2011
DOI: 10.1371/journal.pone.0022996
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Modeling Peripheral Olfactory Coding in Drosophila Larvae

Abstract: The Drosophila larva possesses just 21 unique and identifiable pairs of olfactory sensory neurons (OSNs), enabling investigation of the contribution of individual OSN classes to the peripheral olfactory code. We combined electrophysiological and computational modeling to explore the nature of the peripheral olfactory code in situ. We recorded firing responses of 19/21 OSNs to a panel of 19 odors. This was achieved by creating larvae expressing just one functioning class of odorant receptor, and hence OSN. Odor… Show more

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Cited by 20 publications
(24 citation statements)
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“…Further, the larval odor receptor repertoire has been comprehensively tested in terms of electrophysiological responsiveness to odors in the “empty neuron” system ( Dobritsa et al, 2003 ; Kreher et al, 2008 ). Calcium imaging studies and direct recordings from larval olfactory sensory neurons have led to similar conclusions about the receptive ranges of odor receptors, supporting assignment of ligands to the larval odor receptor repertoire ( Asahina et al, 2009 ; Hoare et al, 2011 ).…”
Section: Introductionmentioning
confidence: 65%
“…Further, the larval odor receptor repertoire has been comprehensively tested in terms of electrophysiological responsiveness to odors in the “empty neuron” system ( Dobritsa et al, 2003 ; Kreher et al, 2008 ). Calcium imaging studies and direct recordings from larval olfactory sensory neurons have led to similar conclusions about the receptive ranges of odor receptors, supporting assignment of ligands to the larval odor receptor repertoire ( Asahina et al, 2009 ; Hoare et al, 2011 ).…”
Section: Introductionmentioning
confidence: 65%
“…The sequential perception of olfactory and gustatory cues is also necessary for adult discrimination of Drosophila sex pheromones [38][39][40]. We cannot currently explain why the simultaneous presentation of A-food patches of the two species dramatically reduced the general attractivity of food, particularly in D. simulans larvae.…”
Section: Discussionmentioning
confidence: 91%
“…We applied Bayesian classifiers to decode which stimulus class evoked a particular neural response. Naïve Bayes classifiers have frequently been used to quantify encoded information in neural spike trains (for reviews see Pouget et al, 2000 ; Quiroga and Panzeri, 2009 ), for instance in olfactory sensory neurons in Drosophila larvae (Hoare et al, 2011 ), in visual interneurons of the blowfly (Karmeier et al, 2005 ), or in motor cortical neurons of behaving monkeys (Rickert et al, 2009 ). Let P (s) denote the probability of presentation of stimulus class s and P ( x 1 , …, x n | s ) the conditional probability of observing spike train features x 1 , …, x n given s. The posterior probability that stimulus class s was presented given x 1 , …, x n is according to Bayes' theorem…”
Section: Methodsmentioning
confidence: 99%