An argument for how (and why) to incentivise replication.

Although Zwaan et al. (2018) have made a compelling case as to why direct replications should occur more frequently than they do, they do not address how such replications attempts can best be encouraged. We propose a novel method for incentivising replication attempts and discuss some issues surrounding its implementation.

Hallucinations and mental imagery demonstrate top-down effects on visual perception.

In this commentary, we present two examples where perception is not only influenced by, but also in fact driven by, top-down effects: hallucinations and mental imagery. Crucially, both examples avoid all six of the potential confounds that Firestone & Scholl (F&S) raised as arguments against previous studies claiming to demonstrate the influence of top-down effects on perception.

Object tracking: absence of long-range spatial interference supports resource theories.

Attentional tracking of a moving target can be impaired by the presence of a second object, particularly if the second object is another target. One potential cause of this impairment is spatial interference. But the impairment may alternatively reflect a need to divide a finite attentional resource among targets. The performance cost of splitting a resource among targets should not be affected by the targets' proximity and should persist even at very large target separations. In contrast, spatial interference should impair performance more when the second object is near than when it is far. Here, we report six experiments that assess the effect of the separation between two targets. Within the crowding zone for target identification found by previous psychophysical literature, tracking performance improved with separation. Beyond the crowding zone, there was no evidence that increases in separation improved two-target performance, suggesting no long-range spatial interference. Unexpectedly, in the one-target condition, greater separation from other distractors reduced performance somewhat. This may reflect a configural tracking process. For the two-target condition, due to the absence of a separation effect beyond the crowding zone, at the largest separations performance at tracking two targets remained much poorer than performance tracking one target. This large additional-target cost is better explained by hemisphere-specific resource theories than by spatial interference.

Evaluating the effectiveness of different perceptual training methods in a difficult visual discrimination task with ultrasound images.

Recent work has shown that perceptual training can be used to improve the performance of novices in real-world visual classification tasks with medical images, but it is unclear which perceptual training methods are the most effective, especially for difficult medical image discrimination tasks. We investigated several different perceptual training methods with medically naïve participants in a difficult radiology task: identifying the degree of hepatic steatosis (fatty infiltration of the liver) in liver ultrasound images. In Experiment 1a (N = 90), participants completed four sessions of standard perceptual training, and participants in Experiment 1b (N = 71) completed four sessions of comparison training. There was a significant post-training improvement for both types of training, although performance was better when the trained task aligned with the task participants were tested on. In both experiments, performance initially improves rapidly, with learning becoming more gradual after the first training session. In Experiment 2 (N = 200), we explored the hypothesis that performance could be improved by combining perceptual training with explicit annotated feedback presented in a stepwise fashion. Although participants improved in all training conditions, performance was similar regardless of whether participants were given annotations, or underwent training in a stepwise fashion, both, or neither. Overall, we found that perceptual training can rapidly improve performance on a difficult radiology task, albeit not to a comparable level as expert performance, and that similar levels of performance were achieved across the perceptual training paradigms we compared.

Motion information is sometimes used as an aid to the visual tracking of objects.

In everyday life, observers often need to visually track moving objects. Currently, there is a debate as to whether observers utilize motion information in doing this or whether they rely purely on positional information (e.g., frame-by-frame locations). In our experiments, we had observers keep track of a subset of moving objects. In one condition, the objects moved in straight lines and their future positions were thus predictable. In a second condition, the objects changed directions randomly. Across three experiments, tracking performance was better in the predictable condition, suggesting that observers can use motion to help them track objects, at least when tracking just two. When tracking four objects, performance was not different between the two conditions. We discuss these findings in relation to several theories of object tracking.

Characterizing the time course of decision-making in change detection.

We propose a novel modeling framework for characterizing the time course of change detection based on information held in visual short-term memory (VSTM). Specifically, we seek to answer whether change detection is better captured by a first-order integration model, in which information is pooled from each location, or a second-order integration model, in which each location is processed independently. We diagnose whether change detection across locations proceeds in serial or parallel and how processing is affected by the stopping rule (i.e., detecting any change vs. detecting all changes; Experiment 1) and how the efficiency of detection is affected by the number of changes in the display (Experiment 2). We find that although capacity is generally limited in both tasks, the architecture varies from parallel self-terminating in the OR task to serial self-terminating in the AND task. Our novel framework allows model comparisons across a large set of models ruling out several competing explanations of change detection. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Explainable models for forecasting the emergence of political instability.

Building on previous research on the use of macroeconomic factors for conflict prediction and using data on political instability provided by the Political Instability Task Force, this article proposes two minimal forecasting models of political instability optimised to have the greatest possible predictive power for one-year and two-year event horizons, while still making predictions that are fully explainable. Both models employ logistic regression and use just three predictors: polity code (a measure of government type), infant mortality, and years of stability (i.e., years since the last instability event). These models make predictions for 176 countries on a country-year basis and achieve AUPRC's of 0.108 and 0.115 for the one-year and two-year models respectively. They use public data with ongoing availability so are readily reproducible. They use Monte Carlo simulations to construct confidence intervals for their predictions and are validated by testing their predictions for a set of reference years separate from the set of reference years used to train them. This validation shows that the models are not overfitted but suggests that some of the previous models in the literature may have been. The models developed in this article are able to explain their predictions by showing, for a given prediction, which predictors were the most influential and by using counterfactuals to show how the predictions would have been altered had these predictors taken different values. These models are compared to models created by lasso regression and it is shown that they have at least as good predictive power but that their predictions can be more readily explained. Because policy makers are more likely to be influenced by models whose predictions can explained, the more interpretable a model is the more likely it is to influence policy.

The more often you see an object, the easier it becomes to track it.

Is it easier to track objects that you have seen repeatedly? We compared repeated blocks, where identities were the same from trial to trial, to unrepeated blocks, where identities varied. People were better in tracking objects that they saw repeatedly. We tested four hypotheses to explain this repetition benefit. First, perhaps the repeated condition benefits from consistent mapping of identities to target and distractor roles. However, the repetition benefit persisted even when both the repeated and the unrepeated conditions used consistent mapping. Second, repetition might improve the ability to recover targets that have been lost, or swapped with distractors. However, we observed a larger repetition benefit for color-color conjunctions, which do not benefit from such error recovery processes, than for unique features, which do. Furthermore, a repetition benefit was observed even in the absence of distractors. Third, perhaps repetition frees up resources by reducing memory load. However, increasing memory load by masking identities during the motion phase reduced the repetition benefit. The fourth hypothesis is that repetition facilitates identity tracking, which in turn improves location tracking. This hypothesis is consistent with all our results. Thus, our data suggest that identity and location tracking share a common resource.

Distinguishing between parallel and serial accounts of multiple object tracking.

Humans can track multiple moving objects. Is this accomplished by attending to all the objects at the same time or do we attend to each object in turn? We addressed this question using a novel application of the classic simultaneous-sequential paradigm. We considered a display in which objects moved for only part of the time. In one condition, the objects moved sequentially, whereas in the other condition they all moved and paused simultaneously. A parallel model would predict that the targets are tracked independently, so the tracking of one target should not be influenced by the movement of another target. Thus, one would expect equal performance in the two conditions. Conversely, a simple serial account of object tracking would predict that an observer's accuracy should be greater in the sequential condition because in that condition, at any one time, fewer targets are moving and thus need to be attended. In fact, in our experiments we observed performance in the simultaneous condition to be equal to or greater than the performance in the sequential condition. This occurred regardless of the number of targets or how the targets were positioned in the visual field. These results are more directly in line with a parallel account of multiple object tracking.

Using meta-predictions to identify experts in the crowd when past performance is unknown.

A common approach to improving probabilistic forecasts is to identify and leverage the forecasts from experts in the crowd based on forecasters' performance on prior questions with known outcomes. However, such information is often unavailable to decision-makers on many forecasting problems, and thus it can be difficult to identify and leverage expertise. In the current paper, we propose a novel algorithm for aggregating probabilistic forecasts using forecasters' meta-predictions about what other forecasters will predict. We test the performance of an extremised version of our algorithm against current forecasting approaches in the literature and show that our algorithm significantly outperforms all other approaches on a large collection of 500 binary decision problems varying in five levels of difficulty. The success of our algorithm demonstrates the potential of using meta-predictions to leverage latent expertise in environments where forecasters' expertise cannot otherwise be easily identified.

Evidence that within-dimension features are generally processed coactively.

In this paper, we examine whether information about an item's category, provided by the same dimension type presented across multiple spatial locations (which we term within-dimension features), is processed independently or pooled into a common representation. We use Systems Factorial Technology (SFT; Townsend & Nozawa, Journal of Mathematical Psychology, 39, 321-340, 1995) and fit parametric logical rule-based models to diagnose whether information processing is serial, parallel, or coactive. The present work focuses on expanding the scope of categorization response time (RT) models by synthesizing recent work in perceptual categorization with theories of visual attention. Our results show that for the majority of participants, processing occurs coactively (i.e., is pooled into a single decision process). For the remainder, other processing strategies were found (e.g., parallel processing). This finding provides new insight into decision-making using within-dimension features presented in multiple locations. It also highlights the importance of both featural information and spatial attention in categorization decision-making.

Conformity to the descriptive norms of people with opposing political or social beliefs.

The descriptive norm effect refers to findings that individuals will tend to prefer behaving certain ways when they know that other people behave similarly. An open question is whether individuals will still conform to other people's behaviour when they do not identify with these other people, such as a Democrat being biased towards following a popular behaviour amongst Republicans. Self-categorization theory makes the intuitive prediction that people will actively avoid conforming to the norms of groups with which they do not identify. We tested this by informing participants that a particular action was more popular amongst people they identified with and additionally informed some participants that this action was unpopular amongst people they did not identify with. Specifically, we presented descriptive norms of people who supported different political parties or had opposing stances on important social issues. Counter to self-categorization theory's prediction, we found that informing participants that an action was unpopular amongst people they did not identify with led participants' preferences to shift away from that action. These results suggest that a general desire to conform with others may outpower the common ingroup vs outgroup mentality.

Commitments increase preparedness for floods.

The current study investigated whether we could encourage Australian residents to become better prepared for floods by inviting them to make a specific commitment to do so. We sampled 374 residents of the state of Victoria (56% male, 81% metropolitan) and 400 residents of the state of New South Wales (45% male, 59% metropolitan) who lived in locations that were potentially at risk of floods. They residents were sampled so that their distributions of ages, genders and living locations were as representative as possible of the population of those two states. These residents completed two surveys that ascertained their preparedness for floods at two points in time, separate by a two-week period. At the end of the first survey all residents received information about how they could better prepare for floods. In addition, approximately half the residents were randomly selected to be invited to commit to becoming better prepared for floods. We found that 74% of residents who were invited to commit to becoming better prepared for floods, were willing to make this commitment. We found that the group that was invited to commit to become better prepared for floods increased their preparedness for floods over the two-week period that separated the two surveys more than the group that was not invited to make this commitment, F(1, 772) = 4.53, p = .034, η2 = .006. We conclude that when emergency services inform residents of flood-prone areas how to better prepare for floods, they should also attempt to elicit from the residents a commitment to become better prepared for floods.

Even arbitrary norms influence moral decision-making.

It is well known that individuals tend to copy behaviours that are common among other people-a phenomenon known as the descriptive norm effect1-3. This effect has been successfully used to encourage a range of real-world prosocial decisions4-7, such as increasing organ donor registrations8. However, it is still unclear why it occurs. Here, we show that people conform to social norms, even when they understand that the norms in question are arbitrary and do not reflect the actual preferences of other people. These results hold across multiple contexts and when controlling for confounds such as anchoring or mere-exposure effects. Moreover, we demonstrate that the degree to which participants conform to an arbitrary norm is determined by the degree to which they self-identify with the group that exhibits the norm. Two prominent explanations of norm adherence-the informational and social sanction accounts2,9-11-cannot explain these results, suggesting that these theories need to be supplemented by an additional mechanism that takes into account self-identity.

Predictors of gambling and problem gambling in Victoria, Australia.

In 2016, the gambling habits of a sample of 3361 adults in the state of Victoria, Australia, were surveyed. It was found that a number of factors that were highly correlated with self-reported gambling frequency and gambling problems were not significant predictors of gambling frequency and problem gambling. The major predictors of gambling frequency were the degree to which family members and peers were perceived to gamble, self-reported approval of gambling, the frequency of discussing gambling offline, and the participant's Canadian Problem Gambling Severity Index (PGSI) score. Age was a significant predictor of gambling frequency for certain types of gambling (e.g. buying lottery tickets). Approximately 91% of the explainable variance in the participant's PGSI score could be explained by just five predictors: Positive Urgency; Frequency of playing poker machines at pubs, hotels or sporting clubs; Participation in online discussions of betting on gaming tables at casinos; Frequency of gambling on the internet, and Overestimating the chances of winning. Based on these findings, suggestions are made as to how gambling-related harm can be reduced.

The double-anchoring theory of lightness perception: a comment on Bressan (2006).

Recently, a double-anchoring theory (DAT) of lightness perception was proposed (P. Bressan, 2006), which offers explanations for all the data explained by the original anchoring theory (A. Gilchrist et al., 1999), as well as a number of additional lightness phenomena. Consequently, DAT can account for an unprecedented range of empirical results, potentially explaining everything from the basic simultaneous contrast display to subtle variations of the Gelb effect. In this comment, the authors raised 4 concerns that demonstrate serious theoretical and empirical difficulties for DAT.

Natural scenes can be identified as rapidly as individual features.

Can observers determine the gist of a natural scene in a purely feedforward manner, or does this process require deliberation and feedback? Observers can recognise images that are presented for very brief periods of time before being masked. It is unclear whether this recognition process occurs in a purely feedforward manner or whether feedback from higher cortical areas to lower cortical areas is necessary. The current study revealed that the minimum presentation time required to identify or to determine the gist of a natural scene was no different from that required to determine the orientation or colour of an isolated line. Conversely, a visual task that would be expected to necessitate feedback (determining whether an image contained exactly six lines) required a significantly greater minimum presentation time. Assuming that the orientation or colour of an isolated line can be determined in a purely feedforward manner, these results indicate that the identification and the determination of the gist of a natural scene can also be performed in a purely feedforward manner. These results challenge a number of theories of visual recognition that require feedback.

Attribute amnesia is greatly reduced with novel stimuli.

Attribute amnesia is the counterintuitive phenomenon where observers are unable to report a salient aspect of a stimulus (e.g., its colour or its identity) immediately after the stimulus was presented, despite both attending to and processing the stimulus. Almost all previous attribute amnesia studies used highly familiar stimuli. Our study investigated whether attribute amnesia would also occur for unfamiliar stimuli. We conducted four experiments using stimuli that were highly familiar (colours or repeated animal images) or that were unfamiliar to the observers (unique animal images). Our results revealed that attribute amnesia was present for both sets of familiar stimuli, colour (p < .001) and repeated animals (p = .001); but was greatly attenuated, and possibly eliminated, when the stimuli were unique animals (p = .02). Our data shows that attribute amnesia is greatly reduced for novel stimuli.

Shared processing in multiple object tracking and visual working memory in the absence of response order and task order confounds.

To understand how the visual system represents multiple moving objects and how those representations contribute to tracking, it is essential that we understand how the processes of attention and working memory interact. In the work described here we present an investigation of that interaction via a series of tracking and working memory dual-task experiments. Previously, it has been argued that tracking is resistant to disruption by a concurrent working memory task and that any apparent disruption is in fact due to observers making a response to the working memory task, rather than due to competition for shared resources. Contrary to this, in our experiments we find that when task order and response order confounds are avoided, all participants show a similar decrease in both tracking and working memory performance. However, if task and response order confounds are not adequately controlled for we find substantial individual differences, which could explain the previous conflicting reports on this topic. Our results provide clear evidence that tracking and working memory tasks share processing resources.

Perceptual training to improve hip fracture identification in conventional radiographs.

Diagnosing certain fractures in conventional radiographs can be a difficult task, usually taking years to master. Typically, students are trained ad-hoc, in a primarily-rule based fashion. Our study investigated whether students can more rapidly learn to diagnose proximal neck of femur fractures via perceptual training, without having to learn an explicit set of rules. One hundred and thirty-nine students with no prior medical or radiology training were shown a sequence of plain film X-ray images of the right hip and for each image were asked to indicate whether a fracture was present. Students were told if they were correct and the location of any fracture, if present. No other feedback was given. The more able students achieved the same level of accuracy as board certified radiologists at identifying hip fractures in less than an hour of training. Surprisingly, perceptual learning was reduced when the training set was constructed to over-represent the types of images participants found more difficult to categorise. Conversely, repeating training images did not reduce post-training performance relative to showing an equivalent number of unique images. Perceptual training is an effective way of helping novices learn to identify hip fractures in X-ray images and should supplement the current education programme for students.