(4) 江小芳;刘深泉;张煦晨;中等多棘神经元的多房室模型分析.生物物理学报.2013 Vol. 29 (7):527-542
(5) 李敏,刘宣亮,刘深泉.一类Hodgkin_Huxley模型的分支研究生物数学学报, 2013, 28(1):71:76
2014年

(1) H. Ren, S. Q. Liu, X. Zhang, Y. J. Zeng, Spike Timing-Dependent Plasticity in CA1 Pyramidal Neuron-Controlling Hippocampal Circuits: a Model Study Neurophysiology 08/2014; Vol. 46(No. 4):300-307..

(2) W. Ye, S.Q. Liu, X.l. LIU., Synchronization of two electrically coupled inspiratory pacemaker neurons. Science China Technological Sciences, Vol.57, Issue 5, 2014: 929-935.
(3) Congmin Liu, Xuanliang Liu, Shenquan Liu: Bifurcation analysis of a Morris-Lecar neuron model. Biological Cybernetics. Vol.108(1) ,2014: 75-84.
(4) Y.Zh. Guan, Sh.Q. Liu, Y.J. Zeng. Gradient Trigger Mechanisms Related to Bistability Regimes in a Leech Heartbeat Model, Neurophysiology, Vol.46, No.2, April 2014: 108-114
(5) Jing Wang, Shenquan Liu, Xuanliang Liu Quantification of synchronization phenomena in two reciprocally gap-junction coupled bursting pancreatic beta cells. Chaos, Solitons Fractals. Vol.68, November 2014: 65–71.
(6) X.C. Zhang, S.Q. Liu, Y.J. Zeng, G. X. Zhan. Analysis of Long-Term Depression in the Purkinje Cell Circuit (a Model Study). Neurophysiology, Vol. 46, No. 1, February 2014:25-32.
2015年
(1) X. C. Zhang, S. Q. Liu, H. X. Ren, Y. Wen, Y. J. Zeng. Dynamic Properties of Purkinje Cells Having Different Electrophysiological Parameters: a Model Study. Neurophysiology, February 2015, Volume 47, Issue 1, pp 2-10
(2) Jing Wang, Shenquan Liu, Xuanliang Liu, Yanjun Zeng. Birfurcation and Firing Patterns of the Pancreaticβ-cell. International journal of bifurcation and chaos. Vol.25,No.9 (2015):11pages
(3)  Wang J., Liu S., Wang H., Zeng Y. (China), Dynamical Properties of Firing Patterns in the Huber-Braun Cold Receptor Model in Response to External Current Stimuli. Neural Network World. Volume 25.No.6 (2015):641-65
(4) H. X. Ren ,Sh. Q. Liu,X. C. Zhang,Y. J. Zeng. Spike Timing-Dependent Plasticity in the CA1 Pyramidal Neuron in a Modeled Hippocampal Circuit. Neurophysiology. August 2015. Vol 47, No. 4,  264-270
2016 年
(1)N Ju,Sh Q liu,B Lu, X X Jiang. Patterns of Leech Heart Interneurons under External Current Stimalation:a Model Study, Neurophysiology,20 February  2016:1-8
(2) Jing Wang,Shenquan Liu. The Role of Ions Channels in Firing Dynamic of a Two Compartment Purkinje Cell Model. Advance in Connitive Neurodynamics, Chapter 115, Jan,2016:855-860
(3) Jing Wang, Shenquan Liu.Hong Wang,Niansheng Ju,Yanjun Zeng.A model-based analysis of physiological properties of the striatal medium spiny neurn. Neurlogical Research,06,Feb. 2016.
(4) Weijie Ye. Shenquan Liu, Yuguo Yu. A neural model of the frontal eye fields with reward-based learning. Neural Networks. 2016,81:39-51
(5) Bo Lu, Shenquan Liu,Xuanliang Liu, Xiaohui Wang.Bifurcation and Spike Adding  Transition in Chay-Keizer Model. International Journal of Bifurcation and Chaos. Volume.26, Issue 05,May 2016(13 pages)
(6) Jing Wang, Weijie Ye,Shenquan Liu,Xiaofang Jiang. Qualitative and quantitative aspects of synchronization in coupled CA1 pyramidal neurons .Chaos Solitons & Fractals .Oct 2016, Volume 93:32–38
(7) Xiaofang Jiang, Shenquan Liu, Bo Lu,Yanjun Zeng  High-Frequency Stimulation for Parkinson’s Disease and Effects on Pathways in Basal Ganglia Network Model Journal of Medical and Biological Engineering. Dec2016,  36(5).
(8) 陆博,刘深泉,刘宣亮, 神经元模型中混合模式振荡动力学研究进展. 动力学与控制学报. 2016年第14卷第6期:481-491
2017 年
(1)Jing Wang,Bo Lu,Shenquan Liu,Xiaofang Jiang.Bursting Types and Bifurcation Analysis in the Pre-B?tzinger Complex Respiratory Rhythm Neuron.International Journal of Bifurcation and Chaos 27(01):1750010,January 2017
(2)Bo Lu , Shenquan Liu, Xiaofang Jiang ,Xiaohui Wang.The mixed-mode oscillations in Av-Ron-Parnas-Segel model.Discrete and Continuous Dynamical Systems - Series S Volume 10(,Number 3):487 - 504,February 2017
(3)Wang, Jing; Liu, Shenquan; Lu, Bo; Zeng, Yanjun . The role of relative membrane capacitance and time delay in cerebellar Purkinje cells. BIOMEDICAL ENGINEERING BIOMEDIZINISCHE TECHNIK, 2017.10, 62(5): 529-536
[4] Zhan, Feibiao; Liu, Shenquan.Response of Electrical Activity in an Improved Neuron Model under Electromagnetic Radiation and Noise. FRONTIERS IN COMPUTATIONAL NEUROSCIENCE, 2017.11.21, 11 ; SCIE
[5] Ye, W.; Liu, S.; Liu, X. . TRANSITION MODES BETWEEN SPIKING AND BURSTING IN A PACEMAKER NEURON. NEURAL NETWORK WORLD, 2017, 27(2): 247~258 ; SCIE
[6] Zhang, Xiaohan; Liu, Shenquan; Zhan, Feibiao; Wang, Jing; Jiang, Xiaofang. The Effects of Medium Spiny Neuron Morphologcial Changes on Basal Ganglia Network under External Electric Field: A Computational Modeling Study. FRONTIERS IN COMPUTATIONAL NEUROSCIENCE, 2017.10.26, 11.
2018年
[1] Feibiao Zhan; Shenquan Liu; Jing Wang; Bo Lu. Bursting patterns and mixed-mode oscillations in reduced Purkinje model. International Journal of Modern Physics B, 2018.1.20, 32(05): 18500431-185004315.
[2] Feibiao Zhan; Shenquan Liu; Mixed-mode oscillations and bifurcation analysis in a pituitary model. Nonlinear Dynamics, Volume 94, Issue 2, October 2018
[3] XiaoHan Zhang, ShenQuan Liu. Stochastic resonance and synchronization behaviors of excitatory-inhibitory small-world network subjected to electromagnetic induction. Chin. Phys. B,Vol.27,No.4 (2018).

[4] Yingteng Zhang, Shenquan Liu. Analysis of structural brain MRI and multi-parameter classification for Alzheimers disease. Biomedical Engineering/Biomedizinische Technik. 2018, 63(4): 427-437.

[5] Yingteng Zhang, Shenquan Liu. Individual identification using multi-metric of DTI in Alzheimer’s disease and mild cognitive impairment. Chin. Phys. B Vol. 27, No. 8 (2018) 088702.
[6] Yingteng Zhang, Shenquan Liu, Dongsheng Xiong. Respiratory Rhythm in a Simplified Respiratory Network Model. Neurophysiology, April 2018, Volume 50, Issue 2:83–92.
[7]叶伟杰; 刘深泉; 基于学习的多目标脑决策模型研究.动力学与控制学报, 2018.2, 16(1): 72~79
2019年

[1] Qiqian WANG,Shenquan Liu. A General Model of Ion Passive Transmembrane Transport Based on Ionic Concentration. Frontiers in Computational Neuroscience. January 2019,Vol. 12.


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