Jianfeng Feng
According to our database^{1},
Jianfeng Feng
authored at least 97 papers
between 1994 and 2019.
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Bibliography
2019
A powerful and efficient multivariate approach for voxellevel connectomewide association studies.
NeuroImage, 2019
2018
Neural and genetic determinants of creativity.
NeuroImage, 2018
Statistical testing and power analysis for brainwide association study.
Medical Image Analysis, 2018
A Wiener Causality Defined by Relative Entropy.
Proceedings of the Neural Information Processing  25th International Conference, 2018
Chisquare Generative Adversarial Network.
Proceedings of the 35th International Conference on Machine Learning, 2018
Dual Skipping Networks.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018
2017
Generalized reduced rank latent factor regression for high dimensional tensor fields, and neuroimaginggenetic applications.
NeuroImage, 2017
Functional connectivity decreases in autism in emotion, self, and face circuits identified by Knowledgebased Enrichment Analysis.
NeuroImage, 2017
Canonical kernel dimension reduction.
Computational Statistics & Data Analysis, 2017
2016
Using realtime fMRI to influence effective connectivity in the developing emotion regulation network.
NeuroImage, 2016
Comparing data assimilation filters for parameter estimation in a neuron model.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016
2014
Reconstruction of Excitatory Neuronal Connectivity via Metric Score Pooling and Regularization.
Proceedings of the Neural Connectomics Workshop at ECML 2014, 2014
2013
AttentionDependent Modulation of Cortical Taste Circuits Revealed by Granger Causality with SignalDependent Noise.
PLoS Computational Biology, 2013
Spatiotemporal Granger causality: A new framework.
NeuroImage, 2013
Neuronal Synfire Chain via Moment Neuronal Network Approach.
Proceedings of the Neural Information Processing  20th International Conference, 2013
2012
On the Spectral Characterization and Scalable Mining of Network Communities.
IEEE Trans. Knowl. Data Eng., 2012
Invariance Principles Allowing of NonLyapunov Functions for Estimating Attractor of Discrete Dynamical Systems.
IEEE Trans. Automat. Contr., 2012
A SelfOrganizing StateSpaceModel Approach for Parameter Estimation in HodgkinHuxleyType Models of Single Neurons.
PLoS Computational Biology, 2012
Increasing power for voxelwise genomewide association studies: The random field theory, least square kernel machines and fast permutation procedures.
NeuroImage, 2012
Componential Granger causality, and its application to identifying the source and mechanisms of the topdown biased activation that controls attention to affective vs sensory processing.
NeuroImage, 2012
2011
A Dynamical Model Reveals Gene CoLocalizations in Nucleus.
PLoS Computational Biology, 2011
Granger causality with signaldependent noise.
NeuroImage, 2011
Granger Causality: Its Foundation and Applications in Systems Biology.
Proceedings of the Handbook of Research on Computational and Systems Biology, 2011
2010
Rhythmic Dynamics and Synchronization via Dimensionality Reduction: Application to Human Gait.
PLoS Computational Biology, 2010
On a Gaussian neuronal field model.
NeuroImage, 2010
Identifying interactions in the time and frequency domains in local and global networks  A Granger Causality Approach.
BMC Bioinformatics, 2010
Controlling precise movement with stochastic signals.
Biological Cybernetics, 2010
On Gaussian random neuronal field model: Moment neuronal network approach.
Proceedings of the International Joint Conference on Neural Networks, 2010
Find synaptic topology from spike trains.
Proceedings of the International Joint Conference on Neural Networks, 2010
2009
Voxel Selection in fMRI Data Analysis Based on Sparse Representation.
IEEE Trans. Biomed. Engineering, 2009
A Novel Extended Granger Causal Model Approach Demonstrates Brain Hemispheric Differences during Face Recognition Learning.
PLoS Computational Biology, 2009
Maximum Likelihood Decoding of Neuronal Inputs from an Interspike Interval Distribution.
Neural Computation, 2009
Impact of environmental inputs on reverseengineering approach to network structures.
BMC Systems Biology, 2009
Granger causality vs. dynamic Bayesian network inference: a comparative study.
BMC Bioinformatics, 2009
Granger causality vs. dynamic Bayesian network inference: a comparative study.
BMC Bioinformatics, 2009
Filtering noise for synchronised activity in multitrial electrophysiology data using Wiener and Kalman filters.
Biosystems, 2009
2008
Training Spiking Neuronal Networks With Applications in Engineering Tasks.
IEEE Trans. Neural Networks, 2008
Emergent Synchronous Bursting of Oxytocin Neuronal Network.
PLoS Computational Biology, 2008
Uncovering Interactions in the Frequency Domain.
PLoS Computational Biology, 2008
A machine learning approach to explore the spectra intensity pattern of peptides using tandem mass spectrometry data.
BMC Bioinformatics, 2008
On Modularity of Social Network Communities: The Spectral Characterization.
Proceedings of the 2008 IEEE / WIC / ACM International Conference on Web Intelligence, 2008
2007
A Geometrical Method to Improve Performance of the Support Vector Machine.
IEEE Trans. Neural Networks, 2007
Optimal movement control models of Langevin and Hamiltonian types.
Mathematical and Computer Modelling, 2007
Revealing the dynamic causal interdependence between neural and muscular signals in Parkinsonian tremor.
J. Franklin Institute, 2007
A novel approach to detect hotspots in largescale multivariate data.
BMC Bioinformatics, 2007
Decoding spike train ensembles: tracking a moving stimulus.
Biological Cybernetics, 2007
2006
Spiking perceptrons.
IEEE Trans. Neural Networks, 2006
Population approach to a neural discrimination task.
Biological Cybernetics, 2006
Negatively correlated firing: the functional meaning of lateral inhibition within cortical columns.
Biological Cybernetics, 2006
The Ideal Noisy Environment for Fast Neural Computation.
Proceedings of the Advances in Neural Networks  ISNN 2006, Third International Symposium on Neural Networks, Chengdu, China, May 28, 2006
2005
Cueguided search: a computational model of selective attention.
IEEE Trans. Neural Networks, 2005
Impact of temperature and pH value on the stability of hGHRH: An MD approach^{, }.
Mathematical and Computer Modelling, 2005
Scaling the Kernel Function to Improve Performance of the Support Vector Machine.
Proceedings of the Advances in Neural Networks  ISNN 2005, Second International Symposium on Neural Networks, Chongqing, China, May 30, 2005
2004
Decoding Input Signals in Time Domain  A Model Approach.
Journal of Computational Neuroscience, 2004
Stimulusevoked synchronization in neuronal models.
Neurocomputing, 2004
Is partial coherence a viable technique for identifying generators of neural oscillations?
Biological Cybernetics, 2004
2003
Temporal album.
IEEE Trans. Neural Networks, 2003
Training integrateandfire neurons with the Informax principle II.
IEEE Trans. Neural Networks, 2003
The MinimumVariance Theory Revisited.
Proceedings of the Artificial Neural Nets Problem Solving Methods, 2003
2002
Impact of Geometrical Structures on the Output of Neuronal Models: A Theoretical and Numerical Analysis.
Neural Computation, 2002
Ideal observer of single neuron activity.
Neurocomputing, 2002
Training neuron models with the Informax principle.
Neurocomputing, 2002
Clustering within IntegrateandFire Neurons for Image Segmentation.
Proceedings of the Artificial Neural Networks, 2002
2001
The generalization error of the symmetric and scaled support vector machines.
IEEE Trans. Neural Networks, 2001
Is the integrateandfire model good enough?a review.
Neural Networks, 2001
Behaviour of twocompartment models.
Neurocomputing, 2001
Inhibitory inputs increase a neurons's firing rate.
Neurocomputing, 2001
Spike synchronization in a biophysicallydetailed model of the olfactory bulb.
Neurocomputing, 2001
Significance of random neuronal drive.
Neurocomputing, 2001
Nonsymmetric Support Vector Machines.
Proceedings of the Connectionist Models of Neurons, 2001
Neuronal Models with Current Inputs.
Proceedings of the Connectionist Models of Neurons, 2001
2000
Impact of Correlated Inputs on the Output of the IntegrateandFire Model.
Neural Computation, 2000
Synchronization driven by correlated inputs.
Neurocomputing, 2000
Random pulse input versus continuous current plus white noise: Are they equivalent?
Neurocomputing, 2000
Low correlation between random synaptic inputs impacts considerably on the output of the HodgkinHuxley model.
Neurocomputing, 2000
1999
Origin of firing varibility of the integrateandfire model.
Neurocomputing, 1999
Is there a problem matching real and model CV(ISI)?
Neurocomputing, 1999
Coefficient of variation of interspike intervals greater than 0.5. How and when?
Biological Cybernetics, 1999
Estimating Exact Form of Generalisation Errors.
Proceedings of the Foundations and Tools for Neural Modeling, 1999
IntegrateandFire Model with Correlated Inputs.
Proceedings of the Foundations and Tools for Neural Modeling, 1999
Paradoxical Relationship between Output and Input Regularity for the FitzHughNagumo Model.
Proceedings of the Foundations and Tools for Neural Modeling, 1999
Structure of Lateral Inhibition in an Olfactory Bulb Model.
Proceedings of the Foundations and Tools for Neural Modeling, 1999
Effects of Correlation and Degree of Balance in Random Synaptic Inputs on the Output of the HodgkinHuxley Model.
Proceedings of the Foundations and Tools for Neural Modeling, 1999
1998
Fixed Point Attractor Analysis for a Class of Neurodynamics.
Neural Computation, 1998
Impact of temporal variation and the balance between excitation and inhibition on the output of the perfect integrateandfire model.
Biological Cybernetics, 1998
Output jitter diverges to infinity, converges to zero or remains constant.
Proceedings of the ESANN 1998, 1998
What is observable in a class of neurodynamics?
Proceedings of the ESANN 1998, 1998
1997
Linskertype Hebbian Learning: A Qualitative Analysis on the Parameter Space.
Neural Networks, 1997
Lyapunov Functions for Neural Nets with Nondifferentiable InputOutput Characteristics.
Neural Computation, 1997
A discrete version of the dynamic link network.
Neurocomputing, 1997
Convergence theorems for a class of learning algorithms with VLRPs.
Neurocomputing, 1997
Viewing a Class of Neurodynamics on Parameter Space.
Proceedings of the Biological and Artificial Computation: From Neuroscience to Technology, 1997
1996
A Novel Approach for Analyzing Dynamics in Neural Networks with Saturated Characteristics.
Neural Processing Letters, 1996
On Neurodynamics with Limiter Function and Linsker's Developmental Model.
Neural Computation, 1996
1995
Establishment of topological maps  a model study.
Neural Processing Letters, 1995
An Application of the Saturated Attractor Analysis to Three Typical Models.
Proceedings of the From Natural to Artificial Neural Computation, 1995
1994
A Rigorous Analysis of LinskerType Hebbian Learning.
Proceedings of the Advances in Neural Information Processing Systems 7, 1994