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Influence of prior knowledge on eye movements to scenes as revealed by hidden Markov models
Human visual experience usually provides ample opportunity to accumulate knowledge about events unfolding in the environment. In typical scene perception experiments, however, participants view images that are unrelated to each other and, therefore, they cannot accumulate knowledge relevant to the u...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Association for Research in Vision and Ophthalmology
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10511023/ https://www.ncbi.nlm.nih.gov/pubmed/37721772 http://dx.doi.org/10.1167/jov.23.10.10 |
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author | Pedziwiatr, Marek A. Heer, Sophie Coutrot, Antoine Bex, Peter J. Mareschal, Isabelle |
author_facet | Pedziwiatr, Marek A. Heer, Sophie Coutrot, Antoine Bex, Peter J. Mareschal, Isabelle |
author_sort | Pedziwiatr, Marek A. |
collection | PubMed |
description | Human visual experience usually provides ample opportunity to accumulate knowledge about events unfolding in the environment. In typical scene perception experiments, however, participants view images that are unrelated to each other and, therefore, they cannot accumulate knowledge relevant to the upcoming visual input. Consequently, the influence of such knowledge on how this input is processed remains underexplored. Here, we investigated this influence in the context of gaze control. We used sequences of static film frames arranged in a way that allowed us to compare eye movements to identical frames between two groups: a group that accumulated prior knowledge relevant to the situations depicted in these frames and a group that did not. We used a machine learning approach based on hidden Markov models fitted to individual scanpaths to demonstrate that the gaze patterns from the two groups differed systematically and, thereby, showed that recently accumulated prior knowledge contributes to gaze control. Next, we leveraged the interpretability of hidden Markov models to characterize these differences. Additionally, we report two unexpected and interesting caveats of our approach. Overall, our results highlight the importance of recently acquired prior knowledge for oculomotor control and the potential of hidden Markov models as a tool for investigating it. |
format | Online Article Text |
id | pubmed-10511023 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The Association for Research in Vision and Ophthalmology |
record_format | MEDLINE/PubMed |
spelling | pubmed-105110232023-09-21 Influence of prior knowledge on eye movements to scenes as revealed by hidden Markov models Pedziwiatr, Marek A. Heer, Sophie Coutrot, Antoine Bex, Peter J. Mareschal, Isabelle J Vis Article Human visual experience usually provides ample opportunity to accumulate knowledge about events unfolding in the environment. In typical scene perception experiments, however, participants view images that are unrelated to each other and, therefore, they cannot accumulate knowledge relevant to the upcoming visual input. Consequently, the influence of such knowledge on how this input is processed remains underexplored. Here, we investigated this influence in the context of gaze control. We used sequences of static film frames arranged in a way that allowed us to compare eye movements to identical frames between two groups: a group that accumulated prior knowledge relevant to the situations depicted in these frames and a group that did not. We used a machine learning approach based on hidden Markov models fitted to individual scanpaths to demonstrate that the gaze patterns from the two groups differed systematically and, thereby, showed that recently accumulated prior knowledge contributes to gaze control. Next, we leveraged the interpretability of hidden Markov models to characterize these differences. Additionally, we report two unexpected and interesting caveats of our approach. Overall, our results highlight the importance of recently acquired prior knowledge for oculomotor control and the potential of hidden Markov models as a tool for investigating it. The Association for Research in Vision and Ophthalmology 2023-09-18 /pmc/articles/PMC10511023/ /pubmed/37721772 http://dx.doi.org/10.1167/jov.23.10.10 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 Pedziwiatr, Marek A. Heer, Sophie Coutrot, Antoine Bex, Peter J. Mareschal, Isabelle Influence of prior knowledge on eye movements to scenes as revealed by hidden Markov models |
title | Influence of prior knowledge on eye movements to scenes as revealed by hidden Markov models |
title_full | Influence of prior knowledge on eye movements to scenes as revealed by hidden Markov models |
title_fullStr | Influence of prior knowledge on eye movements to scenes as revealed by hidden Markov models |
title_full_unstemmed | Influence of prior knowledge on eye movements to scenes as revealed by hidden Markov models |
title_short | Influence of prior knowledge on eye movements to scenes as revealed by hidden Markov models |
title_sort | influence of prior knowledge on eye movements to scenes as revealed by hidden markov models |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10511023/ https://www.ncbi.nlm.nih.gov/pubmed/37721772 http://dx.doi.org/10.1167/jov.23.10.10 |
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