Prior knowledge about events depicted in scenes decreases oculomotor exploration

Pedziwiatr, Marek A.; Heer, Sophie; Coutrot, Antoine; Bex, Peter J.; Mareschal, Isabelle

doi:10.1016/j.cognition.2023.105544

Cited by 1 publication

(9 citation statements)

References 55 publications

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“…To summarize, the two conditions differed mainly regarding the degree of horizontal spread of the eye movements around the clusters of key elements of the scenes (mainly, but not exclusively, human heads) that were usually aligned along the horizontal direction. This result dovetails with findings from our previous article ( Pedziwiatr, Heer et al, 2023 ), in which we showed that in the discontinuous condition, participants exhibited slightly more exploratory gaze behavior than in the continuous condition. Therefore, while our previous work revealed the nature and direction of the effects of prior knowledge on gaze behavior, here we gained insights into the relationship between these effects and specific image content.…”

Section: Resultssupporting

confidence: 92%

“…This information was likely crucial for the classification accuracy and, therefore, provided insights into the nature of the differences in gaze behavior between our conditions. Importantly, these insights are complementary to the insights gained in our previous article ( Pedziwiatr, Heer et al, 2023 ) because here, owing to the interpretability of the HMM coefficients, they would take the spatiotemporal properties of scanpaths and their relationship to the frames’ content into account.…”

Section: Resultsmentioning

confidence: 81%

“…All analyses reported here were conducted on data from a study described in our earlier article ( Pedziwiatr, Heer et al, 2023 ), and full details of how these data were collected can be found there. The preregistration of our study (outlining the HMMs analysis reported here), the data, and a script for downloading our stimuli are available at the following link: https://osf.io/et7mr/?view_only=6f86dc8211d845c7b2c09ef6f45baf64 .…”

Section: Methodsmentioning

confidence: 99%

“…Each participant viewed all 80 critical frames (one-half in each condition, counterbalanced between groups). We discarded 1.25% of that data based on prespecified criteria (see Pedziwiatr, Heer et al, 2023 for details). We presented an attention check question after each critical frame to keep the participants engaged.…”

Section: Methodsmentioning

confidence: 99%

“…To examine these differences, we recently created a unique stimulus set comprising 80 sequences of static frames from films directed by Alfred Hitchcock ( Pedziwiatr, Heer, Coutrot, Bex, & Mareschal, 2023 ). The sequences were arranged in such a way that participants viewed identical frames after acquiring knowledge that was either relevant to the content of these frames or not.…”

Section: Introductionmentioning

confidence: 99%

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Influence of prior knowledge on eye movements to scenes as revealed by hidden Markov models

Pedziwiatr,

Heer,

Coutrot

et al. 2023

Journal of Vision

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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.

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Section: Resultssupporting

confidence: 92%

Section: Resultsmentioning

confidence: 81%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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