deposit_your_work

Limits of population coding

Files in this item

Files Size Format View
Joh2004Jul5Limitsofp.PDF 516.3Kb application/pdf Thumbnail

Show full item record

Item Metadata

Title: Limits of population coding
Author: Johnson, Don
Type: Conference paper
Keywords: population coding; information processing theory; neural information processing
Citation: D. Johnson, "Limits of population coding," 2003.
Abstract: To understand whether the population response expresses information better than the aggregate of the individual responses, the sum of the individual contributions is frequently used as a baseline against which to assess the population's coding capabilities. Using information processing theory, we show that this baseline is illusory: the independent baseline case is theoretically impossible to apply consistently to any population. Instead, we use as a baseline the noncooperative population, in which each neuron processes a common input independently of the others. Using the information transfer ratio, the ratio of Kullback-Leibler distances evaluated at a population's input and output to measure a population's coding ability, we show that cooperative populations can perform either better or worse than this baseline. Furthermore, we show that population coding is effective only when each neuron poorly codes information when considered out of context of the population.
Date Published: 2003-07-20

This item appears in the following Collection(s)

  • ECE Publications [1048 items]
    Publications by Rice University Electrical and Computer Engineering faculty and graduate students
  • DSP Publications [508 items]
    Publications by Rice Faculty and graduate students in digital signal processing.