Literature DB >> 33362477

The Olfactory Bulb Facilitates Use of Category Bounds for Classification of Odorants in Different Intensity Groups.

Justin Losacco1,2, Nicholas M George1,2, Naoki Hiratani3, Diego Restrepo1,2.   

Abstract

Signal processing of odor inputs to the olfactory bulb (OB) changes through top-down modulation whose shaping of neural rhythms in response to changes in stimulus intensity is not understood. Here we asked whether the representation of a high vs. low intensity odorant in the OB by oscillatory neural activity changed as the animal learned to discriminate odorant concentration ranges in a go-no go task. We trained mice to discriminate between high vs. low concentration odorants by learning to lick to the rewarded group (low or high). We recorded the local field potential (LFP) in the OB of these mice and calculated the theta-referenced beta or gamma oscillation power (theta phase-referenced power, or tPRP). We found that as the mouse learned to differentiate odorant concentrations, tPRP diverged between trials for the rewarded vs. the unrewarded concentration range. For the proficient animal, linear discriminant analysis was able to predict the rewarded odorant group and the performance of this classifier correlated with the percent correct behavior in the odor concentration discrimination task. Interestingly, the behavioral response and decoding accuracy were asymmetric as a function of concentration when the rewarded stimulus was shifted between the high and low odorant concentration ranges. A model for decision making motivated by the statistics of OB activity that uses a single threshold in a logarithmic concentration scale displays this asymmetry. Taken together with previous studies on the intensity criteria for decisions on odorant concentrations, our finding suggests that OB oscillatory events facilitate decision making to classify concentrations using a single intensity criterion.
Copyright © 2020 Losacco, George, Hiratani and Restrepo.

Entities:  

Keywords:  decoding; go-no go; learning; odorant concentration; oscillations

Year:  2020        PMID: 33362477      PMCID: PMC7759615          DOI: 10.3389/fncel.2020.613635

Source DB:  PubMed          Journal:  Front Cell Neurosci        ISSN: 1662-5102            Impact factor:   5.505


  44 in total

1.  Dynamic ensemble odor coding in the mammalian olfactory bulb: sensory information at different timescales.

Authors:  Brice Bathellier; Derek L Buhl; Riccardo Accolla; Alan Carleton
Journal:  Neuron       Date:  2008-02-28       Impact factor: 17.173

2.  Recurrent cortical circuits implement concentration-invariant odor coding.

Authors:  Kevin A Bolding; Kevin M Franks
Journal:  Science       Date:  2018-09-14       Impact factor: 47.728

3.  Olfactory bulb output cell temporal response patterns to increasing odor concentrations in freely breathing rats.

Authors:  M Chalansonnet; M A Chaput
Journal:  Chem Senses       Date:  1998-02       Impact factor: 3.160

4.  Coding odorant concentration through activation timing between the medial and lateral olfactory bulb.

Authors:  Zhishang Zhou; Leonardo Belluscio
Journal:  Cell Rep       Date:  2012-11-15       Impact factor: 9.423

5.  Attention alters orientation processing in the human lateral geniculate nucleus.

Authors:  Sam Ling; Michael S Pratte; Frank Tong
Journal:  Nat Neurosci       Date:  2015-03-02       Impact factor: 24.884

6.  Odor Concentration Change Coding in the Olfactory Bulb.

Authors:  Ana Parabucki; Alexander Bizer; Genela Morris; Antonio E Munoz; Avinash D S Bala; Matthew Smear; Roman Shusterman
Journal:  eNeuro       Date:  2019-02-27

7.  Profound context-dependent plasticity of mitral cell responses in olfactory bulb.

Authors:  Wilder Doucette; Diego Restrepo
Journal:  PLoS Biol       Date:  2008-10-28       Impact factor: 8.029

8.  Enhancement of encoding and retrieval functions through theta phase-specific manipulation of hippocampus.

Authors:  Joshua H Siegle; Matthew A Wilson
Journal:  Elife       Date:  2014-07-29       Impact factor: 8.140

9.  Neural Coding of Perceived Odor Intensity.

Authors:  Yevgeniy B Sirotin; Roman Shusterman; Dmitry Rinberg
Journal:  eNeuro       Date:  2015-12-03

Review 10.  Action and learning shape the activity of neuronal circuits in the visual cortex.

Authors:  Janelle Mp Pakan; Valerio Francioni; Nathalie L Rochefort
Journal:  Curr Opin Neurobiol       Date:  2018-05-01       Impact factor: 6.627

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