Volume 22, Number 1, January 2010

Article

• 
  Christopher DiMattina, Kechen Zhang: How to Modify a Neural Network Gradually Without Changing Its Input-Output Functionality. 1-47

Note

• 
  Daniel K. Wójcik, Szymon Leski: Current Source Density Reconstruction from Incomplete Data. 48-60

Letters

• 
  Sean Byrnes, Anthony N. Burkitt, David B. Grayden, Hamish Meffin: Spiking Neuron Model for Temporal Sequence Recognition. 61-93
• 
  Lars Wolff, Benjamin Lindner: Mean, Variance, and Autocorrelation of Subthreshold Potential Fluctuations Driven by Filtered Conductance Shot Noise. 94-120
• 
  Robert Haslinger, Kristina Lisa Klinkner, Cosma Rohilla Shalizi: The Computational Structure of Spike Trains. 121-157
• 
  Seif Eldawlatly, Yang Zhou, Rong Jin, Karim G. Oweiss: On the Use of Dynamic Bayesian Networks in Reconstructing Functional Neuronal Networks from Spike Train Ensembles. 158-189
• 
  Elisa Magosso, Melissa Zavaglia, Andrea Serino, Giuseppe Di Pellegrino, Mauro Ursino: Visuotactile Representation of Peripersonal Space: A Neural Network Study. 190-243
• 
  Terry Elliott: Discrete States of Synaptic Strength in a Stochastic Model of Spike-Timing-Dependent Plasticity. 244-272
• 
  Florian Landis, Thomas Ott, Ruedi Stoop: Hebbian Self-Organizing Integrate-and-Fire Networks for Data Clustering. 273-288

Volume 22, Number 2, February 2010

Review

• 
  Andreas Knoblauch, Günther Palm, Friedrich T. Sommer: Memory Capacities for Synaptic and Structural Plasticity. 289-341

Article

• 
  Tetsuro Morimura, Eiji Uchibe, Junichiro Yoshimoto, Jan Peters, Kenji Doya: Derivatives of Logarithmic Stationary Distributions for Policy Gradient Reinforcement Learning. 342-376

Letters

• 
  Michael A. Buice, Jack D. Cowan, Carson C. Chow: Systematic Fluctuation Expansion for Neural Network Activity Equations. 377-426
• 
  John Hertz: Cross-Correlations in High-Conductance States of a Model Cortical Network. 427-447
• 
  Jesús M. Cortés, Andrea Greve, Adam B. Barrett, Mark C. W. van Rossum: Dynamics and Robustness of Familiarity Memory. 448-466
• 
  Filip Ponulak, Andrzej J. Kasinski: Supervised Learning in Spiking Neural Networks with ReSuMe: Sequence Learning, Classification, and Spike Shifting. 467-510
• 
  Srinivas C. Turaga, Joseph F. Murray, Viren Jain, Fabian Roth, Moritz Helmstaedter, Kevin L. Briggman, Winfried Denk, H. Sebastian Seung: Convolutional Networks Can Learn to Generate Affinity Graphs for Image Segmentation. 511-538
• 
  Tyler McMillen, Sam Behseta: On the Effects of Signal Acuity in a Multi-Alternative Model of Decision Making. 539-580

Volume 22, Number 3, March 2010

Letters

• 
  Michael Famulare, Adrienne L. Fairhall: Feature Selection in Simple Neurons: How Coding Depends on Spiking Dynamics. 581-598
• 
  Jan A. Freund, Alexander Nikitin, Nigel G. Stocks: Phase Locking Below Rate Threshold in Noisy Model Neurons. 599-620
• 
  Bryan P. Tripp, Chris Eliasmith: Population Models of Temporal Differentiation. 621-659
• 
  Yali Amit, Yibi Huang: Precise Capacity Analysis in Binary Networks with Multiple Coding Level Inputs. 660-688
• 
  Vilson L. DalleMole, Aluizio Fausto Ribeiro Araújo: Growing Self-Organizing Surface Map: Learning a Surface Topology from a Point Cloud. 689-729
• 
  Yiwen Wang, Bertram E. Shi: Autonomous Development of Vergence Control Driven by Disparity Energy Neuron Populations. 730-751
• 
  C. C. Alan Fung, K. Y. Michael Wong, Si Wu: A Moving Bump in a Continuous Manifold: A Comprehensive Study of the Tracking Dynamics of Continuous Attractor Neural Networks. 752-792
• 
  Giorgio Gnecco, Marcello Sanguineti: Regularization Techniques and Suboptimal Solutions to Optimization Problems in Learning from Data. 793-829

Volume 22, Number 4, April 2010

Letters

• 
  Jo-Anne Ting, Aaron D'Souza, Sethu Vijayakumar, Stefan Schaal: Efficient Learning and Feature Selection in High-Dimensional Regression. 831-886
• 
  Daniel R. Cavagnaro, Jay I. Myung, Mark A. Pitt, Janne V. Kujala: Adaptive Design Optimization: A Mutual Information-Based Approach to Model Discrimination in Cognitive Science. 887-905
• 
  Thomas Deneux, Olivier D. Faugeras: EEG-fMRI Fusion of Paradigm-Free Activity Using Kalman Filtering. 906-948
• 
  Rohit Gandrakota, V. S. Chakravarthy, Ranjan K. Pradhan: A Model of Indispensability of a Large Glial Layer in Cerebrovascular Circulation. 949-968
• 
  Roberto C. Sotero, Ramón Martínez-Cancino: Dynamical Mean Field Model of a Neural-Glial Mass. 969-997
• 
  Tiger W. Lin, George N. Reeke Jr.: A Continuous Entropy Rate Estimator for Spike Trains Using a K-Means-Based Context Tree. 998-1024
• 
  P. S. Sastry, K. P. Unnikrishnan: Conditional Probability-Based Significance Tests for Sequential Patterns in Multineuronal Spike Trains. 1025-1059
• 
  Huijuan Fang, Yongji Wang, Jiping He: Spiking Neural Networks for Cortical Neuronal Spike Train Decoding. 1060-1085
• 
  Jen-Yung Chen: A Simulation Study Investigating the Impact of Dendritic Morphology and Synaptic Topology on Neuronal Firing Patterns. 1086-1111

Volume 22, Number 5, May 2010

Article

• 
  Jiaxiang Zhang, Rafal Bogacz: Optimal Decision Making on the Basis of Evidence Represented in Spike Trains. 1113-1148

Letters

• 
  Tobias Larsen, David S. Leslie, Edmund J. Collins, Rafal Bogacz: Posterior Weighted Reinforcement Learning with State Uncertainty. 1149-1179
• 
  Terry Elliott: A Non-Markovian Random Walk Underlies a Stochastic Model of Spike-Timing-Dependent Plasticity. 1180-1230
• 
  Mengyuan Zhao, Satish Iyengar: Nonconvergence in Logistic and Poisson Models for Neural Spiking. 1231-1244
• 
  Sidney R. Lehky: Decoding Poisson Spike Trains by Gaussian Filtering. 1245-1271
• 
  Lars Büsing, Benjamin Schrauwen, Robert A. Legenstein: Connectivity, Dynamics, and Memory in Reservoir Computing with Binary and Analog Neurons. 1272-1311
• 
  Samat Moldakarimov, Maxim Bazhenov, Terrence J. Sejnowski: Representation Sharpening Can Explain Perceptual Priming. 1312-1332
• 
  Xiaolin Hu, Bo Zhang: A Gaussian Attractor Network for Memory and Recognition with Experience-Dependent Learning. 1333-1357
• 
  Osamu Hoshino: Alteration of Ambient GABA by Phasic and Tonic Neuronal Activation. 1358-1382
• 
  Takashi Kanamaru, Kazuyuki Aihara: Roles of Inhibitory Neurons in Rewiring-Induced Synchronization in Pulse-Coupled Neural Networks. 1383-1398

Volume 22, Number 6, June 2010

Article

• 
  Michael Pfeiffer, Bernhard Nessler, Rodney J. Douglas, Wolfgang Maass: Reward-Modulated Hebbian Learning of Decision Making. 1399-1444

Notes

• 
  A. Scaglione, Karen A. Moxon, G. Foffani: General Poisson Exact Breakdown of the Mutual Information to Study the Role of Correlations in Populations of Neurons. 1445-1467
• 
  Michiel D'Haene, Benjamin Schrauwen: Fast and Exact Simulation Methods Applied on a Broad Range of Neuron Models. 1468-1472

Letters

• 
  Roland Memisevic, Geoffrey E. Hinton: Learning to Represent Spatial Transformations with Factored Higher-Order Boltzmann Machines. 1473-1492
• 
  Felix Creutzig, Jan Benda, Sandra Wohlgemuth, Andreas Stumpner, Bernhard Ronacher, Andreas V. M. Herz: Timescale-Invariant Pattern Recognition by Feedforward Inhibition and Parallel Signal Processing. 1493-1510
• 
  William H. Alexander, Joshua W. Brown: Hyperbolically Discounted Temporal Difference Learning. 1511-1527
• 
  Rubén Moreno-Bote, Néstor Parga: Response of Integrate-and-Fire Neurons to Noisy Inputs Filtered by Synapses with Arbitrary Timescales: Firing Rate and Correlations. 1528-1572
• 
  Arturo Berrones: Bayesian Inference Based on Stationary Fokker-Planck Sampling. 1573-1596
• 
  Pengsheng Zheng, Wansheng Tang, Jianxiong Zhang: Efficient Continuous-Time Asymmetric Hopfield Networks for Memory Retrieval. 1597-1614
• 
  Jaehyung Lee, Soo-Young Lee: Learning the Dynamical System Behind Sensory Data. 1615-1645
• 
  Jiucang Hao, Intae Lee, Te-Won Lee, Terrence J. Sejnowski: Independent Vector Analysis for Source Separation Using a Mixture of Gaussians Prior. 1646-1673

Volume 22, Number 7, July 2010

Letters

• 
  Zbynek Pawlas, Lev Klebanov, Viktor Benes, Michaela Prokesová, Jirí Popelár, Petr Lánský: First-Spike Latency in the Presence of Spontaneous Activity. 1675-1697
• 
  Johannes Friedrich, Robert Urbanczik, Walter Senn: Learning Spike-Based Population Codes by Reward and Population Feedback. 1698-1717
• 
  Shun-ichi Amari: Conditional Mixture Model for Correlated Neuronal Spikes. 1718-1736
• 
  Bor-Sen Chen, Cheng-Wei Li: On the Noise-Enhancing Ability of Stochastic Hodgkin-Huxley Neuron Systems. 1737-1763
• 
  Gideon Gradwohl, Yoram Grossman: Statistical Computer Model Analysis of the Reciprocal and Recurrent Inhibitory Postsynaptic Potentials in alpha-Motoneurons. 1764-1785
• 
  Rubén Moreno-Bote: Decision Confidence and Uncertainty in Diffusion Models with Partially Correlated Neuronal Integrators. 1786-1811
• 
  Laurent U. Perrinet: Role of Homeostasis in Learning Sparse Representations. 1812-1836
• 
  R. Rossi Pool, G. Mato: Hebbian Plasticity and Homeostasis in a Model of Hypercolumn of the Visual Cortex. 1837-1859
• 
  Jason Gauci, Kenneth O. Stanley: Autonomous Evolution of Topographic Regularities in Artificial Neural Networks. 1860-1898
• 
  Huajin Tang, Haizhou Li, Rui Yan: Memory Dynamics in Attractor Networks with Saliency Weights. 1899-1926
• 
  Mingjie Zhao, Herbert Jaeger: Norm-Observable Operator Models. 1927-1959

Volume 22, Number 8, August 2010

Article

• 
  Lars Buesing, Wolfgang Maass: A Spiking Neuron as Information Bottleneck. 1961-1992

Note

• 
  Ke Yuan, Mahesan Niranjan: Estimating a State-Space Model from Point Process Observations: A Note on Convergence. 1993-2001

Letters

• 
  Todd P. Coleman, Sridevi S. Sarma: A Computationally Efficient Method for Nonparametric Modeling of Neural Spiking Activity with Point Processes. 2002-2030
• 
  Angelo Arleo, Thierry Nieus, Michele Bezzi, Anna D'Errico, Egidio D'Angelo, Olivier J. M. D. Coenen: How Synaptic Release Probability Shapes Neuronal Transmission: Information-Theoretic Analysis in a Cerebellar Granule Cell. 2031-2058
• 
  Daniel Bush, Andrew Philippides, Phil Husbands, Michael O'Shea: Reconciling the STDP and BCM Models of Synaptic Plasticity in a Spiking Recurrent Neural Network. 2059-2085
• 
  Yingxue Wang, Shih-Chii Liu: Multilayer Processing of Spatiotemporal Spike Patterns in a Neuron with Active Dendrites. 2086-2112
• 
  Ahmet Omurtag, William W. Lytton: Spectral Method and High-Order Finite Differences for the Nonlinear Cable Equation. 2113-2136
• 
  Wei Zhou, Jacek M. Zurada: Competitive Layer Model of Discrete-Time Recurrent Neural Networks with LT Neurons. 2137-2160
• 
  Yansheng Ming, Zhanyi Hu: Modeling Stereopsis via Markov Random Field. 2161-2191
• 
  Nicolas Le Roux, Yoshua Bengio: Deep Belief Networks Are Compact Universal Approximators. 2192-2207
• 
  Intae Lee: Sample-Spacings-Based Density and Entropy Estimators for Spherically Invariant Multidimensional Data. 2208-2227

Volume 22, Number 9, September 2010

Article

• 
  Barbara Hammer, Alexander Hasenfuss: Topographic Mapping of Large Dissimilarity Data Sets. 2229-2284

Letters

• 
  Hugo Larochelle, Yoshua Bengio, Joseph P. Turian: Tractable Multivariate Binary Density Estimation and the Restricted Boltzmann Forest. 2285-2307
• 
  Urs Köster, Aapo Hyvärinen: A Two-Layer Model of Natural Stimuli Estimated with Score Matching. 2308-2333
• 
  Payam Piray, Mohammad Mahdi Keramati, Amir Dezfouli, Caro Lucas, Azarakhsh Mokri: Individual Differences in Nucleus Accumbens Dopamine Receptors Predict Development of Addiction-Like Behavior: A Computational Approach. 2334-2368
• 
  Kentaro Katahira, Jun Nishikawa, Kazuo Okanoya, Masato Okada: Extracting State Transition Dynamics from Multiple Spike Trains Using Hidden Markov Models with Correlated Poisson Distribution. 2369-2389
• 
  Richard F. Lyon, Martin Rehn, Samy Bengio, Thomas C. Walters, Gal Chechik: Sound Retrieval and Ranking Using Sparse Auditory Representations. 2390-2416
• 
  Hideitsu Hino, Yu Fujimoto, Noboru Murata: A Grouped Ranking Model for Item Preference Parameter. 2417-2451
• 
  Robert C. Wilson, Matthew R. Nassar, Joshua I. Gold: Bayesian Online Learning of the Hazard Rate in Change-Point Problems. 2452-2476

Volume 22, Number 10, October 2010

Article

• 
  Robert Haslinger, Gordon Pipa, Emery N. Brown: Discrete Time Rescaling Theorem: Determining Goodness of Fit for Discrete Time Statistical Models of Neural Spiking. 2477-2506

Letters

• 
  Daniel Calabuig, Jose F. Monserrat, Narcís Cardona: Convergence and Stability of Quantized Hopfield Networks Operating in a Fully Parallel Mode. 2507-2521
• 
  Anne C. Smith, Vinh Kha Nguyen, Mattias P. Karlsson, Loren M. Frank, Peter Smith: Probability of Repeating Patterns in Simultaneous Neural Data. 2522-2536
• 
  N. M. Fernandes, B. D. L. Pinto, Lírio Onofre Baptista de Almeida, Jan Frans Willem Slaets, Roland Köberle: Recording from Two Neurons: Second-Order Stimulus Reconstruction from Spike Trains and Population Coding. 2537-2557
• 
  Aniello Buonocore, Ludovico Caputo, Enrica Pirozzi, Luigi M. Ricciardi: On a Stochastic Leaky Integrate-and-Fire Neuronal Model. 2558-2585
• 
  Satohiro Tajima, Hiromasa Takemura, Ikuya Murakami, Masato Okada: Neuronal Population Decoding Explains the Change in Signal Detection Sensitivity Caused by Task-Irrelevant Perceptual Bias. 2586-2614
• 
  Jun Wang, Hendrik Jan Hoogeboom, Linqiang Pan, Gheorghe Paun, Mario J. Pérez-Jiménez: Spiking Neural P Systems with Weights. 2615-2646
• 
  Mouhamad Jradeh: A New Bidimensional Neural Field Model with Heterogeneous Connection Topology. 2647-2654
• 
  Dongpo Xu, Huisheng Zhang, Lijun Liu: Convergence Analysis of Three Classes of Split-Complex Gradient Algorithms for Complex-Valued Recurrent Neural Networks. 2655-2677
• 
  Youngmin Cho, Lawrence K. Saul: Large-Margin Classification in Infinite Neural Networks. 2678-2697
• 
  Luís M. Silva, Joaquim Marques de Sá, Luís A. Alexandre: The MEE Principle in Data Classification: A Perceptron-Based Analysis. 2698-2728

Volume 22, Number 11, November 2010

Articles

• 
  Tanya Schmah, Grigori Yourganov, Richard S. Zemel, Geoffrey E. Hinton, Steven L. Small, Stephen C. Strother: Comparing Classification Methods for Longitudinal fMRI Studies. 2729-2762

Letters

• 
  Christian Wehrhahn, Harald J. Teufel: How Are Lateral Chromatic Interactions Computed from Cone Signals? 2763-2784
• 
  Alexander J. Dubbs, Brad A. Seiler, Marcelo O. Magnasco: A Fast _p Spike Alignment Metric. 2785-2808
• 
  Chrisantha Fernando, Richard Goldstein, Eörs Szathmáry: The Neuronal Replicator Hypothesis. 2809-2857
• 
  Yiming Ying, Colin Campbell: Rademacher Chaos Complexities for Learning the Kernel Problem. 2858-2886
• 
  Hideitsu Hino, Noboru Murata: A Conditional Entropy Minimization Criterion for Dimensionality Reduction and Multiple Kernel Learning. 2887-2923
• 
  Aree Witoelar, Anarta Ghosh, J. J. G. de Vries, Barbara Hammer, Michael Biehl: Window-Based Example Selection in Learning Vector Quantization. 2924-2961
• 
  Qingshan Liu, Jinde Cao, Guanrong Chen: A Novel Recurrent Neural Network with Finite-Time Convergence for Linear Programming. 2962-2978

Volume 22, Number 12, December 2010

Article

• 
  Stefan Klampfl, Wolfgang Maass: A Theoretical Basis for Emergent Pattern Discrimination in Neural Systems Through Slow Feature Extraction. 2979-3035

Letters

• 
  Reza Moazzezi, Peter Dayan: Change-Based Inference in Attractor Nets: Linear Analysis. 3036-3061
• 
  Hiroyuki Nakahara, Sivaramakrishnan Kaveri: Internal-Time Temporal Difference Model for Neural Value-Based Decision Making. 3062-3106
• 
  Charles F. Cadieu, Kilian Koepsell: Phase Coupling Estimation from Multivariate Phase Statistics. 3107-3126
• 
  Marcel van Gerven, Floris P. de Lange, Tom Heskes: Neural Decoding with Hierarchical Generative Models. 3127-3142
• 
  Bor-Sen Chen, Cheng-Wei Li: Robust Observer-Based Tracking Control of Hodgkin-Huxley Neuron Systems Under Environmental Disturbances. 3143-3178
• 
  Jesús Malo, Valero Laparra: Psychophysically Tuned Divisive Normalization Approximately Factorizes the PDF of Natural Images. 3179-3206
• 
  Dan Claudiu Ciresan, Ueli Meier, Luca Maria Gambardella, Jürgen Schmidhuber: Deep, Big, Simple Neural Nets for Handwritten Digit Recognition. 3207-3220
• 
  Hongzhi Tong, Di-Rong Chen, Fenghong Yang: Least Square Regression with l^p-Coefficient Regularization. 3221-3235