On the reliability of value-modulated attentional capture: An online replication and multiverse analysis.

Stimuli predicting rewards are more likely to capture attention, even when they are not relevant to our current goals. Individual differences in value-modulated attentional capture (VMAC) have been associated with various psychopathological conditions in the scientific literature. However, the claim that this attentional bias can predict individual differences requires further exploration of the psychometric properties of the most common experimental paradigms. The current study replicated the VMAC effect in a large online sample (N = 182) and investigated the internal consistency, with a design that allowed us to measure the effect during learning (rewarded phase) and after acquisition, once feedback was omitted (unrewarded phase). Through the rewarded phase there was gradual increase of the VMAC effect, which did not decline significantly throughout the unrewarded phase. Furthermore, we conducted a reliability multiverse analysis for 288 different data preprocessing specifications across both phases. Specifications including more blocks in the analysis led to better reliability estimates in both phases, while specifications that removed more outliers also improved reliability, suggesting that specifications with more, but less noisy, trials led to better reliability estimates. Nevertheless, in most instances, especially those considering fewer blocks of trials, reliability estimates fell below the minimum recommended thresholds for research on individual differences. Given the present results, we encourage researchers working on VMAC to take into account reliability when designing studies aimed at capturing individual differences and provide recommendations to improve methodological practices.

Incidental Attitude Formation via the Surveillance Task: A Preregistered Replication of the Olson and Fazio (2001) Study.

Evaluative conditioning is one of the most widely studied procedures for establishing and changing attitudes. The surveillance task is a highly cited evaluative-conditioning paradigm and one that is claimed to generate attitudes without awareness. The potential for evaluative-conditioning effects to occur without awareness continues to fuel conceptual, theoretical, and applied developments. Yet few published studies have used this task, and most are characterized by small samples and small effect sizes. We conducted a high-powered (N = 1,478 adult participants), preregistered close replication of the original surveillance-task study (Olson & Fazio, 2001). We obtained evidence for a small evaluative-conditioning effect when "aware" participants were excluded using the original criterion-therefore replicating the original effect. However, no such effect emerged when three other awareness criteria were used. We suggest that there is a need for caution when using evidence from the surveillance-task effect to make theoretical and practical claims about "unaware" evaluative-conditioning effects.

Content and source analysis of popular tweets following a recent case of diphtheria in Spain.

Background: Despite major progress in global vaccination coverage, immunization rates are falling, resulting in outbreaks of vaccine-preventable diseases. This study analyses content and source of the most popular tweets related to a recent case in Spain where an unvaccinated child contracted and later died from diphtheria. Understanding the characteristics of these tweets in the context of vaccination could inform efforts by health promotion professionals to increase their reach and impact. Methods: We extracted tweets containing keywords related to the diphtheria case (from 1 May to 15 July 2015). We explored the prevalence of terms relating to policy and misinformation and manually coded the 194 most popular tweets (retweeted 100 or more times) with regard to source, topic, tone and sentiment. Results: A total of 722 974 tweets were collected. Prevalence of terms relating to policy and misinformation increased at the onset of the case and after the death of the child. Popular tweets (194) were either pro-vaccination (58%) or neutral, with none classified as anti-vaccination. Popular topics included criticism towards anti-vaccination groups (35%) and effectiveness of immunization (22%). Popular tweets were informative (47%) or opinions (53%), which mainly expressed frustration (24%) or humour/sarcasm (23%). Popular Twitter accounts were newspaper and TV channels (15%), as well as individual journalists and authors of popular science (13.4%). Conclusions: Healthcare organizations could collaborate with popular journalists or news outlets and employ authors of popular science to disseminate health information on social media, while addressing public concerns and misinformation in accessible ways.

The procedural learning deficit hypothesis of language learning disorders: we see some problems.

Impaired procedural learning has been suggested as a possible cause of developmental dyslexia (DD) and specific language impairment (SLI). This study examined the relationship between measures of verbal and non-verbal implicit and explicit learning and measures of language, literacy and arithmetic attainment in a large sample of 7 to 8-year-old children. Measures of verbal explicit learning were correlated with measures of attainment. In contrast, no relationships between measures of implicit learning and attainment were found. Critically, the reliability of the implicit learning tasks was poor. Our results show that measures of procedural learning, as currently used, are typically unreliable and insensitive to individual differences. A video abstract of this article can be viewed at: https://www.youtube.com/watch?v=YnvV-BvNWSo.

Researching Mental Health Disorders in the Era of Social Media: Systematic Review.

BACKGROUND: Mental illness is quickly becoming one of the most prevalent public health problems worldwide. Social network platforms, where users can express their emotions, feelings, and thoughts, are a valuable source of data for researching mental health, and techniques based on machine learning are increasingly used for this purpose. OBJECTIVE: The objective of this review was to explore the scope and limits of cutting-edge techniques that researchers are using for predictive analytics in mental health and to review associated issues, such as ethical concerns, in this area of research. METHODS: We performed a systematic literature review in March 2017, using keywords to search articles on data mining of social network data in the context of common mental health disorders, published between 2010 and March 8, 2017 in medical and computer science journals. RESULTS: The initial search returned a total of 5386 articles. Following a careful analysis of the titles, abstracts, and main texts, we selected 48 articles for review. We coded the articles according to key characteristics, techniques used for data collection, data preprocessing, feature extraction, feature selection, model construction, and model verification. The most common analytical method was text analysis, with several studies using different flavors of image analysis and social interaction graph analysis. CONCLUSIONS: Despite an increasing number of studies investigating mental health issues using social network data, some common problems persist. Assembling large, high-quality datasets of social media users with mental disorder is problematic, not only due to biases associated with the collection methods, but also with regard to managing consent and selecting appropriate analytics techniques.

Ambiguity produces attention shifts in category learning.

It has been suggested that people and nonhuman animals protect their knowledge from interference by shifting attention toward the context when presented with information that contradicts their previous beliefs. Despite that suggestion, no studies have directly measured changes in attention while participants are exposed to an interference treatment. In the present experiments, we adapted a dot-probe task to track participants' attention to cues and contexts while they were completing a simple category learning task. The results support the hypothesis that interference produces a change in the allocation of attention to cues and contexts.

Metronome LKM: An open source virtual keyboard driver to measure experiment software latencies.

Experiment software is often used to measure reaction times gathered with keyboards or other input devices. In previous studies, the accuracy and precision of time stamps has been assessed through several means: (a) generating accurate square wave signals from an external device connected to the parallel port of the computer running the experiment software, (b) triggering the typematic repeat feature of some keyboards to get an evenly separated series of keypress events, or (c) using a solenoid handled by a microcontroller to press the input device (keyboard, mouse button, touch screen) that will be used in the experimental setup. Despite the advantages of these approaches in some contexts, none of them can isolate the measurement error caused by the experiment software itself. Metronome LKM provides a virtual keyboard to assess an experiment's software. Using this open source driver, researchers can generate keypress events using high-resolution timers and compare the time stamps collected by the experiment software with those gathered by Metronome LKM (with nanosecond resolution). Our software is highly configurable (in terms of keys pressed, intervals, SysRq activation) and runs on 2.6-4.8 Linux kernels.

The effect of noise-induced variance on parameter recovery from reaction times.

BACKGROUND: Technical noise can compromise the precision and accuracy of the reaction times collected in psychological experiments, especially in the case of Internet-based studies. Although this noise seems to have only a small impact on traditional statistical analyses, its effects on model fit to reaction-time distributions remains unexplored. RESULTS: Across four simulations we study the impact of technical noise on parameter recovery from data generated from an ex-Gaussian distribution and from a Ratcliff Diffusion Model. Our results suggest that the impact of noise-induced variance tends to be limited to specific parameters and conditions. CONCLUSIONS: Although we encourage researchers to adopt all measures to reduce the impact of noise on reaction-time experiments, we conclude that the typical amount of noise-induced variance found in these experiments does not pose substantial problems for statistical analyses based on model fitting.

The Bitter Truth About Sugar and Willpower: The Limited Evidential Value of the Glucose Model of Ego Depletion.

The idea behind ego depletion is that willpower draws on a limited mental resource, so that engaging in an act of self-control impairs self-control in subsequent tasks. To present ego depletion as more than a convenient metaphor, some researchers have proposed that glucose is the limited resource that becomes depleted with self-control. However, there have been theoretical challenges to the proposed glucose mechanism, and the experiments that have tested it have found mixed results. We used a new meta-analytic tool, p-curve analysis, to examine the reliability of the evidence from these experiments. We found that the effect sizes reported in this literature are possibly influenced by publication or reporting bias and that, even within studies yielding significant results, the evidential value of this research is weak. In light of these results, and pending further evidence, researchers and policymakers should refrain from drawing any conclusions about the role of glucose in self-control.

A simple algorithm for the offline recalibration of eye-tracking data through best-fitting linear transformation.

Poor calibration and inaccurate drift correction can pose severe problems for eye-tracking experiments requiring high levels of accuracy and precision. We describe an algorithm for the offline correction of eye-tracking data. The algorithm conducts a linear transformation of the coordinates of fixations that minimizes the distance between each fixation and its closest stimulus. A simple implementation in MATLAB is also presented. We explore the performance of the correction algorithm under several conditions using simulated and real data, and show that it is particularly likely to improve data quality when many fixations are included in the fitting process.

Outcome probability modulates anticipatory behavior to signals that are equally reliable.

A stimulus is a reliable signal of an outcome when the probability that the outcome occurs in its presence is different from in its absence. Reliable signals of important outcomes are responsible for triggering critical anticipatory or preparatory behavior, which is any form of behavior that prepares the organism to receive a biologically significant event. Previous research has shown that humans and other animals prepare more for outcomes that occur in the presence of highly reliable (i.e., highly contingent) signals, that is, those for which that difference is larger. However, it seems reasonable to expect that, all other things being equal, the probability with which the outcome follows the signal should also affect preparatory behavior. In the present experiment with humans, we used two signals. They were differentially followed by the outcome, but they were equally (and relatively weakly) reliable. The dependent variable was preparatory behavior in a Martians video game. Participants prepared more for the outcome (a Martians' invasion) when the outcome was most probable. These results indicate that the probability of the outcome can bias preparatory behavior to occur with different intensities despite identical outcome signaling.

Working memory load does not interfere with distractor suppression in the additional singleton task.

Over the last decade, the additional singleton task has been widely used to study visual statistical learning. In this paradigm, participants are instructed to find a target while ignoring a series of distractors. In some trials, a salient singleton distractor is added to the search display, making the task more difficult. However, if the singleton appears more frequently in one particular location of the display, participants eventually learn to suppress attention towards this location. It has been suggested that this type of learning is probably implicit and independent of working memory (WM) resources. To our knowledge, only one study has explored the impact of WM in suppression effect (Gao & Theeuwes, Psychonomic Bulletin & Review, 27, 96-104, 2020). However, there are reasons to suspect that the amount and type of WM load used in that study may have been suboptimal to detect any effects on distractor suppression. The aim of the present study was to explore the impact of WM load on distractor suppression addressing these issues. Contrary to our expectations, our results confirm that this type of learning is indeed highly resilient even to strong manipulations of WM load.

The role of selection history in the learned predictiveness effect.

Previous research has shown that cues that are good predictors of relevant outcomes receive more attention than nonpredictive cues. This attentional bias is thought to stem from the different predictive value of cues. However, because successful performance requires more attention to predictive cues, the bias may be a lingering effect of previous attention to cues (i.e., a selection history effect) instead. Two experiments assessed the contribution of predictive value and selection history to the bias produced by learned predictiveness. In a first task, participants responded to pairs of cues, only one of which predicted the correct response. A second task was superficially very similar, but the correct response was determined randomly on each trial and participants responded based on some physical characteristic of a target stimulus in each compound. Hence, in this latter task, participants had to pay more attention to the target stimuli, but these stimuli were not consistently associated with a specific response. Results revealed no differences in the attentional bias toward the relevant stimuli in the two tasks, suggesting that the bias induced by learned predictiveness is a consequence of deploying more attention to predictive stimuli during training. Thus, predictiveness may not bias attention by itself, adding nothing over and above the effect expected by selection history. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Zapping the brain to enhance sport performance? An umbrella review of the effect of transcranial direct current stimulation on physical performance.

Concepts such as "neurodoping" have contributed to an expansion in the area of transcranial direct current stimulation (tDCS) and its impact over physical performance in recent years. This umbrella review examines meta-analyses to evaluate tDCS's impact on exercise performance in healthy individuals. We identified 9 meta-analyses that met our inclusion criteria, encompassing 50 crossover studies and 683 participants. Like previous meta-analyses, we found a small but significant effect across individual studies (gz = 0.28, 95%CI [0.18, 0.39]). However, we also found clear evidence of publication bias, low power and substantial variability in methodological decisions. The average effect became non-significant after accounting for publication bias (grm = 0.10, 95%CrI [-0.04, 0.20], BF10 = 0.99), and a specification curve analysis showed that the final effect could range from g = -0.23 to g = 0.33, depending on decisions such as the formula used for estimating the effect size and multiple additional analytic steps. Overall, our findings suggest that current evidence does not conclusively support acute tDCS as an exercise performance enhancer.

Measuring learning and attention to irrelevant distractors in contextual cueing.

Visual search usually improves with repeated exposure to a search display. Previous research suggests that such a "contextual cueing" effect may be supported even by aspects of the search display that participants have been explicitly asked to ignore. Based on this evidence, it has been suggested that the development of contextual cueing over trials does not depend on selective attention. In the present series of experiments, we show that the most common strategy used to prevent participants from paying attention to task-irrelevant distractors often results in suboptimal selection. Specifically, we show that visual search is slower when search displays include many irrelevant distractors. Eye-tracking data show that this happens, at least in part, because participants fixate on them. These results cast doubts on previous demonstrations that contextual cueing is independent of selective attention. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Interactive effects of the probability of the cue and the probability of the outcome on the overestimation of null contingency.

Overestimations of null contingencies between a cue, C, and an outcome, O, are widely reported effects that can arise for multiple reasons. For instance, a high probability of the cue, P(C), and a high probability of the outcome, P(O), are conditions that promote such overestimations. In two experiments, participants were asked to judge the contingency between a cue and an outcome. Both P(C) and P(O) were given extreme values (high and low) in a factorial design, while maintaining the contingency between the two events at zero. While we were able to observe main effects of the probability of each event, our experiments showed that the cue- and outcome-density biases interacted such that a high probability of the two stimuli enhanced the overestimation beyond the effects observed when only one of the two events was frequent. This evidence can be used to better understand certain societal issues, such as belief in pseudoscience, that can be the result of overestimations of null contingencies in high-P(C) or high-P(O) situations.

Revisiting the role of within-compound associations in cue-interaction phenomena.

Although it is thought that within-compound associations are necessary for the occurrence of both backward blocking and unovershadowing, it is not known whether this variable plays a similar role in mediating the two phenomena. Similarly, the roles of within-compound associations in forward blocking and in reduced overshadowing have not been tested independently. The present experiments evaluated how the strength of within-compound associations affects backward blocking, unovershadowing, forward blocking, and reduced overshadowing. Using an allergy task, the strength of within-compound associations was varied by taking advantage of the participants' prior knowledge of common and uncommon food pairings. Backward blocking and unovershadowing effects were present only when highly memorable compound cues were used. Moreover, the magnitudes of both retrospective revaluation effects were affected by the strength of within-compound associations. Forward blocking and reduced overshadowing effects were independent of within-compound associations. These results have important theoretical implications for causal learning research.

Model-free decision making resists improved instructions and is enhanced by stimulus-response associations.

Human behaviour may be thought of as supported by two different computational-learning mechanisms, model-free and model-based respectively. In model-free strategies, stimulus-response associations are strengthened when actions are followed by a reward and weakened otherwise. In model-based learning, previous to selecting an action, the current values of the different possible actions are computed based on a detailed model of the environment. Previous research with the two-stage task suggests that participants' behaviour usually shows a mixture of both strategies. But, interestingly, a recent study by da Silva and Hare (2020) found that participants primarily deploy model-based behaviour when they are given detailed instructions about the structure of the task. In the present study, we reproduce this essential experiment. Our results confirm that improved instructions give rise to a stronger model-based component. Crucially, we also found a significant effect of reward that became stronger under conditions that favoured the development of strong stimulus-response associations. This suggests that the effect of reward, often taken as indicator of a model-free component, is related to stimulus-response learning.

Learning to suppress a distractor may not be unconscious.

The additional singleton task has become a popular paradigm to explore visual statistical learning and selective attention. In this task, participants are instructed to find a different-shaped target among a series of distractors as fast as possible. In some trials, the search display includes a singleton distractor with a different color, making search more difficult. This singleton distractor appears more often in one location than in the remaining locations. The typical results of these experiments show that participants learn to ignore the area of the screen that is more likely to contain the singleton distractor. It is often claimed that this learning takes place unconsciously, because at the end of the experiment participants seem to be unable to identify the location where the singleton distractor appeared most frequently during the task. In the present study, we tested participants' awareness in three high-powered experiments using alternative measures. Contrary to previous studies, the results show clear evidence of explicit knowledge about which area of the display was more likely to contain the singleton distractor, suggesting that this type of learning might not be unconscious.