Single trial Bayesian inference by population vector readout in the barn owl's sound localization system.
Bayesian models have proven effective in characterizing perception, behavior, and neural encoding across diverse species and systems. The neural implementation of Bayesian inference in the barn owl's sound localization system and behavior has been previously explained by a non-uniform populatio...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2024-01-01
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| Series: | PLoS ONE |
| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0303843&type=printable |
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| _version_ | 1849467967137382400 |
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| author | Brian J Fischer Keanu Shadron Roland Ferger José L Peña |
| author_facet | Brian J Fischer Keanu Shadron Roland Ferger José L Peña |
| author_sort | Brian J Fischer |
| collection | DOAJ |
| description | Bayesian models have proven effective in characterizing perception, behavior, and neural encoding across diverse species and systems. The neural implementation of Bayesian inference in the barn owl's sound localization system and behavior has been previously explained by a non-uniform population code model. This model specifies the neural population activity pattern required for a population vector readout to match the optimal Bayesian estimate. While prior analyses focused on trial-averaged comparisons of model predictions with behavior and single-neuron responses, it remains unknown whether this model can accurately approximate Bayesian inference on single trials under varying sensory reliability, a fundamental condition for natural perception and behavior. In this study, we utilized mathematical analysis and simulations to demonstrate that decoding a non-uniform population code via a population vector readout approximates the Bayesian estimate on single trials for varying sensory reliabilities. Our findings provide additional support for the non-uniform population code model as a viable explanation for the barn owl's sound localization pathway and behavior. |
| format | Article |
| id | doaj-art-730dbfd3e5c44d52b06d09d12e33cdb1 |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-730dbfd3e5c44d52b06d09d12e33cdb12025-08-20T03:25:59ZengPublic Library of Science (PLoS)PLoS ONE1932-62032024-01-01195e030384310.1371/journal.pone.0303843Single trial Bayesian inference by population vector readout in the barn owl's sound localization system.Brian J FischerKeanu ShadronRoland FergerJosé L PeñaBayesian models have proven effective in characterizing perception, behavior, and neural encoding across diverse species and systems. The neural implementation of Bayesian inference in the barn owl's sound localization system and behavior has been previously explained by a non-uniform population code model. This model specifies the neural population activity pattern required for a population vector readout to match the optimal Bayesian estimate. While prior analyses focused on trial-averaged comparisons of model predictions with behavior and single-neuron responses, it remains unknown whether this model can accurately approximate Bayesian inference on single trials under varying sensory reliability, a fundamental condition for natural perception and behavior. In this study, we utilized mathematical analysis and simulations to demonstrate that decoding a non-uniform population code via a population vector readout approximates the Bayesian estimate on single trials for varying sensory reliabilities. Our findings provide additional support for the non-uniform population code model as a viable explanation for the barn owl's sound localization pathway and behavior.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0303843&type=printable |
| spellingShingle | Brian J Fischer Keanu Shadron Roland Ferger José L Peña Single trial Bayesian inference by population vector readout in the barn owl's sound localization system. PLoS ONE |
| title | Single trial Bayesian inference by population vector readout in the barn owl's sound localization system. |
| title_full | Single trial Bayesian inference by population vector readout in the barn owl's sound localization system. |
| title_fullStr | Single trial Bayesian inference by population vector readout in the barn owl's sound localization system. |
| title_full_unstemmed | Single trial Bayesian inference by population vector readout in the barn owl's sound localization system. |
| title_short | Single trial Bayesian inference by population vector readout in the barn owl's sound localization system. |
| title_sort | single trial bayesian inference by population vector readout in the barn owl s sound localization system |
| url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0303843&type=printable |
| work_keys_str_mv | AT brianjfischer singletrialbayesianinferencebypopulationvectorreadoutinthebarnowlssoundlocalizationsystem AT keanushadron singletrialbayesianinferencebypopulationvectorreadoutinthebarnowlssoundlocalizationsystem AT rolandferger singletrialbayesianinferencebypopulationvectorreadoutinthebarnowlssoundlocalizationsystem AT joselpena singletrialbayesianinferencebypopulationvectorreadoutinthebarnowlssoundlocalizationsystem |