Quantifying information and performance for flash detection in the blowfly photoreceptor.

Neural Netw

Department of Electrical and Computer Engineering and the Institute for Systems Research, University of Maryland, College Park, MD 20742, USA.

Published: November 2005

Performance on specific tasks in an organism's everyday activities is essential to survival. In this paper, we extend information-theoretic investigation of neural systems to task specific information using a detailed biophysical model of the blowfly photoreceptor. We determine the optimal detection performance using ideal observer analysis and find that detection threshold increases with background light according to a power function. We show how Fisher information is related to the detection performance and compare Fisher information and mutual information in this task-specific context. Our detailed model of the blowfly photoreceptor enables us to detangle the components of phototransduction and analyze the sensitivity of detection performance with respect to biophysical parameters. The biophysical model of the blowfly photoreceptor provides a rich framework for investigation of neural systems.

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http://dx.doi.org/10.1016/j.neunet.2005.06.004DOI Listing

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