Trafton Drew - US grants
Affiliations: | University of Oregon, Eugene, OR, United States |
Area:
Visual attentionWebsite:
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The funding information displayed below comes from the NIH Research Portfolio Online Reporting Tools and the NSF Award Database.The grant data on this page is limited to grants awarded in the United States and is thus partial. It can nonetheless be used to understand how funding patterns influence mentorship networks and vice-versa, which has deep implications on how research is done.
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High-probability grants
According to our matching algorithm, Trafton Drew is the likely recipient of the following grants.Years | Recipients | Code | Title / Keywords | Matching score |
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2021 | Schotter, Elizabeth Drew, Trafton Payne, Brennan |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
@ University of South Florida Visual attention plays a fundamental role in many tasks that have important consequences for the daily lives of Americans. Two primary tasks are visual search (e.g., identifying signs of cancer in medical images, or weapons in TSA baggage scans) and reading text (e.g., learning inside and outside of the classroom). Eye movements play a critical role in both tasks, but most cognitive neuroscience methods (e.g., electroencephalography; EEG) require research participants to refrain from moving the eyes because doing so produces artifacts in the neural measurements, which make the brain processes of interest harder to study. However, when eye movements are restricted, the inferences made in these neuroscience studies are somewhat removed from the phenomena being studied. New analytic techniques may allow these fields to move beyond simplified laboratory paradigms but this transition requires significant technological and analytic advances. The long-term goal is to create documentation of ?best practices? and frameworks for future research applications that promote the best work using a combination of eye tracking and electroencephalography methods. Such guidelines should also foster reliability and reproducibility of studies and allow better integration of theoretical insights across scientific domains. |
0.969 |
2023 — 2024 | Drew, Trafton Moher, Jeff |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
@ Connecticut College Distractions are everywhere in modern life, and they bring consequences ranging from the mundane to the deadly. It is well established that distracting objects can attract attention when a viewer first looks at a scene. For example, a flashing roadside billboard may take a driver’s eyes off the road for a moment. But might distractions change behavior in other, more subtle but equally critical ways? Another key aspect of visual attention arises when a person searches for something that may or may not be present and must decide whether or not they’ve found what they are looking for. An important illustration of this is that when a radiologist searches a medical image, there may or may not be an area of concern present in the scan. In these searches, there is a strategic decision component in which the searcher must decide that they’ve looked thoroughly enough to be confident that indeed no “target” is present. However, there is a gap in our knowledge – there has been little research on how distracting objects might affect this decision component. In the current project, the investigators explore the phenomenon of distractor-induced quitting, in which distracting objects alter this decision process and cause people to terminate search earlier than they otherwise would. This early quitting causes people to entirely miss targets that they would otherwise likely find. Knowledge gained from this project will advance our understanding of how distractions are processed, leading to new insights into human behavior in the fields of attention, distraction, and decision-making. Furthermore, these results have potential real-world implications for tasks that involve high-stakes searches for targets, such as medical image screening or x-ray baggage inspection. In particular, it is worth considering that the use of salient signals (e.g., from artificial intelligence) to convey information to a human observer may inadvertently trigger this exact problematic situation. For example, if a computer system is trained to scan images and highlight potential areas of interest for a radiologist (or security personnel) by using a salient signal, these quitting effects might offset any benefits the computer guidance system might otherwise afford. Finally, undergraduate students participate in the design of these experiments, collection of data, and the presentation of results at conferences including those focused on medical imaging. Some of these students are recruited from the Science Leaders program at Connecticut College, a program dedicated to providing opportunities in the sciences for students from historically excluded identities.<br/><br/>Salient signals can alter search strategies when people are looking for targets. More precisely, in recent work, the investigators have discovered that task-irrelevant distractors can cause people to quit searching early. As a result, people more frequently miss targets when these distractors are present. In this project, the investigators use a variety of experimental protocols to explore the impact of salient distractors on visual search in tasks where targets may or may not be present. Participants search for simple targets in visual displays with multiple non-targets and press a key to indicate whether a target is present or not. Eye-tracking is employed to investigate the specific mechanisms that cause participants to quit early as a result of visual distraction – for example, when a distractor is present, does it cause participants to scan the display less exhaustively? Or does it cause participants to look at each item for a shorter time, making them more likely to look at a target but fail to process it correctly? Next, the investigators establish factors that can modulate and potentially eliminate this distractor-induced quitting, such as giving participants control over the appearance and disappearance of a salient cue that may or may not highlight the target. Finally, the investigators examine how the information content of salient signals can impact distractor-induced quitting – in other words, if salient signals sometimes draw attention to the target, do those signals cause as much (or perhaps more) disruption on the occasions where they do not draw attention to the target? Results from these studies may aid our understanding of human visual attention and visual search. Findings are shared with the scientific community at large, but also (more specifically) with colleagues in radiology in order to spark new discussion on how the investigators might apply this research to help improve communications from artificial intelligence systems to human observers in medical settings.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. |
0.919 |