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This article is part of the supplement: Seventeenth Annual Computational Neuroscience Meeting: CNS*2008

Open Access Poster presentation

What you show is what you get: sampling biases in determining biological sensory function

Alexander G Dimitrov

Author Affiliations

Center for Computational Biology, Montana State University, Bozeman, MT 59715, USA

BMC Neuroscience 2008, 9(Suppl 1):P121  doi:10.1186/1471-2202-9-S1-P121


The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1471-2202/9/S1/P121


Published:11 July 2008

© 2008 Dimitrov; licensee BioMed Central Ltd.

Introduction

Classical studies of biological sensory systems use the following main technique: sensory stimuli are drawn from a pre-determined distribution P(stim) and presented to the animal; the ensemble associated with sensory response is collected and used to characterize the conditional distribution P(stim|resp) (or parameters thereof) as a model of sensory system function. However, most of the standard statistical tool used in neuroscience to estimate P(stim|resp) are valid under a very fundamental condition – that the samples used to estimate P(stim|resp) are drawn from the same distribution. This is obviously not the case in most studies of sensory system, where the samples are drawn explicitly from a different distribution, P(stim) (the sampling distribution), selected by the scientist. We demonstrate here that in this case the observed conditional distribution is P*(stim|resp) = P(stim|resp)*P(stim) and expectations estimated with this dataset are parameters of P*, not P. To characterize the actual functional properties of the system, one needs to use estimators developed within unequal probability sampling theory [1]. We apply one of these estimators, the Horvitz-Thompson estimator of the mean mHT = Σi xi/P(xi), to observations {xi} from the cricket cercal sensory system and illustrate the ensuing changes in apparent functionality (Figure 1).

thumbnailFigure 1. The spike-triggered average (STA) of air current stimulis sampled from a band-limited GWN distribution (5–500 Hz) is shown in blue. The corresponding Horvitz-Thompson estimate of the STA is plotted in green.

References

  1. Thomson SK: Sampling. 2nd edition. New York: Wiley Interscience; 2002. OpenURL