Neural Computation

Volume 22 : Issue 1

Table of Contents

• How to Modify a Neural Network Gradually Without Changing Its Input-Output Functionality 
  Christopher DiMattina and Kechen Zhang
  Page 1
• Current Source Density Reconstruction from Incomplete Data 
  Daniel K. Wjcik and Szymon ski
  Page 48
• Spiking Neuron Model for Temporal Sequence Recognition 
  Sean Byrnes, Anthony N. Burkitt, David B. Grayden and Hamish Meffin
  Page 61
• Mean, Variance, and Autocorrelation of Subthreshold Potential Fluctuations Driven by Filtered Conductance Shot Noise 
  Lars Wolff and Benjamin Lindner
  Page 94
• The Computational Structure of Spike Trains 
  Robert Haslinger, Kristina Lisa Klinkner and Cosma Rohilla Shalizi
  Page 121
• On the Use of Dynamic Bayesian Networks in Reconstructing Functional Neuronal Networks from Spike Train Ensembles 
  Seif Eldawlatly, Yang Zhou, Rong Jin and Karim G. Oweiss
  Page 158
• Visuotactile Representation of Peripersonal Space: A Neural Network Study 
  Elisa Magosso, Melissa Zavaglia, Andrea Serino, Giuseppe di Pellegrino and Mauro Ursino
  Page 190
• Discrete States of Synaptic Strength in a Stochastic Model of Spike-Timing-Dependent Plasticity 
  Terry Elliott
  Page 244
• Hebbian Self-Organizing Integrate-and-Fire Networks for Data Clustering 
  Florian Landis, Thomas Ott and Ruedi Stoop
  Page 273