Learning modifies odor mixture processing to improve detection of relevant components

Jen Yung Chen, Emiliano Marachlian, Collins Assisi, Ramon Huerta, Brian Smith, Fernando Locatelli, Maxim Bazhenov

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

Honey bees have arich repertoireofolfactory learning behaviors, and they therefore arean excellent modelto study plasticity in olfactory circuits. Recent behavioral, physiological, and molecular evidence suggested that the antennal lobe, the first relay of the olfactory system in insects and analog to the olfactory bulb in vertebrates, is involved in associative and nonassociative olfactory learning. Here we use calcium imaging to reveal how responses across antennal lobe projection neurons change after association of an input odor with appetitive reinforcement. After appetitive conditioning to 1-hexanol, the representation of an odor mixture containing 1-hexanol becomes more similar to this odor and less similar to the background odor acetophenone. We then apply computational modeling to investigate how changes in synaptic connectivity can account for the observed plasticity. Our study suggests that experience-dependent modulationofinhibitory interactionsintheantennallobe aids perceptionofsalientodorcomponentsmixed withbehaviorally irrelevant background odors.

Original languageEnglish (US)
Pages (from-to)179-197
Number of pages19
JournalJournal of Neuroscience
Volume35
Issue number1
DOIs
StatePublished - Jan 7 2015

Fingerprint

Learning
Honey
Olfactory Bulb
Bees
Insects
Vertebrates
Odorants
Calcium
Neurons
1-hexanol

Keywords

  • Antennal lobe
  • Honey bees
  • Olfaction
  • Olfactory learning

ASJC Scopus subject areas

  • Neuroscience(all)

Cite this

Chen, J. Y., Marachlian, E., Assisi, C., Huerta, R., Smith, B., Locatelli, F., & Bazhenov, M. (2015). Learning modifies odor mixture processing to improve detection of relevant components. Journal of Neuroscience, 35(1), 179-197. https://doi.org/10.1523/JNEUROSCI.2345-14.2015

Learning modifies odor mixture processing to improve detection of relevant components. / Chen, Jen Yung; Marachlian, Emiliano; Assisi, Collins; Huerta, Ramon; Smith, Brian; Locatelli, Fernando; Bazhenov, Maxim.

In: Journal of Neuroscience, Vol. 35, No. 1, 07.01.2015, p. 179-197.

Research output: Contribution to journalArticle

Chen, JY, Marachlian, E, Assisi, C, Huerta, R, Smith, B, Locatelli, F & Bazhenov, M 2015, 'Learning modifies odor mixture processing to improve detection of relevant components', Journal of Neuroscience, vol. 35, no. 1, pp. 179-197. https://doi.org/10.1523/JNEUROSCI.2345-14.2015
Chen, Jen Yung ; Marachlian, Emiliano ; Assisi, Collins ; Huerta, Ramon ; Smith, Brian ; Locatelli, Fernando ; Bazhenov, Maxim. / Learning modifies odor mixture processing to improve detection of relevant components. In: Journal of Neuroscience. 2015 ; Vol. 35, No. 1. pp. 179-197.
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