Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computations collects, by topic, the most significant papers that have appeared in the journal over the past nine years.
The present volume focuses on neural codes and representations, topics of broad interest to neuroscientists and modelers. The topics addressed are: how neurons encode information through action potential firing patterns, how populations of neurons represent information, and how individual neurons use dendritic processing and biophysical properties of synapses to decode spike trains. The papers encompass a wide range of levels of investigation, from dendrites and neurons to networks and systems.
Introduction vii Deciphering the Brains Codes 1(18) Masakazu Konishi A Neural Network for Coding of Trajectories by Time Series of Neuronal Population Vectors 19(10) Alexander V. Lukashin Apostolos P. Georgopoulos Self-Organization of Firing Activities in Monkeys Motor Cortex: Trajectory Computation from Spike Signals 29(16) Siming Lin, Jennie Si A. B. Schwartz Theoretical Considerations for the Analysis of Population Coding in Motor Cortex 45(10) Terence D. Sanger Statistically Efficient Estimation Using Population Coding 55(30) Alexandre Pouget, Kechen Zhang, Sophie Deneve Peter E. Latham Parameter Extraction from Population Codes: A Critical Assessment 85(20) Herman P. Snippe Energy Efficient Neural Codes 105(14) William B. Levy Robert A. Baxter Seeing Beyond the Nyquist Limit 119(10) Daniel L. Ruderman William Bialek A Model of Spatial Map Formation in the Hippocampus of the Rat 129(10) Kenneth I. Blum L. F. Abbott Probabilistic Interpretation of Population Codes 139(28) Richard S. Zemel Peter Dayan Alexandre Pouget Cortical Cells Should Fire Regularly, But Do Not 167(4) William R. Softky Christof Koch Role of Temporal Integration and Fluctuation Detection in the Highly Irregular Firing of a Leaky Integrator Neuron Model with Partial Reset 171(16) Guido Bugmann, Chris Christodoulou John G. Taylor Physiological Gain Leads to High ISI Variability in a Simple Model of a Cortical Regular Spiking Cell 187(14) Todd W. Troyer Kenneth D. Miller Coding of Time-Varying Signals in Spike Trains of Integrate-and-Fire Neurons with Random Threshold 201(24) Fabrizio Gabbiani Christof Koch Temporal Precision of Spike Trains in Extrastriate Cortex of the Behaving Macaque Monkey 225(18) Wyeth Bair Christof Koch Conversion of Temporal Correlations Between Stimuli to Spatial Correlations Between Attractors 243(18) M. Griniasty, M. V. Tsodyks, Daniel J. Amit Neural Network Model of the Cerebellum: Temporal Discrimination and the Timing of Motor Responses 261(18) Dean V. Buonomano Michael D. Mauk Gamma Oscillation Model Predicts Intensity Coding by Phase Rather than Frequency 279(14) Roger D. Traub Miles A. Whittington, John G. R. Jefferys Effects of Input Synchrony on the Firing Rate of a Three-Conductance Cortical Neuron Model 293(16) Venkatesh N. Murthy Eberhard E. Fetz NMDA-Based Pattern Discrimination in a Modeled Cortical Neuron 309(16) Bartlett W. Mel The Impact of Parallel Fiber Background Activity on the Cable Properties of Cerebellar Purkinje Cells 325(16) Moshe Rapp Yosef Yarom Idan Segev Index 341
