SABER: Spatial Attention, Brain, Extended Reality
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arXiv
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| Autori principali: | , , , , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| author | Bullock, Tom Machniak, Emily Kim, You-Jin Kumaran, Radha Kasowski, Justin Varshney, Apurv Ram, Julia Hernandez, Melissa M. Johansson, Stina Dundon, Neil M. Höllerer, Tobias Giesbrecht, Barry |
| author_facet | Bullock, Tom Machniak, Emily Kim, You-Jin Kumaran, Radha Kasowski, Justin Varshney, Apurv Ram, Julia Hernandez, Melissa M. Johansson, Stina Dundon, Neil M. Höllerer, Tobias Giesbrecht, Barry |
| contents | Tracking moving objects is a critical skill for many everyday tasks, such as crossing a busy street, driving a car or catching a ball. Attention is a key cognitive function that supports object tracking; however, our understanding of the brain mechanisms that support attention is almost exclusively based on evidence from tasks that present stable objects at fixed locations. Accounts of multiple object tracking are also limited because they are largely based on behavioral data alone and involve tracking objects in a 2D plane. Consequently, the neural mechanisms that enable moment-by-moment tracking of goal-relevant objects remain poorly understood. To address this knowledge gap, we developed SABER (Spatial Attention, Brain, Extended Reality), a new framework for studying the behavioral and neural dynamics of attention to objects moving in 3D. Participants (n=32) completed variants of a task inspired by the popular virtual reality (VR) game, Beat Saber, where they used virtual sabers to strike stationary and moving color-defined target spheres while we recorded electroencephalography (EEG). We first established that standard univariate EEG metrics which are typically used to study spatial attention to static objects presented on 2D screens, can generalize effectively to an immersive VR context involving both static and dynamic 3D stimuli. We then used a computational modeling approach to reconstruct moment-by-moment attention to the locations of stationary and moving objects from oscillatory brain activity, demonstrating the feasibility of precisely tracking attention in a 3D space. These results validate SABER, and provide a foundation for future research that is critical not only for understanding how attention works in the physical world, but is also directly relevant to the development of better VR applications. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_24830 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | SABER: Spatial Attention, Brain, Extended Reality Bullock, Tom Machniak, Emily Kim, You-Jin Kumaran, Radha Kasowski, Justin Varshney, Apurv Ram, Julia Hernandez, Melissa M. Johansson, Stina Dundon, Neil M. Höllerer, Tobias Giesbrecht, Barry Human-Computer Interaction H.5.1; I.3.7; H.5.2 Tracking moving objects is a critical skill for many everyday tasks, such as crossing a busy street, driving a car or catching a ball. Attention is a key cognitive function that supports object tracking; however, our understanding of the brain mechanisms that support attention is almost exclusively based on evidence from tasks that present stable objects at fixed locations. Accounts of multiple object tracking are also limited because they are largely based on behavioral data alone and involve tracking objects in a 2D plane. Consequently, the neural mechanisms that enable moment-by-moment tracking of goal-relevant objects remain poorly understood. To address this knowledge gap, we developed SABER (Spatial Attention, Brain, Extended Reality), a new framework for studying the behavioral and neural dynamics of attention to objects moving in 3D. Participants (n=32) completed variants of a task inspired by the popular virtual reality (VR) game, Beat Saber, where they used virtual sabers to strike stationary and moving color-defined target spheres while we recorded electroencephalography (EEG). We first established that standard univariate EEG metrics which are typically used to study spatial attention to static objects presented on 2D screens, can generalize effectively to an immersive VR context involving both static and dynamic 3D stimuli. We then used a computational modeling approach to reconstruct moment-by-moment attention to the locations of stationary and moving objects from oscillatory brain activity, demonstrating the feasibility of precisely tracking attention in a 3D space. These results validate SABER, and provide a foundation for future research that is critical not only for understanding how attention works in the physical world, but is also directly relevant to the development of better VR applications. |
| title | SABER: Spatial Attention, Brain, Extended Reality |
| topic | Human-Computer Interaction H.5.1; I.3.7; H.5.2 |
| url | https://arxiv.org/abs/2603.24830 |