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).

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).

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.

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.

No evidence for contextual cueing beyond explicit recognition.

Many studies claim that visual regularities can be learned unconsciously and without explicit awareness. For example in the contextual cueing paradigm, studies often make claims using a standard reasoning based on two results: (1) a reliable response time (RT) difference between repeated vs. new stimulus displays and (2) a close-to-chance sensitivity when participants are asked to explicitly recognize repeated stimulus displays. From this pattern of results, studies routinely conclude that the sensitivity of RT responses is higher than that of explicit responses-an empirical situation we call Indirect Task Advantage (ITA). Many studies further infer from an ITA that RT effects were driven by a form of recognition that exceeds explicit memory: implicit recognition. However, this reasoning is flawed because the sensitivity underlying RT effects is never computed. To properly establish a difference, a sensitivity comparison is required. We apply this sensitivity comparison in a reanalysis of 20 contextual cueing studies showing that not a single study provides consistent evidence for ITAs. Responding to recent correlation-based arguments, we also demonstrate the absence of evidence for ITAs at the level of individual participants. This lack of ITAs has serious consequences for the field: If RT effects can be fully explained by weak but above-chance explicit recognition sensitivity, what is the empirical content of the label "implicit"? Thus, theoretical discussions in this paradigm-and likely in other paradigms using this standard reasoning-require serious reassessment because the current data from contextual cueing studies is insufficient to consider recognition as implicit.

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.

An umbrella review of randomized control trials on the effects of physical exercise on cognition.

Extensive research links regular physical exercise to an overall enhancement of cognitive function across the lifespan. Here we assess the causal evidence supporting this relationship in the healthy population, using an umbrella review of meta-analyses limited to randomized controlled trials (RCTs). Despite most of the 24 reviewed meta-analyses reporting a positive overall effect, our assessment reveals evidence of low statistical power in the primary RCTs, selective inclusion of studies, publication bias and large variation in combinations of pre-processing and analytic decisions. In addition, our meta-analysis of all the primary RCTs included in the revised meta-analyses shows small exercise-related benefits (d = 0.22, 95% confidence interval 0.16 to 0.28) that became substantially smaller after accounting for key moderators (that is, active control and baseline differences; d = 0.13, 95% confidence interval 0.07 to 0.20), and negligible after correcting for publication bias (d = 0.05, 95% confidence interval -0.09 to 0.14). These findings suggest caution in claims and recommendations linking regular physical exercise to cognitive benefits in the healthy human population until more reliable causal evidence accumulates.

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.

The role of working memory in probabilistic cuing of visual search.

In a typical probabilistic cuing experiment, participants are asked to find a visual target among a series of distractors. Although participants are not informed about this, the target appears more frequently in one region of the display, resulting in faster search times for targets located in this region. This bias is thought to depend on a habit-like attentional control mechanism, unconstrained by the availability of working memory (WM) resources. However, the only study that has explored this feature in the past suffers from methodological shortcomings that leave the results open to alternative explanations. In three experiments, we aimed to confirm whether probabilistic cuing is unaffected by visual, spatial, and spatiotemporal WM load. For each experiment, one group of participants performed the visual search task during the retention interval of a WM task (high-load group), whereas another group of participants (no-load group) carried out the visual search task after the WM task. We hypothesized that the probabilistic cuing effect would be larger for the no-load group compared to the high-load group. This hypothesis was confirmed in one experiment, but exploratory analyses suggest that the results can be highly dependent on the analytic approach, casting doubts on its robustness. Overall, our results provide partial support for the hypothesis that probabilistic cuing is not affected by a secondary task. However, given that some analyses reveal an effect of WM load, we conclude that it might be premature to rule out the possibility that the expression of this attentional bias requires WM resources. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The role of working memory in contextual cueing of visual attention.

It is usually easier to find objects in familiar contexts that we have seen before. The type of learning that underlies this facilitation, known as contextual cueing, has been understood as an incidental and automatic process given that, among other reasons, it seems to be independent of working memory (WM) resources. This claim has found support in previous research showing that contextual cueing can be acquired latently, while participants perform a demanding WM task. However, previous studies have not always found this pattern of results and, in general, the available evidence is far from conclusive. The aim of the present study was to clarify the role of WM in contextual learning with two large-sample, confirmatory experiments. Our results show a robust contextual cueing effect even when visuospatial working memory resources were recruited by a demanding secondary task.

Is probabilistic cuing of visual search an inflexible attentional habit? A meta-analytic review.

In studies on probabilistic cuing of visual search, participants search for a target among several distractors and report some feature of the target. In a biased stage the target appears more frequently in one specific area of the search display. Eventually, participants become faster at finding the target in that rich region compared to the sparse region. In some experiments, this stage is followed by an unbiased stage, where the target is evenly located across all regions of the display. Despite this change in the spatial distribution of targets, search speed usually remains faster when the target is located in the previously rich region. The persistence of the bias even when it is no longer advantageous has been taken as evidence that this phenomenon is an attentional habit. The aim of this meta-analysis was to test whether the magnitude of probabilistic cuing decreases from the biased to the unbiased stage. A meta-analysis of 42 studies confirmed that probabilistic cuing during the unbiased stage was roughly half the size of cuing during the biased stage, and this decrease persisted even after correcting for publication bias. Thus, the evidence supporting the claim that probabilistic cuing is an attentional habit might not be as compelling as previously thought.

Raising awareness about measurement error in research on unconscious mental processes.

Experimental psychologists often neglect the poor psychometric properties of the dependent measures collected in their studies. In particular, a low reliability of measures can have dramatic consequences for the interpretation of key findings in some of the most popular experimental paradigms, especially when strong inferences are drawn from the absence of statistically significant correlations. In research on unconscious cognition, for instance, it is commonly argued that the lack of a correlation between task performance and measures of awareness or explicit recollection of the target stimuli provides strong support for the conclusion that the cognitive processes underlying performance must be unconscious. Using contextual cuing of visual search as a case study, we show that given the low reliability of the dependent measures collected in these studies, it is usually impossible to draw any firm conclusion about the unconscious character of this effect from correlational analyses. Furthermore, both a psychometric meta-analysis of the available evidence and a cognitive-modeling approach suggest that, in fact, we should expect to see very low correlations between performance and awareness at the empirical level, even if both constructs are perfectly related at the latent level. Convincing evidence for the unconscious character of contextual cuing and other effects will most likely demand richer and larger data sets, coupled with more powerful analytic approaches.

The evidential value of research on cognitive training to change food-related biases and unhealthy eating behavior: A systematic review and p-curve analysis.

Cognitive bias modification (CBM), which retrains implicit biases towards unhealthy foods, has been proposed as a promising adjunct to improve the efficacy of weight loss interventions. We conducted a systematic review of research on three CBM approaches (i.e., cue-specific inhibitory control, approach bias modification, and attentional bias modification) for reducing unhealthy eating biases and behavior. We performed a p-curve analysis to determine the evidential value of this research; this method is optimally suited to clarify whether published results reflect true effects or false positives due to publication and reporting biases. When considering all CBM approaches, our results suggested that the findings of CBM trials targeting unhealthy eating are unlikely to be false positives. However, only research on attentional bias modification reached acceptable levels of power. These results suggest that CBM interventions may be an effective strategy to enhance the efficacy of weight loss interventions. However, there is room for improvement in the methodological standards of this area of research, especially increasing the statistical power can help to fully clarify the clinical potential of CBM, and determine the role of potential moderators.

Publication bias and low power in field studies on goal priming.

Research on goal priming asks whether the subtle activation of an achievement goal can improve task performance. Studies in this domain employ a range of priming methods, such as surreptitiously displaying a photograph of an athlete winning a race, and a range of dependent variables including measures of creativity and workplace performance. Chen, Latham, Piccolo and Itzchakov (Chen et al. 2021 J. Appl. Psychol. 70, 216-253) recently undertook a meta-analysis of this research and reported positive overall effects in both laboratory and field studies, with field studies yielding a moderate-to-large effect that was significantly larger than that obtained in laboratory experiments. We highlight a number of issues with Chen et al.'s selection of field studies and then report a new meta-analysis (k = 13, N = 683) that corrects these. The new meta-analysis reveals suggestive evidence of publication bias and low power in goal priming field studies. We conclude that the available evidence falls short of demonstrating goal priming effects in the workplace, and offer proposals for how future research can provide stronger tests.

Contextual cuing of visual search does not guide attention automatically in the presence of top-down goals.

Visual search is faster when it occurs within repeated displays, a phenomenon known as contextual cuing (CC). CC has been explained as the result of an automatic orientation of attention toward a target item driven by learned distractor-target associations. In 3 experiments we tested the specific hypothesis that CC is an automatic process of attentional guidance. Participants first searched for a T target in a standard CC procedure. Then, they experienced the same repeated configurations (with the T still present), but now searched for a Y target that was positioned either in a location on the same, or on a different side, from the old T target. Results suggested that there was no interference caused by the old T-target: target search was not affected by the relative positions of the T and Y. Instead, we found a general facilitation in search times for repeated configurations (Experiments 1 and 2). This main effect disappeared when the need for visual search was eliminated in Experiment 3 using a "feature search task". These results suggest that repeated sets of distractors did not trigger an uncontrollable response toward the position of the T; instead, CC was produced by perceptual learning processes. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

The Challenge of Inferring Unconscious Mental Processes.

Studies of unconscious mental processes often compare a performance measure (e.g., some assessment of perception or memory) with a measure of awareness (e.g., a verbal report or forced-choice response) of the critical cue or contingency taken either concurrently or separately. The resulting patterns of bivariate data across participants lend themselves to several analytic approaches for inferring the existence of unconscious mental processes, but it is rare for researchers to consider the underlying generative processes that might cause these patterns. We show that bivariate data are generally insufficient to discriminate single-process models, with a unitary latent process determining both performance and awareness, from dual-process models, comprising distinct latent processes for performance and awareness. Future research attempting to isolate and investigate unconscious processes will need to employ richer types of data and analyses.

Deep Learning With Anaphora Resolution for the Detection of Tweeters With Depression: Algorithm Development and Validation Study.

BACKGROUND: Mental health problems are widely recognized as a major public health challenge worldwide. This concern highlights the need to develop effective tools for detecting mental health disorders in the population. Social networks are a promising source of data wherein patients publish rich personal information that can be mined to extract valuable psychological cues; however, these data come with their own set of challenges, such as the need to disambiguate between statements about oneself and third parties. Traditionally, natural language processing techniques for social media have looked at text classifiers and user classification models separately, hence presenting a challenge for researchers who want to combine text sentiment and user sentiment analysis. OBJECTIVE: The objective of this study is to develop a predictive model that can detect users with depression from Twitter posts and instantly identify textual content associated with mental health topics. The model can also address the problem of anaphoric resolution and highlight anaphoric interpretations. METHODS: We retrieved the data set from Twitter by using a regular expression or stream of real-time tweets comprising 3682 users, of which 1983 self-declared their depression and 1699 declared no depression. Two multiple instance learning models were developed-one with and one without an anaphoric resolution encoder-to identify users with depression and highlight posts related to the mental health of the author. Several previously published models were applied to our data set, and their performance was compared with that of our models. RESULTS: The maximum accuracy, F1 score, and area under the curve of our anaphoric resolution model were 92%, 92%, and 90%, respectively. The model outperformed alternative predictive models, which ranged from classical machine learning models to deep learning models. CONCLUSIONS: Our model with anaphoric resolution shows promising results when compared with other predictive models and provides valuable insights into textual content that is relevant to the mental health of the tweeter.

Is the habit system altered in individuals with obesity? A systematic review.

Habit-like eating behavior is repeatedly pointed to as a key cognitive mechanism contributing to the emergence and maintenance of obesity. Here, we conducted a systematic review of the literature to assess the existent behavioral evidence for the Habit Hypothesis for Overeating (HHO) which states that obesity is the consequence of an imbalance between the habit and goal-directed reward learning systems, leading to overconsumption of food. We found a total of 19 studies implementing a variety of experimental protocols (i.e., free operant paradigm, slips-of-action test, two-step task, Pavlovian-to-Instrumental paradigm, probabilistic learning task) and manipulations. Taken together, the studies on clinical (binge eating disorder) and non-clinical individuals with overweight or obesity do not support the HHO conclusively. While the scientific literature on HHO is still in its infancy, the heterogeneity of the extant studies makes it difficult to evaluate the degree of convergence of these findings. Uncovering the role of reward learning systems in eating behaviors might have a transformative impact on public health.