competition-based model of pheromone component ratio detection in the moth竞争蛾信息素成分比检测模型.pdfVIP

Competition-Based Model of Pheromone Component Ratio Detection in the Moth 1 1 2 3 Andrei Zavada , Christopher L. Buckley , Dominique Martinez , Jean-Pierre Rospars , Thomas Nowotny1* ` 1 Informatics, University of Sussex, Brighton, United Kingdom, 2 CORTEX Team - LORIA, Vandoeuvre-les-Nancy, France, 3 UMR 1272 Physiologie de l’insecte, INRA, Versailles, France Abstract For some moth species, especially those closely interrelated and sympatric, recognizing a specific pheromone component concentration ratio is essential for males to successfully locate conspecific females. We propose and determine the properties of a minimalist competition-based feed-forward neuronal model capable of detecting a certain ratio of pheromone components independently of overall concentration. This model represents an elementary recognition unit for the ratio of binary mixtures which we propose is entirely contained in the macroglomerular complex (MGC) of the male moth. A set of such units, along with projection neurons (PNs), can provide the input to higher brain centres. We found that (1) accuracy is mainly achieved by maintaining a certain ratio of connection strengths between olfactory receptor neurons (ORN) and local neurons (LN), much less by properties of the interconnections between the competing LNs proper. An exception to this rule is that it is beneficial if connections between generalist LNs (i.e. excited by either pheromone component) and specialist LNs (i.e. excited by one component only) have the same strength as the reciprocal specialis