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1 Lehrstuhl fuer Neurobiologie, Bielefeld University, Bielefeld, Germany
2 Department of Zoology, University of Cambridge, Cambridge, United Kingdom
* To whom correspondence should be addressed. E-mail: kkarmeier{at}uni-bielefeld.de.
Coding of sensory information often involves the activity of neuronal populations. We demonstrate how the accuracy of a population code depends on integration time, the size of the population and on noise correlation between the participating neurons. The population we study consists of ten identified visual interneurons in the blowfly Calliphora vicina involved in optic flow processing. These neurons are assumed to encode the animal's head or body rotations around horizontal axes by means of graded potential changes. From electrophysiological experiments we obtain parameters for modeling the neurons' responses. From applying a Bayesian analysis on the modeled population response we draw three major conclusions. (1) Integration of neuronal activities over a time period of only 5 ms after response onset is sufficient to decode accurately the rotation axis. (2) Noise correlation between neurons has only little impact on the population's performance. (3) Although a population of only two neurons would be sufficient to encode any horizontal rotation axis, the population of ten VS-neurons is advantageous, if the available integration time is short. For the fly short integration times to decode neuronal responses are important when controlling rapid flight maneuvers.
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