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Perceiving depth from texture and disparity cues: Evidence for a non-probabilistic account of cue integration

Bayesian inference theories have been extensively used to model how the brain derives three-dimensional (3D) information from ambiguous visual input. In particular, the maximum likelihood estimation (MLE) model combines estimates from multiple depth cues according to their relative reliability to pr...

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Autores principales: Kemp, Jovan T., Cesanek, Evan, Domini, Fulvio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Association for Research in Vision and Ophthalmology 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10382782/
https://www.ncbi.nlm.nih.gov/pubmed/37486299
http://dx.doi.org/10.1167/jov.23.7.13
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author Kemp, Jovan T.
Cesanek, Evan
Domini, Fulvio
author_facet Kemp, Jovan T.
Cesanek, Evan
Domini, Fulvio
author_sort Kemp, Jovan T.
collection PubMed
description Bayesian inference theories have been extensively used to model how the brain derives three-dimensional (3D) information from ambiguous visual input. In particular, the maximum likelihood estimation (MLE) model combines estimates from multiple depth cues according to their relative reliability to produce the most probable 3D interpretation. Here, we tested an alternative theory of cue integration, termed the intrinsic constraint (IC) theory, which postulates that the visual system derives the most stable, not most probable, interpretation of the visual input amid variations in viewing conditions. The vector sum model provides a normative approach for achieving this goal where individual cue estimates are components of a multidimensional vector whose norm determines the combined estimate. Individual cue estimates are not accurate but related to distal 3D properties through a deterministic mapping. In three experiments, we show that the IC theory can more adeptly account for 3D cue integration than MLE models. In Experiment 1, we show systematic biases in the perception of depth from texture and depth from binocular disparity. Critically, we demonstrate that the vector sum model predicts an increase in perceived depth when these cues are combined. In Experiment 2, we illustrate the IC theory radical reinterpretation of the just noticeable difference (JND) and test the related vector sum model prediction of the classic finding of smaller JNDs for combined-cue versus single-cue stimuli. In Experiment 3, we confirm the vector sum prediction that biases found in cue integration experiments cannot be attributed to flatness cues, as the MLE model predicts.
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spelling pubmed-103827822023-07-30 Perceiving depth from texture and disparity cues: Evidence for a non-probabilistic account of cue integration Kemp, Jovan T. Cesanek, Evan Domini, Fulvio J Vis Article Bayesian inference theories have been extensively used to model how the brain derives three-dimensional (3D) information from ambiguous visual input. In particular, the maximum likelihood estimation (MLE) model combines estimates from multiple depth cues according to their relative reliability to produce the most probable 3D interpretation. Here, we tested an alternative theory of cue integration, termed the intrinsic constraint (IC) theory, which postulates that the visual system derives the most stable, not most probable, interpretation of the visual input amid variations in viewing conditions. The vector sum model provides a normative approach for achieving this goal where individual cue estimates are components of a multidimensional vector whose norm determines the combined estimate. Individual cue estimates are not accurate but related to distal 3D properties through a deterministic mapping. In three experiments, we show that the IC theory can more adeptly account for 3D cue integration than MLE models. In Experiment 1, we show systematic biases in the perception of depth from texture and depth from binocular disparity. Critically, we demonstrate that the vector sum model predicts an increase in perceived depth when these cues are combined. In Experiment 2, we illustrate the IC theory radical reinterpretation of the just noticeable difference (JND) and test the related vector sum model prediction of the classic finding of smaller JNDs for combined-cue versus single-cue stimuli. In Experiment 3, we confirm the vector sum prediction that biases found in cue integration experiments cannot be attributed to flatness cues, as the MLE model predicts. The Association for Research in Vision and Ophthalmology 2023-07-24 /pmc/articles/PMC10382782/ /pubmed/37486299 http://dx.doi.org/10.1167/jov.23.7.13 Text en Copyright 2023 The Authors https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License.
spellingShingle Article
Kemp, Jovan T.
Cesanek, Evan
Domini, Fulvio
Perceiving depth from texture and disparity cues: Evidence for a non-probabilistic account of cue integration
title Perceiving depth from texture and disparity cues: Evidence for a non-probabilistic account of cue integration
title_full Perceiving depth from texture and disparity cues: Evidence for a non-probabilistic account of cue integration
title_fullStr Perceiving depth from texture and disparity cues: Evidence for a non-probabilistic account of cue integration
title_full_unstemmed Perceiving depth from texture and disparity cues: Evidence for a non-probabilistic account of cue integration
title_short Perceiving depth from texture and disparity cues: Evidence for a non-probabilistic account of cue integration
title_sort perceiving depth from texture and disparity cues: evidence for a non-probabilistic account of cue integration
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10382782/
https://www.ncbi.nlm.nih.gov/pubmed/37486299
http://dx.doi.org/10.1167/jov.23.7.13
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