Abstract
The present work shows that the maximum-entropy method can be applied to a sample of neuronal recordings along two different routes: (1) apply to the sample; or (2) apply to a larger, unsampled neuronal population from which the sample is drawn, and then marginalize to the sample. These two routes give inequivalent results. The second route can be further generalized to the case where the size of the larger population is unknown. Which route should be chosen? Some arguments are presented in favour of the second. This work also presents and discusses probability formulae that relate states of knowledge about a population and its samples, and that may be useful for sampling problems in neuroscience.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
pgl{at}portamana.org
vrostami{at}uni-koeln.de
emiliano.torre{at}yahoo.com
yasser.roudi{at}ntnu.no
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