Volume 17, Number 1, January 2005

Notes

• 
  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

Letters

• 
  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

Reviews

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

Notes

• 
  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

Letters

• 
  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

Notes

• 
  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

Letters

• 
  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

Reviews

• 
  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

Letters

• 
  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

Notes

• 
  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

Letters

• 
  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

Reviews

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

Notes

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

Letters

• 
  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

Notes

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

Letters

• 
  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

Reviews

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

Notes

• 
  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

Letters

• 
  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

Reviews

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

Notes

• 
  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

Letters

• 
  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

Notes

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

Letters

• 
  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

Notes

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

Letters

• 
  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

Letters

• 
  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