Jianfeng Feng

According to our database1, Jianfeng Feng authored at least 97 papers between 1994 and 2019.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.



In proceedings 
PhD thesis 



On csauthors.net:


A powerful and efficient multivariate approach for voxel-level connectome-wide association studies.
NeuroImage, 2019

Neural and genetic determinants of creativity.
NeuroImage, 2018

Statistical testing and power analysis for brain-wide association study.
Medical Image Analysis, 2018

A Wiener Causality Defined by Relative Entropy.
Proceedings of the Neural Information Processing - 25th International Conference, 2018

Chi-square 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

Generalized reduced rank latent factor regression for high dimensional tensor fields, and neuroimaging-genetic applications.
NeuroImage, 2017

Functional connectivity decreases in autism in emotion, self, and face circuits identified by Knowledge-based Enrichment Analysis.
NeuroImage, 2017

Canonical kernel dimension reduction.
Computational Statistics & Data Analysis, 2017

Using real-time 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

Reconstruction of Excitatory Neuronal Connectivity via Metric Score Pooling and Regularization.
Proceedings of the Neural Connectomics Workshop at ECML 2014, 2014

Attention-Dependent Modulation of Cortical Taste Circuits Revealed by Granger Causality with Signal-Dependent Noise.
PLoS Computational Biology, 2013

Spatio-temporal 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

On the Spectral Characterization and Scalable Mining of Network Communities.
IEEE Trans. Knowl. Data Eng., 2012

Invariance Principles Allowing of Non-Lyapunov Functions for Estimating Attractor of Discrete Dynamical Systems.
IEEE Trans. Automat. Contr., 2012

A Self-Organizing State-Space-Model Approach for Parameter Estimation in Hodgkin-Huxley-Type Models of Single Neurons.
PLoS Computational Biology, 2012

Increasing power for voxel-wise genome-wide 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 top-down biased activation that controls attention to affective vs sensory processing.
NeuroImage, 2012

A Dynamical Model Reveals Gene Co-Localizations in Nucleus.
PLoS Computational Biology, 2011

Granger causality with signal-dependent noise.
NeuroImage, 2011

Granger Causality: Its Foundation and Applications in Systems Biology.
Proceedings of the Handbook of Research on Computational and Systems Biology, 2011

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

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 reverse-engineering 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 multi-trial electrophysiology data using Wiener and Kalman filters.
Biosystems, 2009

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

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 hot-spots in large-scale multivariate data.
BMC Bioinformatics, 2007

Decoding spike train ensembles: tracking a moving stimulus.
Biological Cybernetics, 2007

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

Cue-guided 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

Decoding Input Signals in Time Domain - A Model Approach.
Journal of Computational Neuroscience, 2004

Stimulus-evoked synchronization in neuronal models.
Neurocomputing, 2004

Is partial coherence a viable technique for identifying generators of neural oscillations?
Biological Cybernetics, 2004

Temporal album.
IEEE Trans. Neural Networks, 2003

Training integrate-and-fire neurons with the Informax principle II.
IEEE Trans. Neural Networks, 2003

The Minimum-Variance Theory Revisited.
Proceedings of the Artificial Neural Nets Problem Solving Methods, 2003

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 Integrate-and-Fire Neurons for Image Segmentation.
Proceedings of the Artificial Neural Networks, 2002

The generalization error of the symmetric and scaled support vector machines.
IEEE Trans. Neural Networks, 2001

Is the integrate-and-fire model good enough?--a review.
Neural Networks, 2001

Behaviour of two-compartment models.
Neurocomputing, 2001

Inhibitory inputs increase a neurons's firing rate.
Neurocomputing, 2001

Spike synchronization in a biophysically-detailed model of the olfactory bulb.
Neurocomputing, 2001

Significance of random neuronal drive.
Neurocomputing, 2001

Non-symmetric Support Vector Machines.
Proceedings of the Connectionist Models of Neurons, 2001

Neuronal Models with Current Inputs.
Proceedings of the Connectionist Models of Neurons, 2001

Impact of Correlated Inputs on the Output of the Integrate-and-Fire 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 Hodgkin-Huxley model.
Neurocomputing, 2000

Origin of firing varibility of the integrate-and-fire 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

Integrate-and-Fire Model with Correlated Inputs.
Proceedings of the Foundations and Tools for Neural Modeling, 1999

Paradoxical Relationship between Output and Input Regularity for the FitzHugh-Nagumo 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 Hodgkin-Huxley Model.
Proceedings of the Foundations and Tools for Neural Modeling, 1999

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 integrate-and-fire 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

Linsker-type Hebbian Learning: A Qualitative Analysis on the Parameter Space.
Neural Networks, 1997

Lyapunov Functions for Neural Nets with Nondifferentiable Input-Output 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

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

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

A Rigorous Analysis of Linsker-Type Hebbian Learning.
Proceedings of the Advances in Neural Information Processing Systems 7, 1994