Literature DB >> 26888922

Cue Reliability Represented in the Shape of Tuning Curves in the Owl's Sound Localization System.

Fanny Cazettes1, Brian J Fischer2, Jose L Peña3.   

Abstract

Optimal use of sensory information requires that the brain estimates the reliability of sensory cues, but the neural correlate of cue reliability relevant for behavior is not well defined. Here, we addressed this issue by examining how the reliability of spatial cue influences neuronal responses and behavior in the owl's auditory system. We show that the firing rate and spatial selectivity changed with cue reliability due to the mechanisms generating the tuning to the sound localization cue. We found that the correlated variability among neurons strongly depended on the shape of the tuning curves. Finally, we demonstrated that the change in the neurons' selectivity was necessary and sufficient for a network of stochastic neurons to predict behavior when sensory cues were corrupted with noise. This study demonstrates that the shape of tuning curves can stand alone as a coding dimension of environmental statistics. SIGNIFICANCE STATEMENT: In natural environments, sensory cues are often corrupted by noise and are therefore unreliable. To make the best decisions, the brain must estimate the degree to which a cue can be trusted. The behaviorally relevant neural correlates of cue reliability are debated. In this study, we used the barn owl's sound localization system to address this question. We demonstrated that the mechanisms that account for spatial selectivity also explained how neural responses changed with degraded signals. This allowed for the neurons' selectivity to capture cue reliability, influencing the population readout commanding the owl's sound-orienting behavior.
Copyright © 2016 the authors 0270-6474/16/362101-10$15.00/0.

Entities:  

Keywords:  Bayesian; barn owl; neural coding; population vector; reliability; sound localization

Mesh:

Year:  2016        PMID: 26888922      PMCID: PMC4756150          DOI: 10.1523/JNEUROSCI.3753-15.2016

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  50 in total

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Authors:  A Moiseff
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Journal:  J Neurosci       Date:  1986-12       Impact factor: 6.167

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Authors:  A Moiseff; M Konishi
Journal:  J Neurosci       Date:  1983-12       Impact factor: 6.167

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Authors:  E I Knudsen
Journal:  J Neurosci       Date:  1982-09       Impact factor: 6.167

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Authors:  E I Knudsen; P F Knudsen
Journal:  J Comp Neurol       Date:  1983-08-01       Impact factor: 3.215

10.  Spatial properties of the population of mechanoreceptive units in the glabrous skin of the human hand.

Authors:  R S Johansson; A B Vallbo
Journal:  Brain Res       Date:  1980-02-24       Impact factor: 3.252

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  10 in total

1.  Synthesis of Hemispheric ITD Tuning from the Readout of a Neural Map: Commonalities of Proposed Coding Schemes in Birds and Mammals.

Authors:  Jose L Peña; Fanny Cazettes; Michael V Beckert; Brian J Fischer
Journal:  J Neurosci       Date:  2019-09-30       Impact factor: 6.167

2.  Barn Owl's Auditory Space Map Activity Matching Conditions for a Population Vector Readout to Drive Adaptive Sound-Localizing Behavior.

Authors:  Roland Ferger; Keanu Shadron; Brian J Fischer; José L Peña
Journal:  J Neurosci       Date:  2021-11-11       Impact factor: 6.709

3.  Effect of Stimulus-Dependent Spike Timing on Population Coding of Sound Location in the Owl's Auditory Midbrain.

Authors:  M V Beckert; B J Fischer; J L Pena
Journal:  eNeuro       Date:  2020-04-23

4.  Emergence of an Adaptive Command for Orienting Behavior in Premotor Brainstem Neurons of Barn Owls.

Authors:  Fanny Cazettes; Brian J Fischer; Michael V Beckert; Jose L Pena
Journal:  J Neurosci       Date:  2018-07-16       Impact factor: 6.167

5.  Optimal nonlinear cue integration for sound localization.

Authors:  Brian J Fischer; Jose Luis Peña
Journal:  J Comput Neurosci       Date:  2016-10-06       Impact factor: 1.621

6.  Development of a Bayesian Estimator for Audio-Visual Integration: A Neurocomputational Study.

Authors:  Mauro Ursino; Andrea Crisafulli; Giuseppe di Pellegrino; Elisa Magosso; Cristiano Cuppini
Journal:  Front Comput Neurosci       Date:  2017-10-04       Impact factor: 2.380

7.  The barn owls' Minimum Audible Angle.

Authors:  Bianca Krumm; Georg M Klump; Christine Köppl; Ulrike Langemann
Journal:  PLoS One       Date:  2019-08-23       Impact factor: 3.240

8.  Investigating the representation of uncertainty in neuronal circuits.

Authors:  Guillaume P Dehaene; Ruben Coen-Cagli; Alexandre Pouget
Journal:  PLoS Comput Biol       Date:  2021-02-12       Impact factor: 4.475

9.  Distinct Correlation Structure Supporting a Rate-Code for Sound Localization in the Owl's Auditory Forebrain.

Authors:  Michael V Beckert; Rodrigo Pavão; José L Peña
Journal:  eNeuro       Date:  2017-06-30

10.  Natural ITD statistics predict human auditory spatial perception.

Authors:  Rodrigo Pavão; Elyse S Sussman; Brian J Fischer; José L Peña
Journal:  Elife       Date:  2020-10-12       Impact factor: 8.140

  10 in total

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