Learning About Natural Variation of Odor Mixtures Enhances Categorization In Early Olfactory Processing

FERNANDO LOCATELLI; FERNANDEZ PATRICIA; SMITH BRIAN

JOURNAL OF EXPERIMENTAL BIOLOGY

COMPANY OF BIOLOGISTS LTD

Lugar: Cambridge; Año: 2016

0022-0949

Learning About Natural Variation ofOdor Mixtures Enhances Categorization In Early Olfactory Processing Fernando F. Locatelli1#, PatriciaC. Fernandez2#, Brian H. Smith*Natural odors are typically mixtures ofseveral chemical components. Mixtures vary in composition among odor objects thathave the same meaning. Therefore a central ?categorization? problem for ananimal as it makes decisions about odors in natural contexts is to correctly identifyodor variants that have the same meaning and avoid variants that have adifferent meaning. We propose that identified mechanisms of associative andnonassociative plasticity in early sensory processing in the insect antennallobe and mammalian olfactory bulb are central to solving this problem.Accordingly, this plasticity should work to improve categorization of odorsthat have the opposite meanings in relation to important events. Usingsynthetic mixtures designed to mimic natural odor variation among flowers, westudied how honey bees learn about and generalize among floral odors associatedwith food. We behaviorally conditioned honey bees on a difficult odordiscrimination problem using synthetic mixtures that mimic natural variationamong snapdragon flowers. We then employed calcium imaging to measure responsesof projection neurons of the antennal lobe, which is the first synaptic relayof olfactory sensory information in the brain, to study how ensembles ofprojections neurons change as a result of behavioral conditioning. We show howthese ensembles become ?tuned? through plasticity to improve categorization ofodors that have the different meanings. We argue that this tuning allows moreefficient use of the immense coding space of the antennal lobe and olfactorybulb to solve the categorization problem. Our data point to the need to abetter understanding of the ?statistics? of the odor space.