Neural Computation, Volume 17

Volume 17, Number 1, January 2005

• Christopher K. I. Williams:
  How to Pretend That Correlated Variables Are Independent by Using Difference Observations. 1-6
  
• Fernando Pérez-Cruz, Carlos Bousoño-Calzón, Antonio Artés-Rodríguez:
  Convergence of the IRWLS Procedure to the Support Vector Machine Solution. 7-18
  

• Evan Smith, Michael S. Lewicki:
  Efficient Coding of Time-Relative Structure Using Spikes. 19-45
  
• David B. Grimes, Rajesh P. N. Rao:
  Bilinear Sparse Coding for Invariant Vision. 47-73
  
• Rishikesh Narayanan, Anusha Narayan, Sumantra Chattarji:
  A Probabilistic Framework for Region-Specific Remodeling of Dendrites in Three-Dimensional Neuronal Reconstructions. 75-96
  
• H. J. Tang, Kay Chen Tan, Weinian Zhang:
  Analysis of Cyclic Dynamics for Networks of Linear Threshold Neurons. 97-114
  
• Shin-ichi Maeda, Wen-Jie Song, Shin Ishii:
  Nonlinear and Noisy Extension of Independent Component Analysis: Theory and Its Application to a Pitch Sensation Model. 115-144
  
• Koby Crammer, Yoram Singer:
  Online Ranking by Projecting. 145-175
  
• Charles A. Micchelli, Massimiliano Pontil:
  On Learning Vector-Valued Functions. 177-204
  
• Kai Keng Ang, Hiok Chai Quek:
  RSPOP: Rough Set-Based Pseudo Outer-Product Fuzzy Rule Identification Algorithm. 205-243
  

Volume 17, Number 2, February 2005

• Florentin Wörgötter, Bernd Porr:
  Temporal Sequence Learning, Prediction, and Control: A Review of Different Models and Their Relation to Biological Mechanisms. 245-319
  

• Shengli Xie, Zhaoshui He, Yuli Fu:
  A Note on Stone's Conjecture of Blind Signal Separation. 321-330
  
• Jinwen Ma, Zhiyong Liu, Lei Xu:
  A Further Result on the ICA One-Bit-Matching Conjecture. 331-334
  

• Jun Morimoto, Kenji Doya:
  Robust Reinforcement Learning. 335-359
  
• Andrew James Smith, Suzanna Becker, Shitij Kapur:
  A Computational Model of the Functional Role of the Ventral-Striatal D2 Receptor in the Expression of Previously Acquired Behaviors. 361-395
  
• Yan Karklin, Michael S. Lewicki:
  A Hierarchical Bayesian Model for Learning Nonlinear Statistical Regularities in Nonstationary Natural Signals. 397-423
  
• Kun Zhang, Lai-Wan Chan:
  Extended Gaussianization Method for Blind Separation of Post-Nonlinear Mixtures. 425-452
  
• A. Menchero, Raquel Montes Diez, David Ríos Insua, Peter Müller:
  Bayesian Analysis of Nonlinear Autoregression Models Based on Neural Networks. 453-485
  
• David Windisch:
  Loading Deep Networks Is Hard: The Pyramidal Case. 487-502
  

Volume 17, Number 3, March 2005

• Marc M. Van Hulle:
  Maximum Likelihood Topographic Map Formation. 503-513
  
• Youshen Xia, Gang Feng:
  On Convergence Conditions of an Extended Projection Neural Network. 515-525
  

• Leslie G. Valiant:
  Memorization and Association on a Realistic Neural Model. 527-555
  
• Christoph Börgers, Nancy Kopell:
  Effects of Noisy Drive on Rhythms in Networks of Excitatory and Inhibitory Neurons. 557-608
  
• Christian D. Swinehart, L. F. Abbott:
  Supervised Learning Through Neuronal Response Modulation. 609-631
  
• Benjamin Pfeuty, Germán Mato, David Golomb, David Hansel:
  The Combined Effects of Inhibitory and Electrical Synapses in Synchrony. 633-670
  
• Lavi Shpigelman, Yoram Singer, Rony Paz, Eilon Vaadia:
  Spikernels: Predicting Arm Movements by Embedding Population Spike Rate Patterns in Inner-Product Spaces. 671-690
  
• Yuval Aviel, David Horn, Moshe Abeles:
  Memory Capacity of Balanced Networks. 691-713
  
• Michael Schmitt:
  On the Capabilities of Higher-Order Neurons: A Radial Basis Function Approach. 715-729
  
• Amir F. Atiya:
  Estimating the Posterior Probabilities Using the K-Nearest Neighbor Rule. 731-740
  

Volume 17, Number 4, April 2005

• Eric E. Thomson, William B. Kristan Jr.:
  Quantifying Stimulus Discriminability: A Comparison of Information Theory and Ideal Observer Analysis. 741-778
  
• Simone Fiori:
  Nonlinear Complex-Valued Extensions of Hebbian Learning: An Essay. 779-838
  

• Shun-ichi Amari, Hiroyuki Nakahara:
  Difficulty of Singularity in Population Coding. 839-858
  
• Rudy Guyonneau, Rufin van Rullen, Simon J. Thorpe:
  Neurons Tune to the Earliest Spikes Through STDP. 859-879
  
• Shawn Mikula, Ernst Niebur:
  Rate and Synchrony in Feedforward Networks of Coincidence Detectors: Analytical Solution. 881-902
  
• William W. Lytton, Michael L. Hines:
  Independent Variable Time-Step Integration of Individual Neurons for Network Simulations. 903-921
  
• Magnus J. E. Richardson, Wulfram Gerstner:
  Synaptic Shot Noise and Conductance Fluctuations Affect the Membrane Voltage with Equal Significance. 923-947
  
• Tianping Chen, Wenlian Lu, Guanrong Chen:
  Dynamical Behaviors of a Large Class of General Delayed Neural Networks. 949-968
  
• Damián Oliva, Inés Samengo, Stefan Leutgeb, Sheri J. Mizumori:
  A Subjective Distance Between Stimuli: Quantifying the Metric Structure of Representations. 969-990
  

Volume 17, Number 5, May 2005

• Denis Burdakov:
  Gain Control by Concerted Changes in I_A and I_H Conductances. 991-995
  
• Jens Christian Claussen:
  Winner-Relaxing Self-Organizing Maps. 996-1009
  

• Joachim M. Buhmann, Tilman Lange, Ulrich Ramacher:
  Image Segmentation by Networks of Spiking Neurons. 1010-1031
  
• Tadashi Yamazaki, Shigeru Tanaka:
  Neural Modeling of an Internal Clock. 1032-1058
  
• Reiner Schulz, James A. Reggia:
  Mirror Symmetric Topographic Maps Can Arise from Activity-Dependent Synaptic Changes. 1059-1083
  
• Emanuel Todorov:
  Stochastic Optimal Control and Estimation Methods Adapted to the Noise Characteristics of the Sensorimotor System. 1084-1108
  
• Barbara Hammer, Alessio Micheli, Alessandro Sperduti:
  Universal Approximation Capability of Cascade Correlation for Structures. 1109-1159
  
• Qiang Wu, Ding-Xuan Zhou:
  SVM Soft Margin Classifiers: Linear Programming versus Quadratic Programming. 1160-1187
  
• Ming-Wei Chang, Chih-Jen Lin:
  Leave-One-Out Bounds for Support Vector Regression Model Selection. 1188-1222
  

Volume 17, Number 6, June 2005

• Henrik Jacobsson:
  Rule Extraction from Recurrent Neural Networks: A Taxonomy and Review. 1223-1263
  

• Yoram Baram:
  Learning by Kernel Polarization. 1264-1275
  

• Chris Eliasmith:
  A Unified Approach to Building and Controlling Spiking Attractor Networks. 1276-1314
  
• Takashi Kanamaru, Masatoshi Sekine:
  Synchronized Firings in the Networks of Class 1 Excitable Neurons with Excitatory and Inhibitory Connections and Their Dependences on the Forms of Interactions. 1315-1338
  
• Jean-Paul Banquet, Philippe Gaussier, Mathias Quoy, Arnaud Revel, Yves Burnod:
  A Hierarchy of Associations in Hippocampo-Cortical Systems: Cognitive Maps and Navigation Strategies. 1339-1384
  
• Faming Liang:
  Evidence Evaluation for Bayesian Neural Networks Using Contour Monte Carlo. 1385-1410
  
• Kian Hsiang Low, Wee Kheng Leow, Marcelo H. Ang Jr.:
  An Ensemble of Cooperative Extended Kohonen Maps for Complex Robot Motion Tasks. 1411-1445
  

Volume 17, Number 7, July 2005

• Arnaud Tonnelier:
  Categorization of Neural Excitability Using Threshold Models. 1447-1455
  

• Gabriela Czanner, Sonja Grün, Satish Iyengar:
  Theory of the Snowflake Plot and Its Relations to Higher-Order Analysis Methods. 1456-1479
  
• Liam Paninski:
  Asymptotic Theory of Information-Theoretic Experimental Design. 1480-1507
  
• Bruno Jedynak, Sanjeev Khudanpur:
  Maximum Likelihood Set for Estimating a Probability Mass Function. 1508-1530
  
• Matthew B. Kennel, Jonathon Shlens, Henry D. I. Abarbanel, E. J. Chichilnisky:
  Estimating Entropy Rates with Bayesian Confidence Intervals. 1531-1576
  
• Michael Stiber:
  Spike Timing Precision and Neural Error Correction: Local Behavior. 1577-1601
  
• Christian G. Habeck, John W. Krakauer, Claude Ghez, Harold A. Sackeim, David Eidelberg, Yaakov Stern, James Ralph Moeller:
  A New Approach to Spatial Covariance Modeling of Functional Brain Imaging Data: Ordinal Trend Analysis. 1602-1645
  
• Elko B. Tchernev, Rory G. Mulvaney, Dhananjay S. Phatak:
  Investigating the Fault Tolerance of Neural Networks. 1646-1664
  

Volume 17, Number 8, August 2005

• Bruno A. Olshausen, David J. Field:
  How Close Are We to Understanding V1? 1665-1699
  

• Alireza S. Mahani, Ralf Wessel:
  Motion Contrast Classification Is a Linearly Nonseparable Problem. 1700-1705
  
• Marc M. Van Hulle:
  Edgeworth-Expanded Gaussian Mixture Density Modeling. 1706-1714
  

• Prashant Joshi, Wolfgang Maass:
  Movement Generation with Circuits of Spiking Neurons. 1715-1738
  
• Osamu Hoshino:
  Cognitive Enhancement Mediated Through Postsynaptic Actions of Norepinephrine on Ongoing Cortical Activity. 1739-1775
  
• Abigail Morrison, Carsten Mehring, Theo Geisel, Ad Aertsen, Markus Diesmann:
  Advancing the Boundaries of High-Connectivity Network Simulation with Distributed Computing. 1776-1801
  
• Miguel A. Atencia Ruiz, Gonzalo Joya Caparrós, Francisco Sandoval Hernández:
  Dynamical Analysis of Continuous Higher-Order Hopfield Networks for Combinatorial Optimization. 1802-1819
  
• Jito Vanualailai, Shin-ichi Nakagiri:
  Some Generalized Sufficient Convergence Criteria for Nonlinear Continuous Neural Networks. 1820-1835
  
• Payam Pakzad, Venkat Anantharam:
  Estimation and Marginalization Using the Kikuchi Approximation Methods. 1836-1873
  

Volume 17, Number 9, September 2005

• Simon Haykin, Zhe Chen:
  The Cocktail Party Problem. 1875-1902
  

• Marc M. Van Hulle:
  Edgeworth Approximation of Multivariate Differential Entropy. 1903-1910
  
• Elko B. Tchernev, Rory G. Mulvaney, Dhananjay S. Phatak:
  Perfect Fault Tolerance of the n-k-n Network. 1911-1920
  
• Kaare Brandt Petersen, Ole Winther, Lars Kai Hansen:
  On the Slow Convergence of EM and VBEM in Low-Noise Linear Models. 1921-1926
  

• Murat Okatan, Matthew A. Wilson, Emery N. Brown:
  Analyzing Functional Connectivity Using a Network Likelihood Model of Ensemble Neural Spiking Activity. 1927-1961
  
• G. Pola, Rasmus S. Petersen, A. Thiele, Malcolm P. Young, Stefano Panzeri:
  Data-Robust Tight Lower Bounds to the Information Carried by Spike Times of a Neuronal Population. 1962-2005
  
• Ilya Nemenman:
  Fluctuation-Dissipation Theorem and Models of Learning. 2006-2033
  
• Kosuke Hamaguchi, Masato Okada, Michiko Yamana, Kazuyuki Aihara:
  Correlated Firing in a Feedforward Network with Mexican-Hat-Type Connectivity. 2034-2059
  
• Pierre A. Fortier, Emmanuel Guigon, Yves Burnod:
  Supervised Learning in a Recurrent Network of Rate-Model Neurons Exhibiting Frequency Adaptation. 2060-2076
  
• Tong Zhang:
  Learning Bounds for Kernel Regression Using Effective Data Dimensionality. 2077-2098
  

Volume 17, Number 10, October 2005

• Tobias Glasmachers, Christian Igel:
  Gradient-Based Adaptation of General Gaussian Kernels. 2099-2105
  

• Walter Senn, Stefano Fusi:
  Learning Only When Necessary: Better Memories of Correlated Patterns in Networks with Bounded Synapses. 2106-2138
  
• Naoki Masuda, Brent Doiron, André Longtin, Kazuyuki Aihara:
  Coding of Temporally Varying Signals in Networks of Spiking Neurons with Global Delayed Feedback. 2139-2175
  
• Pieter R. Roelfsema, Arjen van Ooyen:
  Attention-Gated Reinforcement Learning of Internal Representations for Classification. 2176-2214
  
• Si Wu, Shun-ichi Amari:
  Computing with Continuous Attractors: Stability and Online Aspects. 2215-2239
  
• Petr Lánský, Priscilla E. Greenwood:
  Optimal Signal Estimation in Neuronal Models. 2240-2257
  
• Thomas Wennekers, Nihat Ay:
  Finite State Automata Resulting from Temporal Information Maximization and a Temporal Learning Rule. 2258-2290
  
• Rohana K. Rajapakse, Michael J. Denham:
  Fast Access to Concepts in Concept Lattices via Bidirectional Associative Memories. 2291-2300
  

Volume 17, Number 11, November 2005

• Michael Rudolph, Alain Destexhe:
  An Extended Analytic Expression for the Membrane Potential Distribution of Conductance-Based Synaptic Noise. 2301-2315
  

• Peter A. Appleby, Terry Elliott:
  Synaptic and Temporal Ensemble Interpretation of Spike-Timing-Dependent Plasticity. 2316-2336
  
• Robert A. Legenstein, Christian Naeger, Wolfgang Maass:
  What Can a Neuron Learn with Spike-Timing-Dependent Plasticity? 2337-2382
  
• Claude Meunier, Karol Borejsza:
  How Membrane Properties Shape the Discharge of Motoneurons: A Detailed Analytical Study. 2383-2420
  
• Paul H. E. Tiesinga:
  Stimulus Competition by Inhibitory Interference. 2421-2453
  
• Terence Kwok, Kate A. Smith:
  Optimization via Intermittency with a Self-Organizing Neural Network. 2454-2481
  
• Qi Zhao, David J. Miller:
  Mixture Modeling with Pairwise, Instance-Level Class Constraints. 2482-2507
  
• Kazushi Ikeda, Noboru Murata:
  Geometrical Properties of Nu Support Vector Machines with Different Norms. 2508-2529
  

Volume 17, Number 12, December 2005

• Michiel Berends, Reinoud Maex, Erik De Schutter:
  The Effect of NMDA Receptors on Gain Modulation. 2531-2547
  
• Dominique Martinez:
  Oscillatory Synchronization Requires Precise and Balanced Feedback Inhibition in a Model of the Insect Antennal Lobe. 2548-2570
  
• Xuedong Zhang, Laurel H. Carney:
  Response Properties of an Integrate-and-Fire Model That Receives Subthreshold Inputs. 2571-2601
  
• Sethu Vijayakumar, Aaron D'Souza, Stefan Schaal:
  Incremental Online Learning in High Dimensions. 2602-2634
  
• Jirí Síma, Jiri Sgall:
  On the Nonlearnability of a Single Spiking Neuron. 2635-2647
  
• Zhe Chen, Suzanna Becker, Jeff Bondy, Ian C. Bruce, Simon Haykin:
  A Novel Model-Based Hearing Compensation Design Using a Gradient-Free Optimization Method. 2648-2671
  
• Qing Song:
  A Robust Information Clustering Algorithm. 2672-2698
  
• Justin Werfel, Xiaohui Xie, H. Sebastian Seung:
  Learning Curves for Stochastic Gradient Descent in Linear Feedforward Networks. 2699-2718
  
• Kazushi Ikeda:
  Information Geometry of Interspike Intervals in Spiking Neurons. 2719-2735
  

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