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09:00 - 10:30
Parallel sessions 4
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09:00 - 10:30
Room: C-Building - N14
Chair/s:
Kathrin Finke, Ingrid Scharlau, Jan Tünnermann
The Theory of Visual Attention (TVA) continues to be developed as a powerful quantitative framework for understanding attentional selection and capacity. Current research applies TVA across diverse contexts and methodologies. This symposium presents new theoretical developments, methodological advances, and applied perspectives that extend TVA’s reach and precision and sometimes challenge its present state. Estela Carmona investigates how self-relevant information shapes attentional parameters, offering insights into the role of personal significance in visual selection. Anders Petersen follows by introducing advances in modeling enumeration data within the TVA framework, extending the set of tasks that can be used with TVA. Kai Biermeier, Ngoc Chi Banh, and Ingrid Scharlau test the applicability of TVA to online scenarios and identify methodological challenges in the online estimation of attentional processing speed. Tobias Peters, Kai Biermeier, and Ingrid Scharlau apply TVA measures of attention to human–AI interaction, examining whether attentional signatures can indicate adaptive distrust. Finally, Jan Tünnermann and Ingrid Scharlau revisit lateral asymmetries in visual processing, presenting updated findings on left–right visual field differences within TVA. Together, these contributions demonstrate the continuing vitality of TVA research and its capacity to inform theoretical, methodological, and applied perspectives on visual attention but also challenges that have to be addressed. Part 2 of the symposium will turn to attentional changes in diverse populations. 
Submission 464
Challenges in the Online Estimation of Attentional Processing Speed
SymposiumTalk-03
Presented by: Kai Biermeier
Kai Biermeier, Ngoc Chi Banh, Ingrid Scharlau
Paderborn University, Germany
Visual attention is one of the oldest topics in psychological research, yet its mechanisms remain only partly understood. Especially the temporal progression remains a challenging topic. This is largely due to the short-livedness of attention shifts, which makes it hard to gather enough data points in a given time.

Eye-tracking is a very quick and well-established method to assess overt attention. Nevertheless, it is not capable of measuring covert visual attention. Further, there is no comparable method to capture covert visual attention and, more specifically, total processing speed over time. This is not surprising because the measurement of total processing speed requires not only additional data per time unit but also fast inference methods, as it cannot be directly observed but only inferred.

In this talk, we introduce a framework grounded in Bundesen’s Theory of Visual Attention (TVA) that enables the temporal analysis of covert attention. We evaluated this framework through simulation studies. First, the strengths and limitations of various estimation methods in this context are outlined. Further, the feasibility of quick and frequent estimation under specific assumptions — namely, limited deviation of processing speed from the previous to the next time point, reduced processing speed due to a secondary task, and a sufficiently well-estimated initial processing speed is demonstrated. Finally, we outline an experiment for future empirical evaluation of online estimation based on our proposed framework.