Learning modifies odor mixture processing to improve detection of relevant components

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...

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Autores principales:	Chen, J.-Y., Marachlian, E., Assisi, C., Huerta, R., Smith, B.H., Locatelli, F., Bazhenov, M.
Formato:	JOUR
Materias:	Antennal lobe Honey bees Olfaction Olfactory learning acetophenone hexanol animal experiment Article connectome geometry image analysis imaging learning nerve cell plasticity nerve stimulation nonhuman odor olfactory bulb principal component analysis spatiotemporal analysis animal bee conditioning female nerve cell network olfactory system physiology Animals Bees Conditioning (Psychology) Female Learning Nerve Net Odors Olfactory Pathways Smell
Acceso en línea:	http://hdl.handle.net/20.500.12110/paper_02706474_v35_n1_p179_Chen
Aporte de:	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

id	todo:paper_02706474_v35_n1_p179_Chen
record_format	dspace
spelling	todo:paper_02706474_v35_n1_p179_Chen2023-10-03T15:14:46Z Learning modifies odor mixture processing to improve detection of relevant components Chen, J.-Y. Marachlian, E. Assisi, C. Huerta, R. Smith, B.H. Locatelli, F. Bazhenov, M. Antennal lobe Honey bees Olfaction Olfactory learning acetophenone hexanol animal experiment Article connectome geometry image analysis imaging learning nerve cell plasticity nerve stimulation nonhuman odor olfactory bulb principal component analysis spatiotemporal analysis animal bee conditioning female learning nerve cell network odor olfactory system physiology Animals Bees Conditioning (Psychology) Female Learning Nerve Net Odors Olfactory Pathways Smell 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. © 2015 the authors. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_02706474_v35_n1_p179_Chen
institution	Universidad de Buenos Aires
institution_str	I-28
repository_str	R-134
collection	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic	Antennal lobe Honey bees Olfaction Olfactory learning acetophenone hexanol animal experiment Article connectome geometry image analysis imaging learning nerve cell plasticity nerve stimulation nonhuman odor olfactory bulb principal component analysis spatiotemporal analysis animal bee conditioning female learning nerve cell network odor olfactory system physiology Animals Bees Conditioning (Psychology) Female Learning Nerve Net Odors Olfactory Pathways Smell
spellingShingle	Antennal lobe Honey bees Olfaction Olfactory learning acetophenone hexanol animal experiment Article connectome geometry image analysis imaging learning nerve cell plasticity nerve stimulation nonhuman odor olfactory bulb principal component analysis spatiotemporal analysis animal bee conditioning female learning nerve cell network odor olfactory system physiology Animals Bees Conditioning (Psychology) Female Learning Nerve Net Odors Olfactory Pathways Smell Chen, J.-Y. Marachlian, E. Assisi, C. Huerta, R. Smith, B.H. Locatelli, F. Bazhenov, M. Learning modifies odor mixture processing to improve detection of relevant components
topic_facet	Antennal lobe Honey bees Olfaction Olfactory learning acetophenone hexanol animal experiment Article connectome geometry image analysis imaging learning nerve cell plasticity nerve stimulation nonhuman odor olfactory bulb principal component analysis spatiotemporal analysis animal bee conditioning female learning nerve cell network odor olfactory system physiology Animals Bees Conditioning (Psychology) Female Learning Nerve Net Odors Olfactory Pathways Smell
description	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. © 2015 the authors.
format	JOUR
author	Chen, J.-Y. Marachlian, E. Assisi, C. Huerta, R. Smith, B.H. Locatelli, F. Bazhenov, M.
author_facet	Chen, J.-Y. Marachlian, E. Assisi, C. Huerta, R. Smith, B.H. Locatelli, F. Bazhenov, M.
author_sort	Chen, J.-Y.
title	Learning modifies odor mixture processing to improve detection of relevant components
title_short	Learning modifies odor mixture processing to improve detection of relevant components
title_full	Learning modifies odor mixture processing to improve detection of relevant components
title_fullStr	Learning modifies odor mixture processing to improve detection of relevant components
title_full_unstemmed	Learning modifies odor mixture processing to improve detection of relevant components
title_sort	learning modifies odor mixture processing to improve detection of relevant components
url	http://hdl.handle.net/20.500.12110/paper_02706474_v35_n1_p179_Chen
work_keys_str_mv	AT chenjy learningmodifiesodormixtureprocessingtoimprovedetectionofrelevantcomponents AT marachliane learningmodifiesodormixtureprocessingtoimprovedetectionofrelevantcomponents AT assisic learningmodifiesodormixtureprocessingtoimprovedetectionofrelevantcomponents AT huertar learningmodifiesodormixtureprocessingtoimprovedetectionofrelevantcomponents AT smithbh learningmodifiesodormixtureprocessingtoimprovedetectionofrelevantcomponents AT locatellif learningmodifiesodormixtureprocessingtoimprovedetectionofrelevantcomponents AT bazhenovm learningmodifiesodormixtureprocessingtoimprovedetectionofrelevantcomponents
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Learning modifies odor mixture processing to improve detection of relevant components

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