Volume 11, Number 1, January 1999

• 
  C. E. Carr, M. A. Friedman: Evolution of Time Coding Systems. 1-20

• 
  Steven W. Zucker, Douglas Miller: Computing With Self-Excitatory Cliques: A Model and an Application to Hyperacuity-Scale Computation in Visual Cortex. 21-66

• 
  Corrado Bernasconi, Kaspar Schindler, Ruedi Stoop, Rodney J. Douglas: Complex Response to Periodic Inhibition In Simple and Detailed Neuronal Models. 67-74
• 
  Kechen Zhang, Terrence J. Sejnowski: Neuronal tuning: To Sharpen or Broaden? 75-84
• 
  Alexandre Pouget, Sophie Denève, Jean-Christophe Ducom, Peter E. Latham: Narrow vs Wide Tuning Curves: What's Best for a Population Code? 85-90

• 
  L. F. Abbott, Peter Dayan: The Effect of Correlated Variability on the Accuracy of a Population Code. 91-101
• 
  Dean V. Buonomano, Michael Merzenich: A Neural Network Modell of Temporal Code Generation and Position Invariant Pattern Recognition. 103-116
• 
  Bruce Graham, David J. Willshaw: Probabilistic Synaptic Transmission in the Associative Net. 117-137
• 
  Thore Graepel, Klaus Obermayer: A Stochastic Self-Organizing Map for Proximity Data. 139-155
• 
  Jean-François Cardoso: High-Order Constrasts for Independent Component Analysis. 157-192
• 
  Brendan J. Frey, Geoffrey E. Hinton: Variational Learning in Nonlinear Gaussian Belief Networks. 193-213
• 
  Eric B. Baum, Warren D. Smith: Propagating Distributions Up Directed Acyclic Graphs. 215-227
• 
  Alex Pentland, Andrew Liu: Modeling and Prediction of Human Behavior. 229-242
• 
  Timothy K. Horiuchi, Christof Koch: Analog VLSI-Based Modeling of the Primate Oculomotor System. 243-265
• 
  John Lazzaro, John Wawrzynek: JPEG Quality Transcoding Using Neural Networks Trained With a Perceptual Error Measure. 267-296

Volume 11, Number 2, February 1999

• 
  Sam T. Roweis, Zoubin Ghahramani: A Unifying Review of Linear Gaussian Models. 305-345

• 
  Suzanna Becker: Implicit Learning in 3D Object Recognition: The Importance of Temporal Context. 347-374

• 
  Udo Ernst, Klaus Pawelzik, Misha Tsodyks, Terrence J. Sejnowski: Relation Between Retinotopical and Orientation Maps in Visual Cortex. 375-379

• 
  Florentin Wörgötter, Alex Cozzi, V. Gerdes: A Parallel Noise-Robust Algorithm to Recover Depth Information From Radial Flow Fields. 381-416
• 
  Te-Won Lee, Mark Girolami, Terrence J. Sejnowski: Independent Component Analysis Using an Extended Infomax Algorithm for Mixed Sub-Gaussian and Super-Gaussian Sources. 417-441
• 
  Michael E. Tipping, Christopher M. Bishop: Mixtures of Probabilistic Principal Component Analysers. 443-482
• 
  Ran Avnimelech, Nathan Intrator: Boosted Mixture Of Experts: An Ensemble Learning Scheme. 483-497
• 
  Ran Avnimelech, Nathan Intrator: Boosting Regression Estimators. 499-520
• 
  Isaac David Guedalia, Mickey London, Michael Werman: An On-line Agglomerative Clustering Method for Non-Stationary Data. 521-540
• 
  Anders Krogh, Soren Kamaric Riis: Hidden Neural Networks. 541-563

Volume 11, Number 3, April 1999

• 
  Andrew G. Barto, Andrew H. Fagg, Nathan Sitkoff, James C. Houk: A Cerebellar Model of Timing and Prediction in the Control of Reaching. 565-594

• 
  Luis Garrido, Sergio Gómez, Jaume Roca: Improved Multidimensional Scaling Analysis Using Neural Networks with Distance-Error Backpropagation. 595-600

• 
  Alessandro Treves, Stefano Panzeri, Edmund T. Rolls, Michael Booth, Edward A. Wakeman: Firing Rate Distributions and Efficiency of Information Transmission of Inferior Temporal Cortex Neurons to Natural Visual Stimuli. 601-631
• 
  Stefano Fusi, Maurizio Mattia: Collective Behavior of Networks with Linear (VLSI) Integrate-and-Fire Neurons. 633-652
• 
  Peter Dayan: Recurrent Sampling Models for the Helmholtz Machine. 653-677
• 
  Sepp Hochreiter, Jürgen Schmidhuber: Feature Extraction Through LOCOCODE. 679-714
• 
  Ricard Gavaldà, Hava T. Siegelmann: Discontinuities in Recurrent Neural Networks. 715-745
• 
  Terrence Fine, Sayandev Mukherjee: Parameter Convergence and Learning Curves for Neural Networks. 747-769
• 
  Wolfgang Maass, Eduardo D. Sontag: Analog Neural Nets with Gaussian or Other Common Noise Distribution Cannot Recognize Arbitrary Regular Languages. 771-782
• 
  Randal A. Koene, Yoshio Takane: Discriminant Component Pruning: Regularization and Interpretation of Multi-Layered Back-Propagation Networks. 783-802

Volume 11, Number 4, May 1999

• 
  Hagai Attias: Independent Factor Analysis. 803-851

• 
  Nicol N. Schraudolph: A Fast, Compact Approximation of the Exponential Function. 853-862
• 
  Isabelle Rivals, Léon Personnaz: On Cross Validation for Model Selection. 863-870

• 
  Anthony N. Burkitt, Graeme M. Clark: Analysis of Integrate-and-Fire Neurons: Synchronization of Synaptic Input and Spike Output. 871-901
• 
  Wolfgang Maass, Anthony M. Zador: Dynamic Stochastic Synapses as Computational Units. 903-917
• 
  Gustavo Deco, Bernd Schürmann: Spatiotemporal Coding in the Cortex: Information Flow-Based Learning in Spiking Neural Networks. 919-934
• 
  Shigeru Shinomoto, Yutaka Sakai, Shintaro Funahashi: The Ornstein-Uhlenbeck Process Does Not Reproduce Spiking Statistics of Neurons in Prefrontal Cortex. 935-951
• 
  Erol Gelenbe, Jean-Michel Fourneau: Random Neural Networks with Multiple Classes of Signals. 953-963
• 
  John Sum, Andrew Chi-Sing Leung, Gilbert H. Young, Lai-Wan Chan, Wing-Kay Kan: An Adaptive Bayesian Pruning for Neural Networks in a Non-Stationary Environment. 965-976
• 
  Piërre van de Laar, Tom Heskes: Pruning Using Parameter and Neuronal Metrics. 977-993
• 
  Zehra Cataltepe, Yaser S. Abu-Mostafa, Malik Magdon-Ismail: No Free Lunch for Early Stopping. 995-1009
• 
  Jayanta Basak, Shun-ichi Amari: Blind Separation of a Mixture of Uniformly Distributed Source Signals: A Novel Approach. 1011-1034

Volume 11, Number 5, July 1999

• 
  David J. C. MacKay: Comparison of Approximate Methods for Handling Hyperparameters. 1035-1068

• 
  Danilo P. Mandic, Jonathon A. Chambers: Relating the Slope of the Activation Function and the Learning Rate Within a Recurrent Neural Network. 1069-1077

• 
  Jorge Golowasch, Michael Casey, L. F. Abbott, Eve Marder: Network Stability from Activity-Dependent Regulation of Neuronal Conductances. 1079-1096
• 
  Peter N. Steinmetz, Raimond L. Winslow: Optimal Detection of Flash Intensity Differences Using Rod Photocurrent Observations. 1097-1111
• 
  Paul F. M. J. Verschure, Peter König: On the Role of Biophysical Properties of Cortical Neurons in Binding and Segmentation of Visual Scenes. 1113-1138
• 
  Michael A. Kisley, George L. Gerstein: The Continuum of Operating Modes for a Passive Model Neuron. 1139-1154
• 
  Matthew Brand: Structure Learning in Conditional Probability Models via an Entropic Prior and Parameter Extinction. 1155-1182
• 
  Wenxin Jiang, Martin A. Tanner: On the Approximation Rate of Hierarchical Mixtures-of-Experts for Generalized Linear Models. 1183-1198
• 
  Samy Bengio, Yoshua Bengio, Jacques Robert, Gilles Bélanger: Stochastic Learning of Strategic Equilibria for Auctions. 1199-1209
• 
  Karin Haese: Kalman Filter Implementation of Self-Organizing Feature Maps. 1211-1233
• 
  Wei Wei, Todd K. Leen, Etienne Barnard: A Fast Histogram-Based Postprocessor That Improves Posterior Probability Estimates. 1235-1248
• 
  Don R. Hush: Training a Sigmoidal Node Is Hard. 1249-1260

Volume 11, Number 6, August 1999

• 
  Sidney R. Lehky, Terrence J. Sejnowski: Seeing White: Qualia in the Context of Decoding Population Codes. 1261-1280

• 
  Marco Budinich, Renato Frison: Adaptive Calibration of Imaging Array Detectors. 1281-1296

• 
  I. Fine, Robert A. Jacobs: Modeling the Combination of Motion, Stereo, and Vergence Angle Cues to Visual Depth. 1297-1330
• 
  Florin Cutzu, Michael J. Tarr: Inferring Perceptual Saliency Fields from Viewpoint-Dependent Recognition Data. 1331-1348
• 
  Alfonso Renart, Néstor Parga, Edmund T. Rolls: Backward Projections in the Cerebral Cortex: Implications for Memory Storage. 1349-1388
• 
  D. Chawla, Erik D. Lumer, Karl J. Friston: The Relationship Between Synchronization Among Neuronal Populations and Their Mean Activity Levels. 1389-1411
• 
  Michele Giugliano, Marco Bove, Massimo Grattarola: Fast Calculation of Short-Term Depressing Synaptic Conductances. 1413-1426
• 
  Michael J. Kearns, Dana Ron: Algorithmic Stability and Sanity-Check Bounds for Leave-One-Out Cross-Validation. 1427-1453
• 
  Anand Rangarajan, Alan L. Yuille, Eric Mjolsness: Convergence Properties of the Softassign Quadratic Assignment Algorithm. 1455-1474
• 
  Koji Okuhara, Shunji Osaki, Masaaki Kijima: Learning to Design Synergetic Computers with an Extended Symmetric Diffusion Network. 1475-1491

Volume 11, Number 7, October 1999

• 
  Leo Breiman: Prediction Games and Arcing Algorithms. 1493-1517

• 
  Graeme J. Mitchison, Nicholas V. Swindale: Can Hebbian Volume Learning Explain Discontinuities in Cortical Maps? 1519-1526
• 
  Carlos D. Brody: Disambiguating Different Covariation Types. 1527-1535

• 
  Carlos D. Brody: Correlations Without Synchrony. 1537-1551
• 
  Stefano Panzeri, Alessandro Treves, Simon R. Schultz, Edmund T. Rolls: On Decoding the Responses of a Population of Neurons from Short Time Windows. 1553-1577
• 
  Werner M. Kistler, J. Leo van Hemmen: Short-Term Synaptic Plasticity and Network Behavior. 1579-1594
• 
  Shannon R. Campbell, DeLiang L. Wang, Ciriyam Jayaprakash: Synchrony and Desynchrony in Integrate-and-Fire Oscillators. 1595-1619
• 
  Nicolas Brunel, Vincent Hakim: Fast Global Oscillations in Networks of Integrate-and-Fire Neurons with Low Firing Rates. 1621-1671
• 
  Thomas A. Cleland, Christiane Linster: Concentration Tuning Mediated by Spare Receptor Capacity in Olfactory Sensory Neurons: A Theoretical Study. 1673-1690
• 
  Yali Amit, Donald Geman: A Computational Model for Visual Selection. 1691-1715
• 
  Nir Levy, David Horn, Eytan Ruppin: Associative Memory in a Multimodular Network. 1717-1737
• 
  Aapo Hyvärinen: Sparse Code Shrinkage: Denoising of Nongaussian Data by Maximum Likelihood Estimation. 1739-1768
• 
  George D. Magoulas, Michael N. Vrahatis, George S. Androulakis: Improving the Convergence of the Backpropagation Algorithm Using Learning Rate Adaptation Methods. 1769-1796

Volume 11, Number 8, November 1999

• 
  Amit Manwani, Christof Koch: Detecting and Estimating Signals in Noisy Cable Structures, I: Neuronal Noise Sources. 1797-1829
• 
  Amit Manwani, Christof Koch: Detecting and Estimating Signals in Noisy Cable Structures, II: Information Theoretical Analysis. 1831-1873

• 
  Shun-ichi Amari: Natural Gradient Learning for Over- and Under-Complete Bases in ICA. 1875-1883
• 
  Ethem Alpaydin: Combined 5 x 2 cv F Test for Comparing Supervised Classification Learning Algorithms. 1885-1892

• 
  Jonghan Shin, Christof Koch, Rodney J. Douglas: Adaptive Neural Coding Dependent on the Time-Varying Statistics of the Somatic Input Current. 1893-1913
• 
  Aristidis Likas: A Reinforcement Learning Approach to Online Clustering. 1915-1932
• 
  Marcello Pelillo: Replicator Equations, Maximal Cliques, and Graph Isomorphism. 1933-1955
• 
  Richard M. Everson, Stephen J. Roberts: Independent Component Analysis: A Flexible Nonlinearity and Decorrelating Manifold Approach. 1957-1983
• 
  Jooyoung Park, Hyuk Cho, Daihee Park: On the Design of BSB Neural Associative Memories Using Semidefinite Programming. 1985-1994
• 
  Edward Kei Shiu Ho, Lai-Wan Chan: How to Design a Connectionist Holistic Parser. 1995-2016
• 
  Csaba Szepesvári, Michael L. Littman: A Unified Analysis of Value-Function-Based Reinforcement Learning Algorithms. 2017-2060
• 
  Gal Chechik, Isaac Meilijson, Eytan Ruppin: Neuronal Regulation: A Mechanism for Synaptic Pruning During Brain Maturation. 2061-2080
• 
  Teuvo Kohonen: Comparison of SOM Point Densities Based on Different Criteria. 2081-2095

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