[B1]Computational Neuroscience: A Comprehensive Approach; Feng J.F. (Ed.), Chapman and Hall / CRC Press, Boca Raton, 626 pages,2003,Oct.

[B2]Networks: from Biology to Theory; Feng J.F., J.F.Jost and M.P.Qian (eds.), Springer-Verlag, 2007

[B3]Frontiers in Computational and Systems Biology; Feng J.F., W.J. Fu, and F.Z Sun(eds.), Springer-Verlag,2010

Publications( IF=Impact Factor, *corresponding author)

2020 (under revision or accepted, pdf is availabel when it is in press)

[J267] Du L, et al., Feng JF (2020) AGO-Net: Associateion-guided 3D point cloud object detection network IEEE PAMI (IF=17.7, under revision)

[J266] Chao H, Wang K. He Y, Zhang J, Feng JF(2020) GaitSet: Cross-view gait recognition through utilizing gait as a deep set IEEE PAMI (IF=17.7, under revision)

[J265] Xu L, et al. (2020) Avalanche criticality in individuals is associated with fluid intelligence and working memory capacity biorxiv doi:

[J264] Gong WK, et al. (2020) Family environment, and psychiatric problems and brain structure in the children Nature Commun. (IF=12, accepted)

[J263] He L, et al. (2020) The functional connectome predicts anxiety related to the COVID-19 pandemics American Journal of Psychiatry (IF=13, accepted)

[J262] Zeyu Jiao, Yinglei Lai, Jujiao Kang, Weikang Gong, Liang Ma, Tianye Jia, Chao Xie, Wei Cheng, Andreas Heinz, Sylvane Desrivi®®res, Gunter Schumann, IMAGEN Consortium, Fengzhu Sun, Jianfeng Feng (2020) Assessing Study Reproducibility through M2RI: A Novel Approach for Large-scale High-throughput Association Studies biorxiv doi:

[J261]Jujiao Kang, Tianye Jia, Zeyu Jiao, Chun Shen, Chao Xie, Wei Cheng, Barbara J Sahakian, David Waxman, Jianfeng Feng (2020) Increased brain volume from cereal, decreased brain volume from coffee -- shared genetic determinants and impacts on cognitive function, body mass index (BMI) and other metabolic measures: cohort study of UK Biobank participants medrxiv doi:

[J260]Jia TY, et al. Jianfeng Feng (2020) Neural network involving medial orbitofrontal cortex and dorsal periaqueductal grey regulation in human alcohol abuse Science Advances (IF=13, accepted)

[J259] H Wang, et al. Jianfeng Feng (2020) Severe nausea and vomiting in pregnancy: psychiatric and cognitive problems and brin structure in children BMC Medicine doi: 10.1186/s12916-020-01701-y

[J258] Gong XH et al. (2020) Polygenic risk for autism spectrum disorder affects left amygdala activity and negative emotion in schizophrenia Translational Psychiatry (accepted)

[J257] Feng RQ et al. (2020) Hypertension is associated with reduced hippocampal connectivity and impaired memory EBioMedicine (accepted)

[J256] Qi Zhao, Valerie Voon, Lingli Zhang, Chun Shen, Jie Zhang, Jianfeng Feng (2020) Cortical thickness and intelligence during a neurodevelopmental transition stage: results from the ABCD study Human Brain Mapping (under revision)

[J255] Xie C et al. (2020) Reward vs Non-reward Sensitivity of the Medial vs Lateral Orbitofrontal Cortex Related to the Severity of Depressive Symptoms Biological Psychiatry: CCNI (accepted)

[J254] Rolls E, Cheng W, Feng JF (2020) The orbitofrontal cortex: reward, emotion, and depression Brain Communications (accepted)

[J253] Wan Z et al. (2020) Sensation-seeking is related to functional connectivities of the medial orbitofrontal cortex with the anterior cingulate cortex NeuroImaging Volume 215, 116845

[J252] Chong H. et al. (2020) Connections of the human orbitofrontal cortex and inferior frontal gyrus Cerebral Cortex doi: 10.1039/cercor/bhaa160

[P40] L DU, et al. (2020) 3DCFS: fast and robust joint 3d semantic-instance segmentation via couped feature selection ICRA (accepted)

[P39] L DU, et al. (2020) Associate-3Ddet: perceptual-to-conceptual assocation for 3D point cloud object detection CVPR (accepted)

[J251] Lingli Zhang et al. (2020) Symptom improvement in children with autism sprectrum disorder following bumetanide administration is associated with decreased GABA/glutamate ratios Translational Psychiatry 10(1): 1-12

[J250] WJ Duan et al. (2020) pH rationametrically responsive surface enhanced resonance Rman scattering probe for tumor acidic margin delineation and image-guided surgery Chemical Science ( accepted )

[J249] HT Ruan (2020) Topographic diversity of structural connectivity in schizophrenia Schizophrenia Research 215: pp. 181-189

[J248] Chu-Chung Huang et al. (2020) Transdiagnosrtic and illness-specific fundational dysconnectivity across schizophrenia, bipolar disorder and major depression Biological Psychiatry: CNNI doi: 10.1016/j.bpsc.2020.01.010

[J247]Cheng,W., Rolls, E. T., Gong,W., Du,J., Zhang,J., Zhang,X., Li,F. and Feng,J. (2020) Sleep duration, brain structure, and psychiatric and cognitive problems in children. Molecular Psychiatry doi: 10.1038/s41380-020-0663-2. Press Release Supplementary Material

[J246] Rolls, E. T., Cheng,W., Du,J., Wei,D., Qiu,J., Dai,D., Zhou,Q., Xie, P. and Feng, J. (2020) Functional connectivity of the right inferior frontal gyrus and orbitofrontal cortex in depression. Social Cognitive and Affective Neuroscience doi: 10.1093/scan/nsaa014. Supplementary Material

[J245] Rolls, E. T., Zhou, Y., Cheng,W., Gilson,M., Deco,G. and Feng,J. (2020) Effective connectivity in autism. Autism Research 13: 32-44.

[J244] Du,J., Rolls, E. T., Cheng,W., Li,Y., Gong,W., Qiu,J. and Feng,J. (2020) Functional connectivity of the orbitofrontal cortex, anterior cingulate cortex, and inferior frontal gyrus in humans. Cortex 123: 185-199.

[J243] Rolls, E. T., Huang, C., Lin, C.-P.,Feng, J. and Joliot, M. (2020) Automated anatomical labelling atlas 3. NeuroImaging 206: 116189. AAL3

[J242] NingNing Ma, Edmund Rolls, and Jianfeng Feng (2020) Brain avalanche rate in fMRI dynamics is related to attention and ADHD NeuroImaging (under revision)

[J241] Jia TY et al. (2020) Neurobehavioural characterisation and stratification of reinforcement-related behaviour Nature Human Behaviour (accepted)

[J240*] Libo Wang t al. (2020) Two biotypes in Parkibsib's disease with distnictive longitudinal progression Neurology doi:10.1212/WNL.0000000000010498 Editorial

[J239*] chun Shen et al. (2020) Neural correlates of the dual pathway model for ADHD in adolescents American Journal of Psychiatry (accepted)

[J238*] chun Shen et al. (2020) What is the link between ADHD and sleep disturbance? A multimodal examination of logitudinal relationships and brain structure using large-scale population-based cohorts Biological Psychiatry (accepted)

[J237*] Lingli Zhang, Qiang Luo, et al., Fei Li, Jianfeng Feng (2020) Frontopolar grey matter volume mediates both genetic and environmental influences on overweight and obesity BMC Medicine (accepted)

[J236*] Jingnan Du, lena Palaniyappan, Zhaowen Liu, Wei Cheng, Weikang Gong, Mengmeng Zhu, Jijun Wang, Jie Zhang, Jianfeng Feng (2020) The genetic determinants of language network dysconnectivity in drug-native early stage schizophrenia NPJ Schizophrenia (accepted)


[P39] CY Tao, et al. (2019) On Fenchel Mini-Max learning NeuIPS (accepted)

[J235] Edmund Rolls, Chu-chung Huang, Ching-Po Lin, Jianfeng Feng, Marc Joliot (2019) Automated anatomical labelling atlas 3 NeuroImaging (accepted)

[J234] Limei Han et al. (2019) Surface-enhanced resonance Raman scattering-guided brain turmor surgery showing prognostic benefit in rat models Applied Materials and Interfaces Doi: 10.1021/acsami.9b00227

[P38] Liang Du, et al. (2019) SSF-DAN: Separated semantic feature vased domain adaption network for semantic segmentation ICCV (accepted)

[P37] Kai Wu, Bowen Du, Man Luo, Hongkai Wen, Yiran Shen, Jianfeng Feng (2019) Weakly supervised brain lesion segmentation via attentional representation learning MICCAI (accepted)

[J233*] Edmund T. Rolls; Wei Cheng; Matthieu Gilson; Weikang Gong; Gustavo Deco; Chun-Yi Zac Lo; Albert C. Yang; Shih-Jen Tsai; Mu-En Liu; Ching-Po Lin; Jianfeng Feng (2019) Beyond the disconnectivity hypothesis of schizophrenia Cerebral Cortex (accepted)


[P36] Zhang JP et al. (2018) GaitSet: Regarding Gait as a Set for Cross-View Gait Recognition AAAI-19 (accepted as Oral presentation)

[J232*] Wei Cheng, Edmund T. Rolls, et al., Jianfeng Feng (2018) Decreased brain connectivity in smoking contrasts with increased connectivity in drinking eLife , [Warwick News] , [Fudan News] , [XinHua News] which is viewed by more than a million people, a record high for our papers.

[P35] Junya Chen, Jianfeng Feng and Wenlian Lu (2018) A Wiener causality defined by relative entropy ICONIP 2018 (accepted and is awarded as The Best Student Paper)

[J231*] Qiang Luo, et al., Jianfeng Feng (2018) Voxel-wise and genome-wide assocation study reveals a volumetric association of a schizophrenia-associated nonsynonymous variant in putamen JAMA Psychiatry doi:10.1001/jamapsychiatry.2018.4126

[P34] Tao CY et al. (2018) Chi2 Generative Adverarial Netorks ICML 2018 (accepted)

[J230*] Wei Cheng, Edmund T. Rolls, Jianfeng Feng (2018) Brain mechanisms that mediate the relationship between depressive problems and sleep quality JAMA Psychiatry doi:10.1001/jamapsychiatry.2018.1941 (IF=16.6), [Daily Mail] , [Fudan News] , [Warwick News] , [TRT (Espanol)] , [People's Daily] , [TV] , [TV] and many others.

[J229*] Wei Cheng, Edmund T. Rolls, Jiang Qiu, Xiongfei Xie, Dongtao Wei, Chu-Chung Huang, Albert C. Yang, Shih-Jen Tsai, Qi Li, Jie Meng, Ching-Po Lin, Peng Xie, Jianfeng Feng (2018) Functional connectivity of the precuneus in unmedicated patients with depression Biological Psychiatry: CNNI (accepted)

[J228*] Rolls E et al. Jianfeng Feng (2018) Functional connectivity of the anterior cingulate cortex in depression and in health Cerebral Cortex (accepted)

[P33] Changmao Cheng, Yanwei Fu, Yu-Gang Jiang, Wei Liu, Wenlian Lu, Jianfeng Feng, Xiangyang Xue (2018) Dual Skipping Networks CVPR 2018 (accepted)

[J227*] Gong WK et al. Jianfeng Feng (2018) Identifying associations in dense connectomes using structured kernel principal component regression NeuroImage (under revision)

[J226*] Liu ZW et al. Jianfeng Feng (2018) Brain annotation toolbox: exploring the functional and genetic associations of neuroimaging results Bioinformatics (under revision)

[J225*] Yunyi Zhou, Jianfeng Feng (2018) An asymptotic theory for cross-correlation between auto-correlated sequences and its application on neuroimaging data J. Neuroscience Methods 10.1016/j.jneumeth.2018.04.009

[J224*] Lu Zhang, Richard Apps, Wei Cheng, Jie Zhang, Lena Palaniyappan, Longnian Lin, Jonathan C.W. Brooks, Zhi Geng, Wenlian Lu, Keith M. Kendricki, Jianfeng Feng (2018) Causal analysis of brain-wide dysconnectivity in Schizophrenia patients identifies the frontal cortex as the primary source Human Brain Mapping (under revision)

[J223*] Wei Cheng, Edmund T. Rolls, Jiang Qiu, Xiongfei Xie, Dongtao Wei, Chu-Chung Huang, Albert C. Yang, Shih-Jen Tsai, Qi Li, Jie Meng, Ching-Po Lin, Peng Xie, Jianfeng Feng (2018) Increased functional connectivity of the posterior cingulate cortex with the lateral orbitofrontal cortex in depression Translational Psychiatry (accepted)

[J222*] Zhaowen Liu, Jie Zhang, Kai Zhang, Wei Cheng, Junying Zhang, Paul M. Matthews, Jianfeng Feng (2018), Distinguishable brain networks relate disease susceptibility to symptom expression in schizophrenia, Human Brain Mapping NeuroImage, (in press)

[J221*] Zhaowen Liu, Jie Zhang, Xiaohua Xie, Edmund T. Rolls, Jiangzhou Sun, Zeyu Jiao, Qunlin Chen, Junying Zhang, Jiang Qiu, Jianfeng Feng (2018) Neural and genetic determinants of creativity NeuroImage ,

[J220*] Wei Cheng, Edmund T. Rolls, Jiang Qiu, Xiongfei Xie, Dongtao Wei, Chu-Chung Huang, Albert C. Yang, Shih-Jen Tsai, Qi Li, Jie Meng, Ching-Po Lin, Peng Xie, Jianfeng Feng (2018) Functional connectivity of the human amygdala in health and depression Social Cognitive and Affective Neuroscience (accepted)

[J219*] Jiangzhou Sun, Zhaowen Liu, Jie Zhang, Edmund T. Rolls, Qunlin Chen, Ye Yao, Wenjing Yang, Dongtao Wei, Jianfeng Feng, Jiang Qiu(2018) Verbal creativity correlates with the temporal variability of brain networks during the resting state Cerebral Cortex


[J218*] Qiang Luo, Yina Ma, Meghana A. Bhatt, P. Read Montague, and Jianfeng Feng (2017) The Functional Architecture of the Brain Underlies Strategic Deception in Impression Management Front. Hum. Neurosci., 02 November 2017 |

[J217] Xin Bai, Jian-an Jia, Meng Fang, Shipeng Chen, Xiaotao Liang£¨ Shanfeng Zhu, Shuqin Zhang, Jianfeng Feng, Fengzhu Sun, Chunfang Gao (2017) Deep Sequencing of HBV Pre-S Region Reveals High Heterogeneity of HBV Genotypes and Associations of Word Pattern Frequencies with HCC Plos Genetics (accepted)

[J216*] Edmund T. Rolls, Wei Cheng, Matthieu Gilson, Jiang Qiu, Zicheng Hu, Hongtao Ruan, Yu Li, Chu-Chung Huang, Albert C. Yang, Shih-Jen Tsai, Xiaodong Zhang, Kaixiang Zhuang, Ching-Po Lin, Gustavo Deco, Peng Xie Peng Xie, Jianfeng Feng (2017) Effective Connectivity in Depression Biological Psychiatry: Cognitive Neuroscience and Neuroimaging

[J214*] Liu, Z., Rolls, E. T., Zhang,J., Yang,M., Du,J., Gong,W., Cheng,W., Wang,H., Ugurbil,K,, Feng, J. (2017) The functional and genetic associations of neuroimaging data: a toolbox. BioRxiv

[J213*] Liu ZW et al. (2017). Brain Connectivity deviates by Sex and Hemisphere in the First Episode of Schizophrenia: a route to the genetic basis of language and psychosis? Schizophrenia Bulletin (under revision)

[J212] Li T et al. (2017). Functional connectivity in first-spisode and chronic stages of schizophrenia Schizophrenia Bulletin doi: 10.1093/schbul/sbw099

[J211*] Rolls, E. T., Lu,W., Wan,L., Yan,H., Wang,C., Yang,F., Tan,Y.L., Li,L., Chinese Schizophrenia Collaboration Group, Yu,H., Liddle,P.F., Palaniyappan,L., Zhang,D., Yue,W. and Feng,J. (2017). Individual differences in schizophrenia British Journal of Psychiatry Open (in press)

[J210*] Weikang Gong, Lin Wan, Wenlian Lu, Liang Ma, Fan Cheng, Wei Cheng, Stefan Gr®Ļnewald, and Jianfeng Feng (2017). Statistical testing and power analysis for brain-wide association study Medical Image Analysis (under revision)

[J209*] Wanlu Deng; Edmund T. Rolls; Xiaoxi Ji; Trevor W. Robbins; et al. Jianfeng Feng. (2017). Separate neural systems for behavioral change and for emotional responses to failure during behavioral inhibition Human Brain Mapping (in press)


[J208*] Wei Cheng; Edmund Rolls; Jie Zhang; Wenbo Sheng; Liang Ma; Lin Wan; Qiang Luo; Jianfeng Feng (2016). Functional connectivity decreases in autism in emotion, self, and face circuits identified by Knowledge-based Enrichment Analysis NeuroImage doi: 10.1016/j.neuroimage.2016.12.068, software package is coming soon

[J207*] Wei Cheng; Edmund T. Rolls; Jiang Qiu; Wei Liu; Yanqing Tang; Chu-Chung Huang; XinFa Wang; Jie Zhang; Wei Lin; Lirong Zheng; JunCai Pu; Shih-Jen Tsai; Albert C Yang; Ching-Po Lin; Fei Wang; Peng Xie; Jianfeng Feng(2016). Medial reward and lateral non-reward orbitofrontal cortex circuits change in opposite directions in depression Brain doi: 10.1093/brain/aww255, [Psychology Today] , [Fudan news] , [Warwick news] , [BBC Focus] , [Successful rTMS treatment]

[J206*] CY Tao, JF Feng (2016). Canonical kernel dimension reduction Computational Statistics and Data Analysis Volume 107, March 2017, Pages 131--148

[P33] Nicola Politi, Jianfeng Feng and Wenlian Lu (2016). Comparing filtering data assimilation methods for parameter estimation in single neuron model ICNN (in press)

[J205*] Zhang J. et al. (2016). Functional connectivity in first-spisode and chronic stages of schizophrenia Schizophrenia Bulletin doi: 10.1093/schbul/sbw099, IF=8.45

[J204*] Chenyang Tao; Thomas E Nichols; Hua Xue; Christopher R Ching; Edmund T Rolls; Paul Thompson; Jianfeng Feng (2016). Generalized reduced rank latent factor regression for high dimensional tensor fields, and neuroimaging-genetic applications NeuroImage

[J203*] Jie Zhang, Wei Cheng, Zhaowen Liu, Xu Lei, Ye Yao, Ben Becker, Yicen Liu, Keith Kendrick, Guangming Lu, Jianfeng Feng (2016). Neural, electrophysiological and anatomical basis of brain-network variability and its characteristic changes in mental disorders Brain doi: 10.1093/brain/aww143 [Scientific Commentary from Bassett DS] , [Daily Mail] , [Chinese version] , [Warwick News] , [Journal Cover story] , [Front page in GuangMing Daily] and many others.

[J202*] Shuixia Guo, Lena Palaniyappan, Peter F. Liddle, Jianfeng Feng (2016). Dynamic Cerebral Reorganisation in the Pathophysiology of Schizophrenia: A MRI derived Cortical Thickness Study Psychological Medicine doi:10.1017/S0033291716000994 [Forbes news] [Chinese version]

[J201*] Q Wang, et al. (2016). The CHRM3 gene is implicated in abnormal thalamo-orbital frontal cortex functional connectivity in first-episode treatment-naive patients with schizophrenia Psychological Medicine (accepted), IF=5.9

[J200*] Weidan Pu, Qiang Luo et al. (2016). Failed cooperative, but not competitive, interaction between large-scale brain networks impairs working memory in schizophrenia Psychological Medicine doi:10.1017/S0033291715002755

[J199]* CY Tao, Jianfeng Feng (2016). Nonlinear Association Criterion, Nonlinear Granger Causality and Related Issues with applications to Neuroimage Studies J. Neurosci Methods doi:10.1016/j.jneumeth.2016.01.003 NAC

[J198*] Huiru Cui, Jie Zhang, et al. (2016). Differential alterations of resting-state functional connectivity in generalized anxiety disorder and panic disorder Human Brain Mapping DOI: 10.1002/hbm.23113

[J197] Jia TY, et al. (2016). The neural basis of reward anticipation and its genetic determinants PNAS vol. 13, no. 14, 3879-3884


[J196] KC Kadosh et al. (2015). Using real-time fMRI to influence differential effective connectivity in the adolescent emotion regulation network NeuroImage , doi:10.1016/j.neuroimage.2015.09.070

[J195] Shamsideen A. Ojelade, et al. (2015). Rsu1 Regulates Ethanol Consumption in Drosophila and Humans PNAS , doi:10.1073/pnas.1417222112

[J194]* Yao Y, et al. Jianfeng Feng (2015). Variability of structurally constrained and unconstrained functional connectivity in schizophrenia Human Brain Mapping DOI: 10.1002/hbm.22932

[J193]Jiewei Liu, Bing Su, Yin Mo, Tian Ge, Yi Wang, Xiong-jian Luo, Jianfeng Feng, Ming Li,, Bing Su(2015). Allelic Variation at 5-HTTLPR is Associated with Brain Morphology in a Chinese Population Psychiatry Research (accepted)

[J192]* Xinjun Gan, Bing Xua, Xiaoxi Jia, Wenlian Lu, David Waxmana, Jianfeng Feng (2015). A Statistical Approach for Detecting Common Features J. Neurosci Methods doi:10.1016/j.jneumeth.2015.02.010

[J191]* Cheng W, et al. Jianfeng Feng (2015). Voxel-based, brain-wide association study of aberrant functional connectivity in schizophrenia implicates thalamocortical circuitry Nature Partner Journal Schizophrenia , doi:10.1038/npjschz.2015.16, Supplementry materials; Featured Article

[J190]* Cheng W, Rolls ET, Gu HG, Zhang J, Jianfeng Feng (2015). Autism: Reduced Connectivity between Cortical Areas Involved in Face Expression, Theory of Mind, and the Sense of Self, Brain vol. 138; 1382--1393, doi: 10.1093/brain/awv051, Suppl. Materials, IF=10.3, Editor's Choice, , Warwick Press Release, Fudan News, Many others, for example [1] , Many others, for example [2]

[J189] Shuixia Guo, Sarina Iwabuchi, Vijender Balain, Jianfeng Feng, Peter Liddle, and Lena Palaniyappan (2015). Cortical folding and the potential for prognostic neuroimaging in schizophrenia B J Psychiatry doi:10.1192/bjp.bp.114.155796, IF=7.3


[J188]* Zhang J, Kendrick KM, Lu GM Jianfeng Feng (2014). The fault lies on the other side: altered brain functional connectivity in psychiatric disorders is mainly caused by counterpart regions in the opposite hemisphere Cerebral Cortex doi:10.1093/cercor/bhu173, IF=8.3

[J187]* Gong XH, Lu WL, Kendrick KM, Pu WD, Wang C, Jin L, Liu ZN, Jianfeng Feng (2014). A Brain-wide Association Study of DISC1 Genetic Variants Reveals a Relationship with the Structure and Functional Connectivity of the Precuneus in Schizophrenia Human Brain Mapping doi:10.1002/hbm.22560, IF=6.9.

[J186] Sylvane Desrivieres, et al. Jianfeng Feng, Gunter Schumann (2014). Single nucleotide polymorphism in the neuroplastin locus associates with cortical thickness and intellectual ability in adolescents Molecular Psychiatry doi:10.1038/mp.2013.197, IF=15.

[J185]* Pu WD et al. (2014) Altered Functional Connectivity Links in Neuroleptic-na?ve and Neuroleptic-treated Patients with Schizophrenia, and their Relation to Symptoms Including Volition, NeuroImaging, IF=6.5, (in press)

[J184] Tian Ge, Xiaoying Tian, J®Ļrgen Kurths, Jianfeng Feng, and Wei Lin (2014) Achieving modulated oscillations by feedback control Phys. Rev. E , 90, 022909

[J183] Yu, Y., Karbowski, J., Sachdev, R.N.S., Feng, J.(2014) Effect of temperature and glia in brain size enlargement and origin of allometric body-brain size scaling in vertebrates BMC Evolutionary Biology , 14 (1), article no. 178

[J182] Cao, L., Guo, S., Xue, Z., ..., Chen, E.Y., Liu, Z.(2014) Aberrant functional connectivity for diagnosis of major depressive disorder: a discriminant analysis. Psychiatry and clinical neurosciences , 68 (2), pp. 110-119

[J181] Z., Zhang, Z., Liao, W., (...), Feng, J., Lu, G. (2014) Frequency-dependent amplitude alterations of resting-state spontaneous fluctuations in idiopathic generalized epilepsy Epilepsy Research , 108 (5), pp. 853-860


[J180] T Ge, G Schumann, Jianfeng Feng (2013). Imaging Genetics: towards a discovery neuroscience Quantitative Biology (pdf version) 2013, Vol. 1 Issue (4) : 227-245 DOI: 10.1007/s40484-013-0023-1.

[J179]* Shuixia Guo, Lena Palaniyappan, Bo Yang, Zhening Liu, Zhimin Xue, Jianfeng Feng (2013). Anatomical distance affects functional connectivity in patients with schizophrenia and their siblings Schizophrenia Bulletins doi:10.1093/schbul/sbt163, IF=8.5.

[J178]* Lu WL, Feng JF , Waxman D, and Amari SI (2013). Achieving precise mechanical control in intrinsically noisy systems New J. Physics vol. 15: 063012., IF=4.1.

[J177]* Y. Yao, WL. Lu, B. Xu, CB. Li, CP. Lin, D. Waxman, and JF. Feng (2013). The Increase of the Entropy of the Human Brain with Age Scientific Report 3: 2583.

[J176] Loth E. et al. Feng JF , Schumann G. (2013). Effect of oxytocin receptor gene variants and stressful experiences on ventral striatal activity and risk for social-affective problems Biol. Psychiatry doi:10.1016/j.biopsych.2013.07.043, IF=9.2

[J175]* Luo Q et al. (2013). Attention-dependent modulation of cortical taste circuits revealed by Granger causality with signal-dependent noise PLoS Comp Biol vol. 9 (10): e1003265, DOI: 10.1371/journal.pcbi.1003265 , IF=5.3.

[J174]* Guo SX, Kendrick KM, Zhang J., Broome M., Liu ZN, Feng JF (2013). Brain-wide functional inter-hemispheric disconnection is a biomarker for schizophrenia and distinguishes it from depression NeuroImage DOI: 10.1016/j.nicl.2013.06.008. supplemental materials

[J173] Li M, Ge T, Feng JF , Su B. (2013). SLC6A15 rs1545853 and depression: implications from brain imaging data American Journal of Psychiatry vol: 170:805,10.1176/appi.ajp.2013.12111458. supplemental materials , IF=14. [ News_1 ], [ News_2 ]

[P32] Leng G, Feng JF (2013). Modelling the Milk-Ejection Reflex Computational Endocrinology (in press).

[J172]* Guo SX, Yu Y, Zhang J, Feng JF (2013). A reversal coarse-grained analysis with applications to a circuit of superior frontal gyrus, insula and putamen in depression Brain and Behaviour DOI: 10.1002/brb3.173, IF=4.9.

[J171]* Qiang Luo, Wenlian Lu, Wei Cheng, Pedro A Valdes-Sosa, Xiaotong Wen, Mingzhou Ding, Feng JF (2013). Spatio-temporal Granger causality: a new framework NeuroImage 79: 241--263 Software, IF=5.9.


[J170]* SX Guo, KM Kendrick, RJ Yu, WY Isaac Tseng, Feng JF (2012). Key functional circuitry altered in schizophrenia involves parietal regions associated with sense of self Human Brain Mapping DOI: 10.1002/hbm.22162.

[J169] Michael David Forrest; Mark J Wall; Daniel A Press; Feng JF (2012). The Sodium-Potassium Pump Controls the Intrinsic Firing of the Cerebellar Purkinje Neuron PLoS One 7(12): e51169. doi:10.1371/journal.pone.0051169

[P31] Zhang XJ; Jianfeng Feng(2012). Computational modelling of neuronal networks Encyclopedia of Biophysics -- Computational modelling of neuronal networks (in press).

[J168] Tian Ge; Jianfeng Feng; Derrek Hibar; Paul Thompson; Thomas Nichols (2012). Increasing Power for Voxel-wise Genome-wide Association Studies: The Random Field Theory, Least Square Kernel Machines and Fast Permutation Procedures NeuroImage vol. 63: 858-873

[J167]* Luo Q., Bhatt MA, Montague PR, Feng JF (2012). Goal-dependent modulatino of effective connectivity during a two-party bargaining game (supplemental materials) J. Neurosci (resubmitted).

[J166] Wei Cheng, Jie Zhang, Xiaoxi Ji, Feng JF (2012).Individual classification of ADHD patients by integrating multiscale neuroimaging markers and advanced pattern recognition techniques Frontiers in Systems Neuroscience 06 August 2012 | doi: 10.3389/fnsys.2012.00058.

[J165]* Y. Wu, W.L. Lu , W. Lin, G. Leng, Feng JF (2012). Bifurcations of emergent bursting in a neuronal network PLoS One 7(6): e38402. doi:10.1371/journal.pone.0038402.

[J164]* Zhang J, Zhang XJ, Wang ZG, Zhang ZQ, Lu WL, Lu GM,, Feng JF (2012). Pattern classification of large-scale functional brain networks: identificaiton of informative neurobiological markers for epilepsy PLoS One 7(5): e36733. doi:10.1371/journal.pone.0036733.

[J163]* Zhang XJ, et al., Feng JF (2012). A Computational Study on Theta/Gamma Dual Oscillations in Learning and Phase Coding PLoS One June 2012 | Volume 7 | Issue 6 | e36472.

[J162]* Dimitris Vavoulis; Volko A. Straub, John A.D. Aston, Feng JF (2012). A self-organising state-space-model approach for parameter estimation in Hodgkin-Huxley-type models of single neurones PLoS Comp. Biol. Volume 8 | Issue 3 | e1002401. cover image

[J161]Yang B., Liu JM, Feng J.F.(2012) On the spectral characterization and scalable mining of network communities IEEE T. Knowledge and Data Engineering (submitted vrsion); Journal version vol. 24:326-337.


[J160]* HJ Tao, SX Guo, T Ge, KM Kendrick, ZM Xue, ZN Liu, JF Feng (2011). Depression Uncouples Brain Hate Circuit Molecular Psychiatry doi:10.1038/mp.2011.127 [Suppl. materials] , Nature Publishing Group Pess Release , CNN news , Daily Mail , Time , MSN , ScienceDaily , Scientific American , XinHua, MarcoDaily, SoHu, Chinese Youngth Daily, Sina, China Daily, XinMinNews, 163, Easter network Chinese People's Radio, ifeng, KeXueWang, WenHuiBao, GuangMingRiBao, More than 1000 others around the world. (IF=15.5), Most viewed paper in the Journal, 2012 Newspaper of the American Psychiatric Association

[J159]* T Ge; JF Feng; F Grabenhorst; E Rolls (2011). Componential Granger causality, and its application to identifying the source and mechanisms of the top-down biased activation that controls attention to affective vs sensory processing NeuroImage doi:10.1016/j.neuroimage.2011.08.047. (IF=5.9)

[J158]* Luo Q, Ge T, Feng JF (2011). Causality with signal-dependent noise NeuroImage vol. 57: 1422-1429. doi: 10.1016/j.neuroimage.2011.05.054. (IF=5.9)

[J157] Webb T, Rolls E, Deco G, Feng JF (2011). Noise in the brain produced by graded firing rate representations PLoS One 6(9): e23630.

[P30]* Ge T, Feng JF (2011). Granger Causality: Its Foundation and Applications in Systems Biology Handbook of Research on Computational and Systems Biology Editor(s): Limin Angela Liu, Dongqing Wei, Yixue Li, and Huimin Lei; pp 511-532.

[J156]* Kang J, Xu B, Hennessy C, Fraser P., Feng JF (2011). A Dynamical Model Reveals Gene Colocalizations in Nucleus PLoS Comp. Biol. 7(7): e1002094. doi:10.1371/journal.pcbi.1002094 .

[J155] Erokhin V, Berzina T, Camorani P, Smerieri A, Vavoulis D, Feng JF , and M.P. Fontana (2011). Material Memristor Circuits with Synaptic Plasticity: Learning and Memory (accepted).

[J154]* Keith M Kendrick, Yang Zhan, Hanno Fisher, Alister U Nicol, Xuejuan Zhang and Feng JF (2011). Learning alters theta amplitude, theta-gamma coupling and neuronal synchronization in inferotemporal cortex BMC Neuroscience 12:55 (highly accessed).

[J153] W. Lin, T. Ge and Feng JF (2011). Invariance Principles Allowing of Non-Lyapunov Functions for Estimating Attractor of Discrete Dynamical Systems IEEE T. on Automatic Control (accepted).

[J152] Durrent S., Kang YM, Stocks NJ, J.F. Feng, (2011). Suprathreshold Stochastic Resonance in Neural Processing Tuned By Correlation PRE vol. 84: 011923


[J151] Zhang J., Zhang K, Feng JF , Small M. (2010). Understanding Rhythmic Dynamics and Synchronization in Human Gait through Dimensionality Reduction PLoS Comp. Biol. 6(12): e1001033. (selected as Featured Research,IF=5.9).

[J150]* Smerieri A, Rolls ET, J.F. Feng,, (2010). Decision time, slow inhibition, and theta rhythms J. Neurosci. vol. 30: 14173-14181 (IF=7.5).

[J149] Ma HF, Xu B, Lin W J.F. Feng,, (2010). Adaptive identification of time delays in nonlinear dynamical models PRE 82:066210.

[J148]* E. Rossoni, J. Kang, Feng J.F. (2010) Controlling precise movement with stochastic signals, Biol. Cybern. vol. 102:441-450. DOI: 10.1007/s00422-010-0377-7.

[J147] D Vavoulis, ES Nikitin, I Kemenes, V Marra, J.F. Feng,, P. R. Benjamin and G. Kemenes, (2010). Balanced plasticity and stability of the electrical properties of a molluscan modulatory interneuron after classical conditioning: a computational study Frontiers in Behaviour Neuroscience 5: 4-19.

[J146] V Marra, I Kemenes, D Vavoulis, J.F. Feng, M O'shea and PR. Benjamin (2010). Role of tonic inhibition in associative reward conditioning in Lymnaea Frontiers in Behaviour Neuroscience doi:10.3389/fnbeh.2010.00161

[P29]* SX Guo, C Ladroue and J.F. Feng,, (2010). Granger causality: theory and applications Frontiers in Computational and Systems Biology, Computational Biology, 2010, Volume 15, 83-111, DOI: 10.1007/978-1-84996-196-7_5.

[P28] Kendrick KM J.F. Feng,, (2010). Neural encoding principles in face perception revealed using non-primate models Handbook of Face Perception Oxford University Press, ed. Calder AJ, Rhodes G, Johnson MH, and Haxby JV (in press).

[J145] Lin W, Ma HF, J.F. Feng,, Chen GR (2010). Locating unstable periodic orbits: When adaption meets feedback PRE vol. 82: 046214 .

[P27]* Lu WL J.F. Feng,, (2010). On Gaussian Random Neuronal Field Model: Moment Neuronal Network Approach IJCNN2010 (in press).

[P26]* Ge T, Lu WL, J.F. Feng,, (2010). Find Synaptic Topology from Spike Trains Neural Networks (IJCNN), The 2010 International Joint Conference on Digital Object Identifier: 10.1109/IJCNN.2010.5596299, Page(s): 1 - 6 .

[J144]* Zou ZL, Ladroue C, Gou SX J.F. Feng,, (2010). Indentifying interactions in the time and freqeuncy domains in local and global networks BMC Bioinformatics vol. 11: 337, (IF =3.4).

[J143]* Kang J, Robinson HPC, J.F. Feng,, (2010). Minimal mechanism for decoding input temporal frequencies -modelling and experimental approach PLoS One 5(3):e9608, (IF=4.3)

[J142]* Kang J, Wu JH, Smerieri A, J.F. Feng,, (2010). Weber's Law Implies Sub-Poisson Neural Discharge Eur. J. Neurosci. vol. 36: 1006-1018. (IF=3.4).

[J141]* Lu W.L., Rossoni E., J.F. Feng,, (2010). Toward a theory of random neuronal field model NeuroImage vol. 52, pp. 913-933; doi: 10.1016/j.neuroimage.2010.02.075, (IF=5.7).

[J140]* Zhang XJ, Leng G., J.F. Feng,, (2010). Coherent Peptide-mediated Brain Activities of Neuronal Networks Controlled by Subcellular Signaling Pathway: Experimental and Modelling Results J. Biotechnology 10.1016/j.jbiotec.2010.01.003, vol. 149:215-225 (IF=2.7).


[J139]* Ge T., Kendrick K., J.F. Feng,, (2009). A Unified Dynamic and Granger Causal Model Approach Demonstrates Brain Hemispheric Differences During Face Recognition Learning PLoS Comp. Biol. 5(11): e1000570. doi:10.1371/journal.pcbi.1000570.(IF=5.9).

[J138]* Wu** JH, Sinfield** J.L., J.F. Feng, (2009). Impact of Environmental Inputs on Reverse-Engineering Approach to Network Structures BMC Systems Biology 3:113 (**=co-first author, IF=3.7).

[J137]* C.Ladroue**, SX Guo**, K. Kendrick, J.F. Feng, (2009). Beyond element-wise interactions: defining group-to-group interactions for biological processes PLoS One , 4(9): e6899. doi:10.1371/journal.pone.0006899, **=co-first author.

[J136]* Zou CL, Kendrick KM, Feng JF (2009) The Fourth Way: Granger Causality is better than the three other Reverse-engineering Approaches , COMMENTS ON Cell, 3 April 2009, A Yeast Synthetic Network for In Vivo Assessment of Reverse-Engineering and Modeling Approaches Cell, vol. 137: 172-181.

[J135] I. Ashmole, D.V. Vavoulis, P.J. Stansfeld, J.F. Feng, M.J. Sutcliffe, P.R. Stanfield (2009). The response of the tandem pore potassium channel TASK-3 (K2P9.1) to voltage: gating at the cytoplasmic mouth J. Physiology , 587.20: 4769-4783, doi: 10.1113/jphysiol.2009.175430. Cover Image (IF=4.6)

[J134]* Kendrick KM, Y Zhan, H Fischer, A U Nicol, XJ Zhang, Feng J.F. (2009) Learning alters theta-nested gamma oscillations in inferotemporal cortex Nature Precedings hdl: 10101/ npre. 2009.3151.1.

[J133]* Zou CL, Feng J.F. (2009) Granger causality vs. Dynamic Bayesian network inference: A Comparative Study BMC Bioinformatics vol. 10:122 doi:10.1186/1471-2105-10-122. ( most viewed paper in past 30 days in the journal, flagged as 'highly accessed paper', IF=3.8)

[J132]*Feng J.F. Yi DY, Krishna R, Guo SX, Buchanan-Wollaston V.(2009) Listen to genes: dealing with microarray data in the frequency domain PLoS One 4(4): e5098. doi: 10.1371 / journal.pone. 0005098.

[J131]* Zhang XJ,You GQ, Chen TP, Feng J.F. (2009) Readout of spike waves in a microcolumn Neural Computation ,vol. 21, 3079-3105 (IF=2.2).

[J130]Li YQ ,Namburi P,Yu ZL, Guan CT,Feng J.F., Gu ZH (2009) Voxel selection in fMRI data analysis based on sparese representation IEEE T. Biomedical Engineering vol. 56, 2439-2451 (IF=1.6).

[J129]Feng J.F.,Shcherbina M, Tirozzi B  (2009)Stability of the dynamics of an asymmetric neural network Commun. on Pure and Applied Analysis vol. 9: 655-671


[J128]* Guo SX, Wu J.F.H.,  Ding MZ, Feng J.F.(2008) Uncovering interactions in the frequence domain PLoS Comput Biol 4(5): e1000087. doi:10.1371/journal.pcbi.1000087 (selected as Featured Research, IF=6.2).

[J127]* Rossoni E., Feng J.F.,   Tirozzi B., Brown D., Leng G., and Moos F. (2008) Synchronous bursting of oxytocin neurons; emergent behaviour of a model, PLoS Comp. Biol. 4(7): e1000123. doi:10.1371/journal.pcbi.1000123 (see also BBC News , Washington Post , Scientific American , Reuters , BBC Radio 4 , Daily Telegraph , Daily Mail , National Post (Canada) , ANSA (in Italy) , Newstrack (India) , Science Daily , National Post (Canada) , Shanghai Daily , Malaysian Daily Star , Mexico , Chile I Think , Spain , Warwick Univ. , +more than 100 others , IF=6.2) Link to Scholarpedia .

[J126]* Zhou.C, Bowler L. Feng J.F.   (2008) A machine learning approach to explore the spectra intensity pattern of peptides using tandem mass spectrometry data BMC Bioinformatics 9: 325 (flagged as 'highly accessed paper', IF=3.5)

[J125]ES Nikitin, DV Vavoulis,Feng J.F.,M O’Shea, PR Benjamin & G Kemenes(2008) Persistent sodium current is a non-synaptic substrate for long-term memory Current Biology vol. 18: 1221-1226 (IF=10.5), also selected in F1000 Biology

[J124]Qian M., Zhang XJ, Wilson R., Feng J.F.   (2008) Efficiency of Brownian motors in terms of entropy production rate Europhys. Letts. vol. 84, 10014 (IF=2.2)

[J123]Guo SX, A. Seth, K. Kendrick, Feng J.F. (2008) Partial Granger causality: eliminating exogenous inputs and latent variables, J. Neurosci. Methods , vol. 172: 79-83 (IF=1.8)

[J122]Zhan Y, Guo SX, Kendrick K., and Feng J.F. (2008)  Filtering Noise for Synchronised Activity in Multi-trial Electrophysiology Data using Wiener and Kalman filters Biosystems vol. 96: 1-13.

[J121]Feng J.F.Shcherbina M, Tirozzi B  (2008) Stability of the dynamics of an asymmetric neural network Commun. on Pure and Applied Analysis vol. 7: 249-265.

[J120]* P. Rowcliffe, Feng J.F. (2008)Training Spiking Neuronal Networks With Applications in Engineering Tasks IEEE T. NN, vol. 19:1626-1640, (IF=2.7)


[J119]Wu J.H., Liu XG., Feng J.F. ??2007) Detecting causality between different frequencies, J. Neuroscience Methods 167:367-375.

[P25]Wu J.H., Liu XG., Feng J.F. ¬†(2007) Moment neuronal networks: stochastic computation in neuronal systems - art. no. 66021E, Noise and Fluctuations in Biological, Biophysical, and Biomedical Systems šłõšĻ¶: PROCEEDINGS OF THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS (SPIE) vol.: 6602, page: E6021-E6021.

[J118]Wu J.H, Kendrick K., Feng J.F. (2007)Detecting Hot-Spots in Multivariates Biological Data, BMC Bioinformatics 8:331. doi:10.1186/1471-2105-8-331

[J117]Vavoulis DV, Straub VA, Kemenes I, Feng J.F., Benjamin P.(2007)   Dynamic control of a central pattern generator circuit: a computational model of the snail feeding network, European Journal of Neuroscience;   25(9): 2805-2818

[J116]Feng J.F.,   Shcherbina M, Tirozzi B, You GQ (2007) Optimal movement control models of Langevin and Hamiltonian types Mathematical and Computer Modelling  46: (5-6): 680-698.

[J115]Huang CX, Huang LH, Feng J.F.,   et al.(2007) Hopf bifurcation analysis for a two-neuron network with four delays; Chaos, Solitons and Fractal, 34 (3): 795-812.

[J114]Williams P, Li S, Feng J.F.,   Wu S (2007) A geometrical method to improve performance of the support vector machine IEEE T on Neural Networks   18 (3): 942-947.

[J113]Wang S, Chen Y, Ding M, Feng J.F. et al. (2007) Revealing the dynamic causal interdependence between neural and muscular signals in Parkinsonian tremor J. of Franklin Institute-Engineering and Applied Mathematics   344(3-4): 180-195.

[J112]Wu JH, Kendrick K, Feng J.F.   (2007) Detecting correlation changes in electrophysiological data J.  Neuroscience Methods   161(1): 155-165.

[J111]Horton PM, Nicol AU, Kendrick KM, Feng J.F.   (2007) Spike sorting based upon machine learning algorithms (SOMA) J. Neuroscience Methods   160(1): 52-68.

[J110]Rossoni E, Feng J.F. (2007)   Decoding spike train ensembles: tracking a moving stimulus Biol. Cybern.   96(1): 99-112.


[J109]Zhan Y.Halliday D, Liu XG, and Feng J.F. (2006) Detecting the time-dependent coherence between non-stationary electrophysiological signals --A combined statistical and time-frequency approach (software homepage), J. Neurosci. Methods vol. 156, 322-332.

[J108]Durrant S, and Feng J.F. (2006) Negatively-correlated firing: the functional meaning of lateral inhibition within cortical columns, Bio. Cyber. vol.95, 431-453

[J107]Horton PM,Nicol AU, Kendrick KM, and Feng J.F.(2006) Spike sorting based upon machine learning algorithms (SOMA), J. Neurosci Methods vol.160, 52-68.

[J106]Xiang XY, Yang XQ, Deng YC, and Feng J.F.(2006) Identifying transition rates of ionic channels of star-graph branch type J. Phys. A vol .39: 9477-9491.

[J105]Feng J.F.,Jirsa V., and Ding M.Z. (2006) Synchronization in networks with random interactions: theory and applications Chaos 16, 015109.

[J104]Gaillard B., Buxton H., and Feng J.F. (2006) Population Approach to a Neural Discrimination task Bio.Cyber vol. 94, pages: 180-191.

[J103]Feng J.F.,Deng Y.C., and Rossoni E. (2006) Theory of moment neuronal networks, Phys. Rev. E vol. 73, no. 4,


[J102]Rossoni E, Chen YH, Ding MZ, and Feng J.F. (2005) Stability of synchronous oscillations in a system of HH neurons with delayed diffusive and pulsed coupling Phys. Rev. E vol. 71,061964.

[J101]Rossoni E, and Feng J.F. (2005) Non-parametric approach to extract information from interspike intervals J. Neurosci. Methods(software ) vol. 150, 30-40.

[J100]Rowcliffe P.,Feng J.F. , and Buxton H. (2005) Spiking perceptrons, IEEE T NN vol.17,803-807.

[J99]Waxman D, and Feng J.F. (2005) Implications of long tails in the distribution of mutant effects Physica D vol. 206: 265-274.

[J98]P.M. Horton, L. Bonny, A.U. Nicol, K.M. Kendrick and Feng J.F. (2005), Applictions of multi-variate analysis of variances (MANOVA) to multi-electrode array data, (Software home page)J.F. Neurosci. Meth. vol. 146, 22-41.

[J97] Feng J.F., and Liu W.B.(2005) Sufficient and necessary condition for the convergence of stochastic approximation algorithms Statistics and Probability Letters(accepted)

[J96]Rossoni E.,Leng G.,and Feng J.F. (2005) Modelling the milk-ejection reflex, Neurocomputing (in press).

[J95]Gaillard B.and Feng J.F. (2005) Modelling a Visual Discrimination Task, Neurocomputing 55-66,203-209.

[J94]Lee K.W., Buxton H., and Feng J.F. (2005) Cue-guided search: a computational model of selective attention, IEEE T??NN vol 16, 910-924

[J93]Feng J.F., Ferraro E., and Tirozzi  B. (2004) Impact of temperature and pH value on the stability of hGHRH: an MD approach, Applied Mathematics Letters,vol. 41, 1157-1170


[J92]Albo Z., Di Prisco G.V., Chen Y.H., Rangarajan G., Truccolo W., Feng J.F., Vertes R., and Ding M.Z.  Is partial coherence a viable technique for identifying generators of neural oscillations Bio. Cyber. Vol. 90, 318-326.

[J91]Chen YH, Rangarajan G., Feng J.F. and Ding M.Z. Analyzing multiple nonlinear time series with extended Granger causality, Phys. Lett. A, vol. 324, 26-35.

[J90]Li G.B., and Feng J.F.(2004) Stimulus-evoked synchronization in neuronal models Neurocomputing, vol 58-60, 203-208.

[J89]Feng J.F. , Chen X.J., Tuckwell H.C., and Vasilaki E. (2004) Some optimal stochastic control problems in neuroscience‚ÄĒA Review, Modern Physics Letters B,(invited review, in press)

[J88]Waxman D., and Feng J.F. (2004) Application of a generalised Levy residence time problem to neuronal dynamics Europhysics Letters,vol.65, 434-439.

[J87]Deng Y.C., Ding M.Z., and Feng J.F. (2004) Synchronization in stochastic coupled systems, J. Phys. A. vol. 37, 2163-2173.

[J86]Rossoni E.,  Leng G.,  and Feng J.F. (2004) Modelling phasic firing in vasopressin neurones (CNS'03, oral presentation), Neurocomputing

[J85]Feng J.F. and M.Z.Ding (2004) Reading spikes in a spiking neuronal network (movie) J. Phys. A vol. 37, 5713-5728.

[J84]Feng J.F. and Brown D(2004) Decoding input signals in time domain--A model approach, J. Comp. Neurosci. vol. 16, 237-249.

[J83]Feng J.F.,Tartaglia G.,and Tirozzi B. (2004) A note on the minimum variance theory and beyond J. Phys. A  vol. 37,4685-4700.


[J82]Feng J.F.,and Tuckwell H.C.(2003)Optimal control of neuronal activity (2003), Phys. Rev. Letts. vol. 91, 018101

[J82+]Feng J.F.,and Tuckwell H.C.(2003) Optimal control of neuronal activity (2003), Detailed Proof of Theorem 1 in [84]

[J81]Feng J.F.,and Li G.B.(2003) Relationships between spiking rates and calcium concentrations during stochastic synaptic inputs  J. Theoretical Biology, vol 223, 367-375.

[J80]Feng J.F.,Zhang K.W., and Luo Y. (2003), A study on an optimal movement model J. Phys. A., vol. 36, 7469-7484.

[J79]Vasilaki H., Feng J.F., and Buxton H. (2003) Temporal Album, IEEE T Neural Networks, vol. 14. No. 3,439-443.

[J78]Deng Y.C., Peng SL, Qian MP,  and Feng J.F.(2003) Identifying transition rates of ion channels via observations of a single state  J. Phys A vol. 36, 1159-1212.

[J77]Davison A.P., Feng J.F., and Brown D (2003) Dendrodendritic inhibition and odour-induced synchronization in a detailed olfactory bulb model, J. Neurophysiology vol. 90, 1921-193.

[J76]Liu F, Feng J.F.,  and Wang W. (2003) Impact of Poisson synaptic inputs with a changing rate on weak signal processing, Europhysics Letters, vol 64, 131-136.

[J75]Feng J.F.(2003) Effects of correlated and synchronized stochastic inputs to leaky integrator neuronal model  J.  Theoretical Biology, vol. 222,151-162.

[J74]Feng J.F.(2003) LNCS, vol. 2686, 62-69.

[J73]Deng Y.C.,Williams P.,Liu F. and Feng J.F. (2003) Neuronal discrimination capacity  J. Phys. A  vol. 36, no. 50,12379-12398.


[J72]Feng J.F., and Zhang K.W. (2002) Towards A Mathematical Foundation of Minimum-variance Theory J. Phys. A vol 35, 7287-7304.

[J71]Wei G., Clifford P., and Feng J.F. (2002) On Cox processes driven by interacting Feller diffusions and death sequences of immigration-emigration linked population networks J. Phys A  vol.35, 9309-9331.

[J70]Clifford P.,  Green N.J.F.B.,  Feng J.F., and Wei G. (2002) Probability representations of a class of two-way diffusions, J. Phys. A vol.35, 5795-5805.

[J69] Feng J.F.,Buxton H. (2002) Training the integrate-and-fire model with the Informax principlie I, J. Phys. A vol. 35: 2379-2394

[J68]Feng J.F.,Sun Y.L., Buxton H. (2003) Training the integrate-and-fire model with the Informax principlie II  IEEE T. NN,  vol 14, no.2.

[J67]Feng J.F.,Liu F.(2002) A modelling study on discrimination tasks, Biosystems (pdf file) vol 67,  67-73.

[J66] Feng J.F. and Li  G. (2002) Impact of geometrical structures on the output of neuronal models - a theoretical and numerical analysis Neural Computation vol. 14 (3) 621-640.

[J65]Rowcliffe P., Feng J.F., and Buxton H.(2002) Clustering within Integrate-and-Fire Neurons for Image Segmentation,  LNCS  vol. 2415, 69-74.

[J64]Feng J.F.  Training neuron models withth e Informax principle (2002)  Neurocomputing vol. 44, 97-101

[J63]Zhang P. and Feng J.F. (2002) Ideal observer ofsingle neuron activity Neurocomputing vol. 44, 243-247.


[J62]Feng J.F., and Wei G. (2001) Increasing inhibitory input increases neuronal firing rate   J. Phys. A.  vol. 34, 7493-7510

[J61]Feng J.F. (2001) Optimally decoding the input rate from an observation of the interspike intervals J. Phys. A. vol. 34, 7475-7492

[J60]Feng J.F. (with G.Leng et al. ) (2001) Responses of magnocellular neurons to osmotic stimulation involves co-activation of excitatory and inhibitory input: an experimental and theoretical analysis J. Neurosci. vol 21(17) 6967-6977

[J59]Feng J.F., and Williams P. M. (2001) The generalization error of the symmetric and scaled support vector machine IEEE T. Neural Networks Vol. 12, No. 5. 1255-1260.

[J58]Feng J.F. (2001) Is the integrate-and-fire model good enough? - a review  Neural Networks vol.14, 955-975.

[J57]Feng J.F., Brown D., Wei G., and Tirozzi  B. (2001) Detectable and undetectable input signals for the integrate-and-fire model J. Phys. A. vol. 34,637-1645.

[J56]Feng J.F. and Zhang P. (2001) The behaviour of integrate-and-fire and Hodgkin-Huxley models with correlated input Phys. Rev. E. vol. 63, 051902: 1-11

[J55]Feng J.F.,Li G.B.,Brown D. and Buxton H. (2001) Balance between four types of synaptic input for the integrate-and-fire model J. Theor. Biol.vol.209, 61-79

[J54]Feng J.F. and Li  G. (2001) Neuronal models with current inputs J. Phys. A. vol. 34,1649-1669.

[J53]Feng J.F. Neuronal models with current inputs LNCS  vol. 2084,47-54.

[J52]Feng J.F.(2001) Non-symmetric Support Vector Machines LNCS  vol. 2084, 418-426.

[J51]Davison A., Feng J.F., and Brown D. (2001) Spike synchronization in a biophysically-detailed model of the olfactory bulb Neurocomputing 38: 515-521.

[J50]Brown D., Feng J.F., and Feerick S. (2001) Significance of random neuronal drive Neurocomputing 38: 111-119.

[J49]Feng J.F., and Li, G.B. (2001) Behaviour of two-compartment model  Neurocomputing  38: 205-211.

[J48]Feerick S., Feng J.F., and Brown D. (2001) Inhibitory inputs increase a neuron's firing rate Neurocomputing 38: 197-203.

[J47]Feng J.F.,Shcherbina M. and Tirozzi B.(2001) On the critical capacity of the Hopfield model Communications in Mathematical Physics vol. 216, 139-177.


[J46] Feng J.F., and Brown D.(2000) Integrate-and-fire models with nonlinear leakage Bulletin of Mathematical Biology vol. 62, 467-481.

[J45]Davison A., Feng J.F., Brown D.(2000) A reduced compartmental model of the mitral cell for use in network models of the olfactory  bulb Brain  Research Bulletin  vol. 51,  393-399.

[J44]Feng J.F.,Brown D., and Li G. (2000) Synchronization due to common pulsed input in Stein's model Physics Review E vol. 61, 2987-2995.

[J43]Feng, J.F., and Tirozzi B. (2000) Stochastic resonance tuned by correlations in neuronal models Phys. Rev. E. vol. 61, 4207-4211.

[J42]Feng J.F., and Brown D.(2000). Impact of correlated inputs on the output of the integrate-and-fire models Neural Computation vol.12, 671-692.

[J41]Feng J.F.,Georgii H.O. and Brown D. (2000) Convergence to global minima for a class of diffusion processes Physica A vol. 276,465-476.

[J40]Feerick S., Feng J.F., and Brown D. (2000) Random pulse input versus continuous current plus white/colored noise: are they  equivalent Neurocomputing vol. 32-33, 127-132.

[J39]Feng J.F.(2000) Stimulus-evoked oscillatory synchronisation in neuronal models Neurocomputing (CNS'00, oral presentation) vol. 32-33,371-378.

[J38]Brown D. and Feng J.F. (2000) Low correlation between random synaptic inputs impacts considerably on the output of the Hodgkin-Huxley model Neurocomputing vol. 32-33 61-67.


[J37]Brown D.,Feng J.F., and Feerick S.(1999) Variability of firing of Hodgkin-Huxley and FitzHugh-Nagumo neurons with stochastic synaptic input. Phys. Rev. Lett vol 82, 4731-4734.

[J36]Feng J.F. and Cassia-Moura R. (1999) Output of a neuronal population code. Phys. Rev. E. vol. 59, 7246-7249.

[J35]Feng, J.F., and Tirozzi T.  (1999) Learning in a higher-order simple perceptron. Mathematical and Computer Modelling vol. 30, 217-223

[J34]Brown D.,and Feng J.F..(1999) Effects of correlation and degree of balance in random synaptic inputs on the output of   the Hodgkin-Huxley model Lecture Notes in Computer Science,vol. 1606, 197-205

[J33]Davison A., Feng J.F.,Brown D.(1999) Structure of lateral inhibition in an olfactory bulb model Lecture Notes in Computer Science,vol.1606,189-196

[J32]Feericks, S.,Feng J.F.,and Brown D.(1999) Paradoxical relationship between output and input regularity for the FitzHugh-Nagumo  model Lecture Notes in Computer Science vol. 1606, 221-229.

[J31]Feng J.F.(1999)  Lecture Notes in Computer Science vol.1606,258-267.

[J30]Feng J.F.(1999) Estimating exact form of generalisation errors Lecture Notes in Computer Science vol. 1606, 413-420.

[J29]Feng J.F. and Brown D.(1999) Coefficient Of Variation Greater Than 0.5 How And When Biol. Cybern. vol. 80, 291-297.

[J28]Brown, D. and Feng, J.F.(1999) Is there a problem matching real and model CV(ISI)? Neurocomputing vol. 26-27, 117-122.

[J27]Feng J.F. (1999) Origin Of Firing Variability Of The Integrate-and-fire Model Neurocomputing vol. 26-27, 87-91.


[J26]Feng J.F.(1998) Generalization errors of the simple perceptron J. Phys. A: Math. and Gen.4037-4048.

[J25]Feng J.F. and Brown D. (1998) Impact of temporal variation and the balance between excitation and inhibition on the output  of the perfect integrate and fire model  Biol. Cyber. vol. 78, 369-376.

[J24]Feng, J.F. and Brown, D.(1998) Fixed point attractor analysis for a class of neurodynamics Neural Computation vol. 10, 189-213.

[J23]Feng J.F. and Brown D.(1998) Spike output jitter, mean firing time and coefficient of variation J. Phys. A: Math. and Gen. vol.31,1239-1252.


[J22]Feng J.F.(1997) Behaviours of spike output jitter in the integrate-and-fire model Phys. Rev. Lett vol. 79(21), 4505-4508.

[J21]Feng J.F.(1997) Lyapunov functions for neural nets with nondifferentiable input-output characteristics. Neural Computation vol. 9: 45-51.

[J20]Feng J.F. and Brown D.(1997) Viewing a class of neurodynamics on parameter space. Lecture Notes in Computer Science vol. 1240, 546-555.

[J19]Feng, J.F. and Tirozzi B.(1997) Convergence Theorems for the Kohonen feature mapping algorithms with VLRPs. Computers and Mathematics with Applications vol. 33: 45-63

[J18]Feng, J.F. and Tirozzi B.(1997) Convergence theorems for a class of learning algorithm with VLRPs. Neurocomputing vol. 15: 45-68.

[J17]Feng J.F. ,Pan H. and Roychowdhury V. P.(1997) A rigorous analysis of Linsker's unsupervised Hebbian learning. Neural Network vol. 10: 705-720.

[J16]Feng J.F. and Tirozzi B.(1997) An analysis on neural dynamics with saturated sigmoidal functions. Computers and  Mathematics with Applications vol. 34: 71-99.

[J15]Feng J.F., and Tirozzi B.(1997) A Discrete Version of the Dynamic Link Network. Neurocomputing vol. 15: 91-106.

[J14]Feng J.F., and Tirozzi B.(1997) Capacity of the Hopfield model. Journal of Physics A: Mathematics and General vol. 30:3383-3391.

[J13]Chen D., Feng J.F. and Qian M.(1997) The metastable behaviour of the three-dimensional stochastic Ising model.1. Science in China series A vol. 40: 832-842.

[J12]Chen D., Feng J.F.,and Qian M.(1997) The metastable behaviour of the three-dimensional stochastic Ising model.2. Science in China series A vol. 40: 1129-1135.


[J11]Feng J.F. (1996) The hydrodynamic limit for the reaction diffusion equation-an approach in terms of the GPV method. Journal of Theoretical Probability vol. 9: 285-299.

[J10]Chen D.,Feng, J.F., and Qian, M.(1996).Metastability of exponential perturbated Markov chains. Science in China series A vol. 39: 7-28.

[J9]Feng J.F., Pan, H., and Roychowdhury, V. P.(1996) On neurodynamics with limiter function and Linsker's developmental model. Neural Computation vol. 8: 1003-1019.

[J8]Feng J.F. and Hadeler K. P.(1996) Qualitative behavior of some simple networks. Journal of Physics A: Mathematics and General vol. 29: 5019-5033.

[J7]Feng J.F. and Brown D.(1996) A novel approach for analyzing dynamics in neural networks with saturated characteristic. Neural Processing Letter vol. 4: 9-16.

[J6]Feng J.F., Tirozzi B. and Zucchi, R. (1996) Rigorous results and critical capacity for a short-term memory model Markov Processes  And Related Fields vol. 2: 539-55


[J5]Albeverio S., Feng, J.F. and Qian, M.(1995) Role of noises in neural networks. Physical Review E vol. 52: 6593-6606.

[J4]Feng J.F.(1995) Establishment of topological maps--a model stud ; Neural Processing Letters; vol. 2: 1-4.

[J3] Feng, J., and Tirozzi, B. (1995). ; The SLLN for the free-energy of the Hopfield and spin glass model. Helvetica Physica Acta, vol. 68: 365-379.

[J2] Feng, J., and Tirozzi, B. (1995). ; An application of the saturated attractor analysis to three typical models; Lecture Notes in Computer Science; vol. 930: 353-360.

[J1] Feng, J., Lei, G., and Qian, M. (1992). ; Second-order algorithms for SDE.; Journal of Computational Mathematics ; vol. 10: 376-387.

Publications (Proceeding and book chapter):

[P24] S. Wu, F. Feng and S. Amari (2006). The Ideal Noisy Environment for Fast Neural Computation. ISSN2006 (in press).

[p23] S Wang, Y Chen, M Ding, J F Feng, JF Stein, TZ Aziz and X Liu (2005). Revealing the dynamic correlation between neural and muscular signals using time-dependent Granger causality analysis. Proceedings of IEE Medical Applications of Signal Processing, pp99-104.

[P22] Williams P, Li S, Feng JF; Scaling the kernel function to improve performance of the support vector machine; LECTURE NOTES IN COMPUTER SCIENCE 3496: 831-836 2005

[P21] P.M. Williams, S. Wu, and J.F. Feng (2004) Improving the Performance of the Support Vector Machine: Two Geometrical Scaling Methods; Support Vector Machines: Theory and Applications, L. Wang (Ed.) Springer-Verlag (invited book chapter), 205-218.

[P20] K.W. Lee, H. Buxton, and J.F. Feng (2003)  Selective attention for cue-guided search using a spiking neural network,  in Proc. International Workshop on Attention and Performance in Computer Vision, 2003, L. Paletta, G.W. Humphreys, and R.B. Fisher (eds.), 55-63.

[P19] Tuckwell H.C., and Feng J.F. (2003) A theoretical overview, 1-30, in Computational Neuroscience: A Comprehensive Approach,   J. F. Feng (ed.),  Chapman and Hall/CRC Press.

[P18] Feng J.F.,  (2002) Coorelated Neuronal Computation  Unsolved Problems Of Noise and Fluctuations In Physics, Biology and High Technology, AIP conference proceedings, S.M. Bezrukov  (ed.),  208-215.

[P17] Lee K.W.,  Feng J.F., and Buxton H. (2002) A dynamic neural network model on global-to-local interraction over time course  Proc. Int. Conf. on Neural Information Processing

[P16] Feng J. (2002) Stochastic computations in neurons and neural networks,  Cytocom, R. Paton (ed.).

[P15] Lee K.W.,  Feng J.F., and Buxton H. (2001) Perceptual reversal over time course Proc. Int. Conf. on Neural Information Processing

[P14]   Liu  W.B.,  Feng J.  (2001)  SSC Algorithms for Nonsmooth and Stochastic Optimization, to be published in Encyclopaedia of Optimization, Kluwer Acaademic, 2001.

[P13] Feng J., and Brown D. (2000)A comparison between abstract and biophysical neuron models in: Broomhead D.S., Luchinskaya E.A., McClintock V.E. an Mulin T. (eds) Stochastic and Chaotic Dynamics in the Lakes, AIP conference proceedings 502, 118-123.

[P12] Feng J., Brown D., and Tirozzi B. (1999) A model of pulse neural networks in: Inan E., Markov K.Z. (eds)  Continuum Models and Discrete Systems,  World Scientific Publishing Co., 353-357.

[P11] Feng, J., and Brown D. (1998). Output jitter diverges to infinity, converges to zero or remains constant? in: M. Verleysen (ed), ESANN'98, 39-46.

[P10] Feng, J., and Brown D. (1998) What are we observable in a class of neurodynamics? in: M. Verleysen (ed), ESANN'98, 147-154.

[P9] Feng, J., and Tirozzi, B. (1996). On Choosing the Parameters in the Dynamic Link Network. in: Marinaro, M. and Tagliaferri, R. (ed), WIRN VIETRI-95, World Scientific: Singapore, 245-250.

[P8] Feng, J., and Heyer, H. (1995). Large Deviations on a class of Compact Hypergroups, in: Heyer, H.(ed), Probability on the Group XI, Singapore: World Scientific, 126-140.

[P7] Feng, J., and Pan, H., and Roychowdhury, V. P. (1995). A Rigorously Analysis of Linsker-Type Hebbian Learning}, in: Tesauro, G, Touretzky, D., and Leen, T.K.(ed), Advances in the Neural Information Processing System 7, Cambridge MA: MIT Press, 319-326.

[P6] Chen, D., Feng, J., and Qian, M. (1995) Metastability of Two Dimensional Ising Model. Workshop on Dirichlet Forms and Markov Process, Walter de Gruyter, 73-86.

[P5] Feng, J., and Pan, H. (1993). Analysis of Linsker-Type Hebbian Learning: Rigorous Results. Proc. of IEEE ICNN'93, San Francisco, 1516-1521.

[P4] Feng, J., and Qian, M. (1993). Two-Stage Annealing in Retrieving Memories I, In: Badrikian, A.; Meyer P-A, and Yan, J-A (ed.), Probability and Statistics, Singapore: World Scientific, 149-176.

[P3] Feng, J. (1992). Learning with Random Sampling Inputs in a Simple Perceptron. Proc. of Inter. Joint Conf. on NN: Beijing II, 59-66.

[P2] Qian, M., and Feng, J. (1992). Is the Noise Just a Perturbation? Proc. of Inter. Joint Confer. on NN: Beijing II, 545-551.

[P1] Pan, H., Feng, J., and GUO, A. (1991). Layered Self-Adaptive Neural Network Approach to Early Visual Information Processing. in Artificial Neural Network, ed. by T, Kohonen, North-Holland, 1389-1392.

Publications (Journals Inside China):

[10] Feng, J. (2000).  Impact of  correlated inputs on the output of neuronal modelsvol.  Fudan Lectures In Neurobiology  XVI, 129-148  (invited)

[9] Feng, J., and PAN, H. (1996). Determining the parameter region of the Linsker's network. Acta Scientiarum Naturalium, Universitatis Pekinensis vol. 31: 302-315.

[8] Feng, J. (1995). Phase transition for a class of inhomogeneous Markov chains I. Advances in Mathematics vol. 24: 102-112.

[7] Feng, J. (1995). A dicussion of the learning in a simple perceptron. Acta Scientiarum Naturalium, Universitatis Pekinensis vol. 31: 20-26.

[6] Feng, J., and Qian, M. (1994). Retrieving memories-an approach in terms of the mean first exiting times. Advances in Mathematics vol 23: 50-65.

[5] Xu, J., Feng, J., and Ren, M. (1994). Inter-well prediction for permeability: an application of spline. Acta Scientiarum Naturalium Universitatis Pekinensis vol. 30: 116-121

[4] Feng, J., and Qian, M. (1994). The convergence of the Hopfield type model. Advances in Mathematics vol. 23: 451-459.

[3] Feng, J., and Qian, M. (1993). Annealing in the neural networks, I. homogeneous case. Acta Scientiarum Naturalium, Universitatis Pekinensis vol. 29: 303-314.

[2] Feng, J., and Qian, M. (1993). Annealing in the neural networks, II. inhomogeneous case. Acta Scientiarum Naturalium, Universitatis Pekinensis vol 29: 528-540.

[1] Feng, J. (1990). Numerical solution of the stochastic differential equation. Chinese Journal of Numerical Mathematics and Applications vol. 12: 28-41.

Publications (Abstract):

[4] AU Nicol, MS Magnusson, A Segonds-Pichon, A Tate, J Feng & KM Kendrick (2005) Local and global encoding of odor stimuli by olfactory bulb neural networks, Annual Meeting of Neuroscience? (Oral presentation).

[3] A.J. Tate; A.U. Nicol; H. Fischer; A. Segonds-Pichon; J. Feng; M.S. Magnusson; K.M. Kendrick(2005), Lateralised local and global encoding of face stimuli by neural networks in the temporal cortex , Annual Meeting of Neuroscience?(Oral presentation)

[2] D.V. Vavoulis, V.A. Straub, S.J. Dunn, J.F. Feng, and P.R. Benjamin (2004).?Modelling plateau potentials in a molluscan central pattern generator, Annual Meeting of Neuroscience.

[1] A. Nicol, M.S. Man, J.F. Feng, R. Mason and K. Kendrick (2003) Differential spatial activation patterns evoled by odor stimui in the rate olfactory bulb,

Patent: "Signal Processing and transmission and data storage and representation" EU 05253204.1, (Kendrick, Durrant and Feng)