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Population Coding

  • Stefano Panzeri
  • Fernando Montani
  • Giuseppe Notaro
  • Cesare Magri
  • Rasmus S. Peterson
Part of the Springer Series in Computational Neuroscience book series (NEUROSCI, volume 7)

Abstract

Population coding is the quantitative study of which algorithms or representations are used by the brain to combine together and evaluate the messages carried by different neurons. Here, we review an information-theory-based approach to population coding. We discuss how to quantify the information carried by a neural population and how to quantify the contribution of individual members of the population, or the interaction between them, to the overall information encoded by the considered group of neurons. We present examples of applications of this formalism to simultaneous recordings of multiple spike trains.

Keywords

Mutual Information Spike Train Primary Visual Cortex Individual Neuron Noise Correlation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Stefano Panzeri
    • 1
  • Fernando Montani
    • 1
  • Giuseppe Notaro
    • 1
  • Cesare Magri
    • 1
  • Rasmus S. Peterson
    • 2
  1. 1.Department of Robotics, Brain and Cognitive SciencesItalian Institute of TechnologyGenoaItaly
  2. 2.Faculty of Life SciencesUniversity of ManchesterManchesterUK

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