Our Research
Our Research
Embedded Files
Our research focuses on the cognitive and neural mechanisms underlying visual attention. I study how human observers learn to control their limited attentional processing to focus on task-relevant stimuli while ignoring distracting information. More specifically, we are interested in how observers learn to suppress distracting information through experience (e.g., learned distractor suppression) both when the distracting information is and is not perceptually salient. Our research has important implications for theories of visual attention.
Our research focuses on the cognitive and neural mechanisms underlying visual attention. I study how human observers learn to control their limited attentional processing to focus on task-relevant stimuli while ignoring distracting information. More specifically, we are interested in how observers learn to suppress distracting information through experience (e.g., learned distractor suppression) both when the distracting information is and is not perceptually salient. Our research has important implications for theories of visual attention.
Behavioral metrics
Behavioral metrics
Eye-tracking
Eye-tracking
EEG recording
EEG recording
Learning to ignore non-salient distractors
Learning to ignore non-salient distractors
Imagine searching through a refrigerator for some blueberries. In a cluttered refrigerator, there are many items competing for one's attention. The blueberries do not inherently stand out from the rest of the items. To locate the blueberries, a reasonable observer could restrict their search to only look for blue items (i.e., form a positive attentional template or set for blue). However, blueberries are never red. This consistent statistical regularity can be learned through experience helping an observer to avoid red items. Combining the two sources of information (i.e., searching for blue while ignoring red) one would eventually locate the blueberries faster than either searching for blue or ignoring red alone. This simple visual search highlights one fundamental aspect of my research: Learned distractor suppression. In this line of research I've shown that these distractor-related statistical regularities serve to complement knowledge concerning relevant items, biasing attention away from consistent distractors.
Imagine searching through a refrigerator for some blueberries. In a cluttered refrigerator, there are many items competing for one's attention. The blueberries do not inherently stand out from the rest of the items. To locate the blueberries, a reasonable observer could restrict their search to only look for blue items (i.e., form a positive attentional template or set for blue). However, blueberries are never red. This consistent statistical regularity can be learned through experience helping an observer to avoid red items. Combining the two sources of information (i.e., searching for blue while ignoring red) one would eventually locate the blueberries faster than either searching for blue or ignoring red alone. This simple visual search highlights one fundamental aspect of my research: Learned distractor suppression. In this line of research I've shown that these distractor-related statistical regularities serve to complement knowledge concerning relevant items, biasing attention away from consistent distractors.
Ignoring salient distractors
Ignoring salient distractors
Humans often use brightly colored and/or abruptly flashing stimuli to signal important information. For example, the dashboard of a car contains many indicator and warning lights with different colors, brightnesses, which may flash at different rates. These indicators are designed to maximize their ability to automatically grab or "capture" the driver's attention to signal potential dangers on the road or mechanical issues with the car. To safely navigate the road, the driver must attend to these warning signs when relevant (e.g., signaling a potential collision) while ignoring other salient sources of distraction such as one's cellphone. The ability for salient stimuli to automatically capture one's attention has been hotly contested for decades. I have helped to resolve this debate by supporting a recent hybrid model of attentional capture: the signal suppression hypothesis. Specifically, I have demonstrated that highly salient distractors (e.g., one red item among many green items) do not automatically capture attention, but instead, can be actively suppressed preventing their capture when these stimuli are irrelevant to one's current goals.
Humans often use brightly colored and/or abruptly flashing stimuli to signal important information. For example, the dashboard of a car contains many indicator and warning lights with different colors, brightnesses, which may flash at different rates. These indicators are designed to maximize their ability to automatically grab or "capture" the driver's attention to signal potential dangers on the road or mechanical issues with the car. To safely navigate the road, the driver must attend to these warning signs when relevant (e.g., signaling a potential collision) while ignoring other salient sources of distraction such as one's cellphone. The ability for salient stimuli to automatically capture one's attention has been hotly contested for decades. I have helped to resolve this debate by supporting a recent hybrid model of attentional capture: the signal suppression hypothesis. Specifically, I have demonstrated that highly salient distractors (e.g., one red item among many green items) do not automatically capture attention, but instead, can be actively suppressed preventing their capture when these stimuli are irrelevant to one's current goals.
Publications
Publications
2026
Stilwell, B.T., & Anderson, B.A. (2026). Signal suppression makes search less effortful. Cognitive, Affective, & Behavioral Neuroscience. 26(2), 484-504 https://doi.org/10.3758/s13415-025-01345-6.[PDF]
2024
Stilwell, B.T., Egeth, H.E., & Gaspelin, N. (2024). Evidence Against the Low-Salience Account of Attentional Suppression. Journal of Experimental Psychology: Human Performance and Perception. 50(10), 1033–1047. https://doi.org/10.1037/xhp0001234. [PDF]
2023
Stilwell, B.T., Adams, O.J., Egeth, H.E., & Gaspelin, N. (2023). The role of salience in the suppression of distracting stimuli. Psychonomic Bulletin & Review. 30(6), 2262–2271. https://doi.org/10.3758/s13423-023-02302-5 https://doi.org/10.3758/s13423-023-02302-5. [PDF]
Gaspelin, N., Lamy, D., Egeth, H.E., Liesefeld, H.R., Kerzel, D., Mandal, A., Müller, M.M., Schall, J.D., Schubö, A., Slagter, H.A., Stilwell, B.T., van Moorselaar., D. (2023). The Distractor Positivity Component and the Inhibition of Distracting Stimuli. Journal of Cognitive Neuroscience, 35(11), 1693–1715. https://doi.org/10.1162/jocn_a_02051. [PDF]
Rigsby, T.J., Stilwell, B.T., Ruthruff, E., & Gaspelin, N. (2023). A new technique for estimating the probability of attentional capture. Attention, Perception, & Psychophysics. 85, 543–559. https://doi.org/10.3758/s13414-022-02639-4. [PDF]
Stilwell, B.T. & Vecera, S.P. (2023). Learned distractor rejection persists across target search in a different dimension. Attention, Perception, & Psychophysics. 85 (3), 785–795. https://doi.org/10.3758/s13414-022-02559-3. [PDF]
2022
Stilwell, B. T., Egeth, H. E., & Gaspelin, N. (2022). Electrophysiological evidence for the suppression of highly salient distractors. Journal of Cognitive Neuroscience, 34(5), 787–805. https://doi.org/10.1162/jocn_a_01827. [PDF]
Stilwell, B. T., & Vecera, S. P. (2022). Testing the underlying processes leading to learned distractor rejection: Learned oculomotor avoidance. Attention, Perception, & Psychophysics, 84(6), 1964–1981. https://doi.org/10.3758/s13414-022-02483-6. [PDF]
2021
Stilwell, B. T., & Gaspelin, N. (2021). Attentional suppression of highly salient color singletons. Journal of Experimental Psychology: Human Perception and Performance, 47(10), 1313–1328. https://doi.org/10.1037/xhp0000948. [PDF]
2020
Stilwell, B. T., & Vecera, S. P. (2020). Learned distractor rejection in the face of strong target guidance. Journal of Experimental Psychology. Human Perception and Performance, 46(9), 926–941. https://doi.org/10.1037/xhp0000757. [PDF]
2019
Stilwell, B. T., Bahle, B., & Vecera, S. P. (2019). Feature-based statistical regularities of distractors modulate attentional capture. Journal of Experimental Psychology: Human Perception and Performance, 45(3), 419–433. https://doi.org/10.1037/xhp0000613. [PDF]
Stilwell, B. T., & Vecera, S. P. (2019). Learned and cued distractor rejection for multiple features in visual search. Attention, Perception, & Psychophysics, 81(2), 359–376. https://doi.org/10.3758/s13414-018-1622-8. [PDF]
Stilwell, B. T., & Vecera, S. P. (2019). Cued distractor rejection disrupts learned distractor rejection. Visual Cognition, 27(3–4), 327–342. https://doi.org/10.1080/13506285.2018.1564808. [PDF]
Page updated
Google Sites
Report abuse