Optimal integration of independent observations from Poisson sources

Huanping Dai, Emily Buss

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The optimal integration of information from independent Poisson sources (such as neurons) was analyzed in the context of a two-interval, forced-choice detection task. When the mean count of the Poisson distribution is above 1, the benefit of integration is closely approximated by the predictions based on the square-root law of the Gaussian model. When the mean count falls far below 1, however, the benefit of integration clearly exceeds the predictions based on the square-root law.

Original languageEnglish (US)
Pages (from-to)EL20-EL25
JournalJournal of the Acoustical Society of America
Issue number1
Publication statusPublished - Jan 1 2015


ASJC Scopus subject areas

  • Acoustics and Ultrasonics
  • Arts and Humanities (miscellaneous)

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