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The traditional lecture model has come under scrutiny for being ineffective at capturing students’ attention (Bradbury, 2016). These effects are exacerbated as universities shift towards online modes of delivery (Fauville et al., 2023; Mu et al., 2019). This failure to capture attention ultimately creates barriers for learning, as poorer attention during lectures is predictive of poorer recall of lecture content (Schachter & Szpunar, 2015). In efforts to address this, studies have found that university students report less mind-wandering and retain more information when lectures are punctuated with frequent rest breaks, or are interpolated with quizzes that prime students to engage with future topics (pre-testing) or assess knowledge of recently covered topics (post-testing) (Welhaf et al., 2022; Buglass et al., 2021; Szpunar et al., 2013). However, the implications of these findings for attention are limited by the use of subjective self-report and little research has directly compared the outcomes of all three lecture strategies. The current study therefore aims to systematically compare the impacts of rest breaks, pre-testing and post-testing on students’ attention and retention of lecture content. We build on previous experiments by comparing how all three lecture strategies influence students’ eye-gaze patterns, which serve as a proxy for how well students are maintaining their attention (Rosengrant et al., 2021; Ranti et al., 2020). We also compare how each lecture strategy predicts students’ long-term recall of lecture content, and investigate the extent that recall in the interpolated testing conditions is influenced by a practice advantage. Finally, we examine note-taking patterns between the lecture conditions, and how this might be related to students’ learning outcomes. In doing so, we can create evidence-based recommendations for educators on how to use each strategy to produce specific learning outcomes and further our knowledge of how attention fluctuates in dynamic contexts. We investigate the following research questions: 1. How do rest breaks, pre-testing and post-testing (lecture strategies) influence patterns of on-task gaze fixation durations throughout the course of a lecture? 2. How do these lecture strategies influence students’ long-term recall of lecture content? 3. Does presenting material in a quiz format during the lecture affect recall of that material later? 4. Does the completeness of students’ notes differ between lectures that use rest breaks, pre-testing and post-testing, and is the completeness of note-taking related to recall?

Vigilance decrements, where performance on monotonous tasks with rare targets worsens over time, have been well documented in the literature (Langner & Eickhoff, 2013). Recently, Karimi-Rouzbahani et al. (2021) replicated these findings with a dynamic multiple-object-monitoring (MOM) task that better captures elements of real-world environments and allows distinction of vigilance effects from the general effects of sustained attention. However, this study only compared very rare target frequencies (6%) to active responding (targets frequency of 50%). To more clearly understand how target frequency influences vigilance performance, examination of the intermediate target frequencies is necessary. Thus, the current study will use the MOM task (see Karimi-Rouzbahani et al., 2021 for more detail) and manipulate target frequency to: 1. Examine the effect of target frequency (TF) on the magnitude of the vigilance decrement. 2. Assess whether the findings of the original study (Karimi-Rouzbahani et al., 2021) can be replicated with a shorter task duration of 20 minutes. For this study, performance will be measured using the magnitude of the vigilance decrement. This decrement will be inferred from a) miss rate for targets; and b) reaction time (RT), defined as average RT on hits. A greater vigilance decrement will be demonstrated by an increase in miss rate and/or increase in RT over time on task (specifically, a comparison of the average performance in the first 3 blocks relative to the final 3 blocks).

Study details and pre-registration for Experiment 1 on Bodily-self cues and visuo-tactile temporal order judgments.

Raw data (BIDS), analysis scripts, figures, and stimuli for "Temporal dissociation of neural activity underlying synesthetic and perceptual colours"

This experiment is based upon the results of Crowe, Howard, Gilchrist, and Kent (2021) who explored the effect of motion on visual search in a change event task. The authors developed a dynamic visual search task, which involved monitoring the display for a critical change event, to investigate the effect that dynamic stimuli may have on the detection of a feature change in visual search (Crowe, Howard, Gilchrist, & Kent, 2021). Participants needed to search for an orientation change of Gabor patches, where the display showed either all static or all dynamic stimuli or a combination of static and dynamic stimuli with either a static or dynamic target (Crowe et al., 2021). Crowe et al. found that motion of the distractors and the target itself slowed down change detection. Crowe et al. suggest that the motion of the target and distractor stimuli silence fast feature change detection, as seen in the ‘Motion Silencing Effect’ (MSE) with other types of stimuli (Suchow & Alvarez, 2011a). The MSE is a visual illusion where a stimulus display changing in size, shape, hue or brightness appears to change more slowly in its respective stimulus dimension once the display starts to rotate, with an apparent cessation of stimulus change at higher rotation speeds (Suchow & Alvarez, 2011a). The authors initially suggested that motion silences the detection of this feature change, despite participants attending to the display and being aware that the stimuli are changing (Suchow & Alvarez, 2011b). It is plausible that the MSE is contributing to the finding by Crowe et al. (2021) of motion possessed by both the target and distractor stimuli slowing down rapid feature change detection. However, the search task employed by Crowe et al. is complex in comparison to the methods used in more ‘classic’ motion silencing experiments. The latter usually employ psychophysical methods, in the form of method-of-adjustment or binary choice tasks, where the observer fixates their gaze on a constrained display of changing stimuli arranged in an annulus (Choi, Bovik, & Cormack, 2014; Suchow & Alvarez, 2011a). To the authors’ best knowledge, no task has yet investigated the MSE in a visual search task, or any task that may translate to more real-world applications. As such, this study aims to investigate the role of the MSE in dynamic change detection tasks, which require visual search for successful task completion. To approach the question of whether dynamic change detection tasks are also subject to motion silencing, the authors have decided to approximate the study by Crowe et al. (2021) gradually, through an initial exploration into the occurrence of the MSE in static and dynamic Gabor patch displays. Here, each Gabor patch changes orientation, and the displays will be shown at different rotational speeds. The participants will be required to make a binary judgement after each visual display, to indicate whether they were able to perceive the orientation change of the individual Gabor patches, or not.

This project investigates the influence of reward on the perception of visual information. Previous studies repeatedly show that reward can capture attention even if the reward information is not behaviorally relevant or counterproductive. This indicates that the effect of reward occurs before the information reaches attention. This project explores this idea of reward's impact on early stages of brain's information-processing stream, i.e., perception.

Computer-aided detection (CAD) systems generally use a binary cue to indicate a target in an image to an observer (Cunningham, Drew, & Wolfe, 2017). This means that the CAD system provides a marker around (or an arrow pointing towards) any location in an image where the strength of the signal is above a certain threshold and does not provide a marker for those locations where the signal is below the threshold. CAD systems are not completely accurate. In target-present trials, the CAD system may correctly mark the target only (hit), however it may also commit three errors: It may correctly mark the target and incorrectly mark one or more distractors (hit / false alarm), fail to mark the target and incorrectly mark one or more distractors (miss / false alarm), or fail to mark the target and correctly not mark any distractors (miss). In target-absent trials, the CAD may correctly not mark any distractors (correct rejection), or incorrectly mark one or more distractors (false alarm). CAD systems that use binary cues have been shown to lead to increased detection (by the observer) of targets that are marked by the CAD, but they also lead to decreased detection of targets that are missed by the CAD, especially when a distractor has also been cued (Drew, Guthrie, & Reback, 2020; see also Russell & Kunar, 2012 for the exogenous cueing of low prevalence targets). When the CAD system does not provide any cue in a target-present trial (miss), the increased misses of these targets could be due to an overreliance of the observer on the information that the CAD conveys (the overreliance hypothesis; Kunar Watson, Taylor-Phillips, & Wolska, 2017). When the CAD system fails to cue a target and also cues a distractor (miss / false alarm) the increased misses of these targets could be due to an overreliance on the CAD and/or because the exogenous CAD cue(s) capture the observer’s attention to specific locations in the image, drawing it away from non-cued locations that may contain a target. Here, we will test the overreliance hypothesis by removing the localised attentional capture aspect of the CAD cues. We will use non-spatial CAD cues to convey the CAD information to the observer through a coloured border around the image when a target is detected by the CAD system. These cues will provide CAD information to the observer without capturing attention to specific locations. These cues differ from spatial cues in the errors that the system can make. When a target is present and the system provides a cue, it can no longer make the hit / false alarm or miss / false alarm errors. Participants will complete a letter search task under two conditions: with non-spatial CAD cues and without. We predict that participants will perform better (than without CAD) when the non-spatial CAD correctly cues a target (hit), demonstrating that participants are using the CAD information. We also predict that participants will perform worse (than without CAD) when the non-spatial CAD fails to cue a target (miss), thus providing support for the overreliance hypothesis. If participants perform better on CAD hit trials, but no worse on CAD miss trials, both relative to without CAD, this suggests that attentional capture may be responsible for some of the errors in spatial CAD.

Suchow and Alvarez (2011a) demonstrated that a stimulus undergoing a feature change in either size, hue, shape or brightness would appear to change more slowly once the display started to rotate. The stimulus, often an annulus made up out of small circles that would exhibit the feature change, would even appear to stop changing at high rotation speeds (Suchow & Alvarez, 2011a). Though previous studies have investigated to what extent grouping (Peirce, 2013), crowding, global motion (Turi & Burr, 2013), velocity, spacing and eccentricity (Choi et al., 2014, 2016) contribute to this visual illusion, no consensus has been reached on what exactly drives this effect called ‘motion silencing’. This study is a follow-up study to The Motion Silencing Effect (MSE) in Static and Dynamic Orientation Change Detection: Experiment 1 (https://doi.org/10.17605/OSF.IO/TZ79W), where we investigated the MSE in a change detection task for dynamic and static Gabor patch displays. We found that local orientation change detection was less accurate with increasing global motion of the display, in line with the MSE and that there was no qualitative difference between the static and dynamic condition that involved global rotation. In this study, we will investigate the role of attention in the MSE, as this has not been researched yet (Suchow & Alvarez, 2017) and qualitative feedback from participants of our first study suggested that covert orienting of attention towards an individual Gabor patch helped successful detection of change. Consequently, we will use the Posner Cueing Paradigm (Posner, 1980; Posner et al., 1978) to direct spatial attention covertly in a direction discrimination task. Using valid, invalid and neutral cueing conditions and the psi-marginal adaptive method (Prins, 2013; Prins & Kingdon, 2009) to estimate threshold parameters, participants will be required to give a binary judgment after each stimulus display, to indicate which way individual Gabor patches rotated throughout the display.

The benefits of scientific discoveries are felt throughout our society, ranging from health to security, communication, and quality of life. With our rapidly changing world, society has a considerable vested interest in attracting creative, passionate, and intelligent people into scientific careers. But this career path is becoming less certain: researchers perceive that fundamental science — the pursuit of knowledge and understanding of humanity or the natural world without consideration for an end product — is undervalued and under threat. This report presents results from an international online survey demonstrating that researchers around the world observe a decrease in support for fundamental science in the context of increased support for applied research. As a result, their decisions about the direction of research programmes have changed. The authors highlight how researchers see changes in patterns of funding and research directions over a decade, and the impact this may have on innovation and our future generations of scientists. Based on survey results of respondents from 64 countries, this report provides unique insights into the different factors that influence decisions about the type of research scientists engage in. Despite distinct experiences, backgrounds, and cultural reference points, clear messages come through regarding the emphasis and value of fundamental research. The ability to create innovation and build capacity in the future requires greater investment in fundamental research and a wider appreciation of the crucial role it plays in our capacity to respond to global challenges.