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Conceptual priorities shape individual gaze patterns during naturalistic visual attention.

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Title: Conceptual priorities shape individual gaze patterns during naturalistic visual attention.
Authors: Haskins, Amanda J.1,2 ajhaskins@ucsd.edu, Packard, Katherine O.1, Robertson, Caroline E.1 cerw@dartmouth.edu
Source: Proceedings of the National Academy of Sciences of the United States of America. 6/16/2026, Vol. 123 Issue 24, p1-11. 11p.
Subjects: Gaze, Concept learning, Virtual reality, Attention control, Selectivity (Psychology), Language models, Individual differences
Abstract: Our visual landscape consists of not only people, places, and objects (e.g., "soldier," "stadium," "flag") but also the conceptual relationships that unite them (e.g., "patriotism"). Because conceptual knowledge varies across individuals, this level of structure may support individualized patterns of attentional selection during naturalistic scene viewing. Here, we ask whether individuals’ gaze patterns reflect, in part, latent attentional priorities organized in conceptual space. Participants (N = 61) freely explored a diverse set of immersive real-world scenes (N = 100) in head-mounted VR while their gaze position was continuously recorded. We modeled gaze behavior using spatial, visual, and conceptual feature spaces, leveraging embeddings from large vision and language models, to uncover the latent priorities guiding individuals’ unique patterns of selective attention across environments. Individuals exhibited stable and idiosyncratic gaze patterns across scenes and test–retest sessions, consistent with trait-like individual differences in attention. Spatial, visual, and conceptual feature spaces each explained unique variance in individual gaze patterns, with conceptual features contributing variance beyond that explained by spatial and visual features alone. Notably, language-model–based predictions were particularly effective at capturing these individualized patterns. Together, these findings indicate that naturalistic visual attention is structured at multiple levels—including a conceptual level—revealing stable individual differences in how people sample and prioritize information across complex visual environments. [ABSTRACT FROM AUTHOR]
Copyright of Proceedings of the National Academy of Sciences of the United States of America is the property of National Academy of Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: Conceptual priorities shape individual gaze patterns during naturalistic visual attention.
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  Data: Our visual landscape consists of not only people, places, and objects (e.g., "soldier," "stadium," "flag") but also the conceptual relationships that unite them (e.g., "patriotism"). Because conceptual knowledge varies across individuals, this level of structure may support individualized patterns of attentional selection during naturalistic scene viewing. Here, we ask whether individuals’ gaze patterns reflect, in part, latent attentional priorities organized in conceptual space. Participants (N = 61) freely explored a diverse set of immersive real-world scenes (N = 100) in head-mounted VR while their gaze position was continuously recorded. We modeled gaze behavior using spatial, visual, and conceptual feature spaces, leveraging embeddings from large vision and language models, to uncover the latent priorities guiding individuals’ unique patterns of selective attention across environments. Individuals exhibited stable and idiosyncratic gaze patterns across scenes and test–retest sessions, consistent with trait-like individual differences in attention. Spatial, visual, and conceptual feature spaces each explained unique variance in individual gaze patterns, with conceptual features contributing variance beyond that explained by spatial and visual features alone. Notably, language-model–based predictions were particularly effective at capturing these individualized patterns. Together, these findings indicate that naturalistic visual attention is structured at multiple levels—including a conceptual level—revealing stable individual differences in how people sample and prioritize information across complex visual environments. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Proceedings of the National Academy of Sciences of the United States of America is the property of National Academy of Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=194721594
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              Text: 6/16/2026
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