Neural Computation, Volume 6

Volume 6, Number 1, January 1994

• Granger G. Sutton III, James A. Reggia, Steven L. Armentrout, C. Lynne D'Autrechy:
  Cortical Map Reorganization as a Competitive Process. 1-13
  

• Alain Destexhe, Zachary F. Mainen, Terrence J. Sejnowski:
  An Efficient Method for Computing Synaptic Conductances Based on a Kinetic Model of Receptor Binding. 14-18
  

• Alexander V. Lukashin, Apostolos P. Georgopoulos:
  A Neural Network for Coding of Trajectories by Time Series of Neuronal Population Vectors. 19-28
  
• Terence D. Sanger:
  Theoretical Considerations for the Analysis of Population Coding in Motor Cortex. 29-37
  
• Dean V. Buonomano, Michael D. Mauk:
  Neural Network Model of the Cerebellum: Temporal Discrimination and the Timing of Motor Responses. 38-55
  
• Allan Gottschalk, Malcolm D. Ogilvie, Diethelm W. Richter, Allan I. Pack:
  Computational Aspects of the Respiratory Pattern Generator. 56-68
  
• Thomas LoFaro, Nancy Kopell, Eve Marder, Scott L. Hooper:
  Subharmonic Coordination in Networks of Neurons with Slow Conductances. 69-84
  
• Ali A. Minai, William B. Levy:
  Setting the Activity Level in Sparse Random Networks. 85-99
  
• Kenneth D. Miller, David J. C. MacKay:
  The Role of Constraints in Hebbian Learning. 100-126
  
• Zhaoping Li, Joseph J. Atick:
  Toward a Theory of the Striate Cortex. 127-146
  
• Barak A. Pearlmutter:
  Fast Exact Multiplication by the Hessian. 147-160
  
• Andrew H. Gee, Richard W. Prager:
  Polyhedral Combinatorics and Neural Networks. 161-180
  

Volume 6, Number 2, March 1994

• Michael I. Jordan, Robert A. Jacobs:
  Hierarchical Mixtures of Experts and the EM Algorithm. 181-214
  

• Gerald Tesauro:
  TD-Gammon, a Self-Teaching Backgammon Program, Achieves Master-Level Play. 215-219
  
• L. F. Cugliandolo:
  Correlated Attractors from Uncorrelated Stimuli. 220-224
  

• Bard Ermentrout, Nancy Kopell:
  Learning of Phase Lags in Coupled Neural Oscillators. 225-241
  
• Mark E. Nelson:
  A Mechanism for Neuronal Gain Control by Descending Pathways. 242-254
  
• Geoffrey J. Goodhill, Harry G. Barrow:
  The Role of Weight Normalization in Competitive Learning. 255-269
  
• Stephen J. Roberts, Lionel Tarassenko:
  A Probabilistic Resource Allocating Network for Novelty Detection. 270-284
  
• William Finnoff:
  Diffusion Approximations for the Constant Learning Rate Backpropagation Algorithm and Resistance to Local Minima. 285-295
  
• Françoise Beaufays, Eric A. Wan:
  Relating Real-Time Backpropagation and Backpropagation-Through-Time: An Application of Flow Graph Interreciprocity. 296-306
  
• Pierre Baldi, Yves Chauvin:
  Smooth On-Line Learning Algorithms for Hidden Markov Models. 307-318
  
• Michel Benaïm:
  On Functional Approximation with Normalized Gaussian Units. 319-333
  
• Alan L. Yuille, Paul E. Stolorz, Joachim Utans:
  Statistical Physics, Mixtures of Distributions, and the EM Algorithm. 334-340
  

Volume 6, Number 3, May 1994

• Alan L. Yuille, J. J. Kosowsky:
  Statistical Physics Algorithms That Converge. 341-356
  

• Randall C. O'Reilly, Mark H. Johnson:
  Object Recognition and Sensitive Periods: A Computational Analysis of Visual Imprinting. 357-389
  

• Ning Qian:
  Computing Stereo Disparity and Motion with Known Binocular Cell Properties. 390-404
  
• Edwin E. Munro, Larry E. Shupe, Eberhard E. Fetz:
  Integration and Differentiation in Dynamic Recurrent Neural Networks. 405-419
  
• Chung-Ming Kuan, Kurt Hornik, Halbert White:
  A Convergence Result for Learning in Recurrent Neural Networks. 420-440
  
• Csaba Szepesvári, László Balázs, András Lörincz:
  Topology Learning Solved by Extended Objects: A Neural Network Model. 441-458
  
• Pascal Koiran:
  Dynamics of Discrete Time, Continuous State Hopfield Networks. 459-468
  
• K. P. Unnikrishnan, Kootala P. Venugopal:
  Alopex: A Correlation-Based Learning Algorithm for Feedforward and Recurrent Neural Networks. 469-490
  
• Jean-Pierre Nadal, Néstor Parga:
  Duality Between Learning Machines: A Bridge Between Supervised and Unsupervised Learning. 491-508
  
• Hong Pi, Carsten Peterson:
  Finding the Embedding Dimension and Variable Dependencies in Time Series. 509-520
  
• Dimitry Gorinevsky, Thomas H. Connolly:
  Comparison of Some Neural Network and Scattered Data Approximations: The Inverse Manipulator Kinematics Example. 521-542
  
• Vera Kurková, Paul C. Kainen:
  Functionally Equivalent Feedforward Neural Networks. 543-558
  

Volume 6, Number 4, July 1994

• David J. Field:
  What Is the Goal of Sensory Coding? 559-601
  

• Ernst Niebur, Florentin Wörgötter:
  Design Principles of Columnar Organization in Visual Cortex. 602-614
  

• Geoffrey J. Goodhill, David J. Willshaw:
  Elastic Net Model of Ocular Dominance: Overall Stripe Pattern and Monocular Deprivation. 615-621
  
• Öjvind Bernander, Christof Koch, Marius Usher:
  The Effect of Synchronized Inputs at the Single Neuron Level. 622-641
  
• Haim Sompolinsky, Michail Tsodyks:
  Segmentation by a Network of Oscillators with Stored Memories. 642-657
  
• Yukio Hayashi:
  Numerical Bifurcation Analysis of an Oscillatory Neural Network with Synchronous/Asynchronous Connections. 658-667
  
• J. Devin McAuley, Joseph Stampfli:
  Analysis of the Effects of Noise on a Model for the Neural Mechanism of Short-Term Active Memory. 668-678
  
• Bard Ermentrout:
  Reduction of Conductance-Based Models with Slow Synapses to Neural Nets. 679-695
  
• Kenji Doya, Allen I. Selverston:
  Dimension Reduction of Biological Neuron Models by Artificial Neural Networks. 696-717
  
• Gary M. Scott, W. Harmon Ray:
  Neural Network Process Models Based on Linear Model Structures. 718-738
  
• Juha Karhunen:
  Stability of Oja's PCA Subspace Rule. 739-747
  
• Man-Fung Cheung, Kevin M. Passino, Stephen Yurkovich:
  Supervised Training of Neural Networks via Ellipsoid Algorithms. 748-760
  
• N. Scott Cardell, Wayne H. Joerding, Ying Li:
  Why Some Feedforward Networks Cannot Learn Some Polynomials. 761-766
  

Volume 6, Number 5, September 1994

• Stephen P. Luttrell:
  A Bayesian Analysis of Self-Organizing Maps. 767-794
  
• Marius Usher, Martin Stemmler, Christof Koch, Zeev Olami:
  Network Amplification of Local Fluctuations Causes High Spike Rate Variability, Fractal Firing Patterns and Oscillatory Local Field Potentials. 795-836
  

• Alan M. N. Fu:
  Statistical Analysis of an Autoassociative Memory Network. 837-841
  

• Jirí Síma:
  Loading Deep Networks Is Hard. 842-850
  
• Vladimir Vapnik, Esther Levin, Yann LeCun:
  Measuring the VC-Dimension of a Learning Machine. 851-876
  
• Wolfgang Maass:
  Neural Nets with Superlinear VC-Dimension. 877-884
  
• Jihong Lee:
  A Novel Design Method for Multilayer Feedforward Neural Networks. 885-901
  
• Jean-Dominique Gascuel, Bahram Moobed, Michel Weinfeld:
  An Internal Mechanism for Detecting Parasite Attractors in a Hopfield Network. 902-915
  
• Thorsteinn Rögnvaldsson:
  On Langevin Updating in Multilayer Perceptrons. 916-926
  
• Hossam Osman, Moustafa M. Fahmy:
  Probabilistic Winner-Take-All Learning Algorithm for Radial-Basis-Function Neural Classifiers. 927-943
  
• T. Matsumoto, K. Kondo:
  Realization of the "Weak Rod" by a Double Layer Parallel Network. 944-956
  
• Daniel J. Amit, Stefano Fusi:
  Learning in Neural Networks with Material Synapses. 957-982
  
• Pierre-Yves Burgi, Norberto M. Grzywacz:
  Model Based on Extracellular Potassium for Spontaneous Synchronous Activity in Developing Retinas. 983-1004
  
• Michael S. Lewicki:
  Bayesian Modeling and Classification of Neural Signals. 1005-1030
  

Volume 6, Number 6, November 1994

• Bartlett W. Mel:
  Information Processing in Dendritic Trees. 1031-1085
  

• Paul A. Rhodes, Charles M. Gray:
  Simulations of Intrinsically Bursting Neocortical Pyramidal Neurons. 1086-1110
  
• Venkatesh N. Murthy, Eberhard E. Fetz:
  Effects of Input Synchrony on the Firing Rate of a Three-Conductance Cortical Neuron Model. 1111-1126
  
• Ying-Cheng Lai, Raimond L. Winslow, Murray B. Sachs:
  The Functional Role of Excitatory and Inhibitory Interactions in Chopper Cells of the Anteroventral Cochlear Nucleus. 1127-1140
  
• Carlos Lourenço, Agnessa Babloyantz:
  Control of Chaos in Networks with Delay: A Model for Synchronization of Cortical Tissue. 1141-1154
  
• Peter Manolios, Robert Fanelli:
  First-Order Recurrent Neural Networks and Deterministic Finite State Automata. 1155-1173
  
• Lawrence K. Saul, Michael I. Jordan:
  Learning in Boltzmann Trees. 1174-1184
  
• Tommi Jaakkola, Michael I. Jordan, Satinder P. Singh:
  On the Convergence of Stochastic Iterative Dynamic Programming Algorithms. 1185-1201
  
• R. S. Shadafan, M. Niranjan:
  A Dynamic Neural Network Architecture by Sequential Partitioning of the Input Space. 1202-1222
  
• Lars Kai Hansen, Carl Edward Rasmussen:
  Pruning from Adaptive Regularization. 1223-1232
  
• Yoshifusa Ito:
  Approximation Capability of Layered Neural Networks with Sigmoid Units on Two Layers. 1233-1243
  
• Motoaki Kawanabe, Shun-ichi Amari:
  Estimation of Network Parameters in Semiparametric Stochastic Perceptron. 1244-1261
  
• Kurt Hornik, Maxwell B. Stinchcombe, Halbert White, Peter Auer:
  Degree of Approximation Results for Feedforward Networks Approximating Unknown Mappings and Their Derivatives. 1262-1275
  
• Yong Liu:
  Influence Function Analysis of PCA and BCM Learning. 1276-1288
  
• Harris Drucker, Corinna Cortes, Lawrence D. Jackel, Yann LeCun, Vladimir Vapnik:
  Boosting and Other Ensemble Methods. 1289-1301