Optimal integration of independent observations from Poisson sources | Zendy

Huanping Dai | Zendy; Emily Buss | Zendy

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Optimal integration of independent observations from Poisson sources

Author(s) -

Huanping Dai,

Emily Buss

Publication year - 2014

Publication title -

the journal of the acoustical society of america

Language(s) - English

Resource type - Journals

eISSN - 1520-8524

pISSN - 0001-4966

DOI - 10.1121/1.4903228

Subject(s) - poisson distribution , square root , context (archaeology) , gaussian , numerical integration , poisson regression , mathematics , count data , interval (graph theory) , square (algebra) , statistics , statistical physics , mathematical analysis , geology , physics , combinatorics , geometry , paleontology , population , demography , quantum mechanics , sociology

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.

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