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Does animacy affect visual statistical learning? Revisiting the effects of selective attention and animacy on visual statistical learning

Animates receive preferential attentional processing over inanimates because, from an evolutionary perspective, animates are important to human survival. We investigated whether animacy affects visual statistical learning-the detection and extraction of regularities in visual information from our rich, dynamic, and complex environment. Participants completed a selective-attention task, in which regularities were embedded in two visual streams, an attended and an unattended visual stream. The attended visual stream always consisted of line-drawings of non-objects, while the unattended visual stream consisted of line-drawings of either animates or inanimates. Participants then completed a triplet-discrimination task, which assessed their ability to extract regularities from the attended and unattended visual streams. We also assessed participants' awareness of regularities in the visual statistical learning task, and asked if any learning strategies were used. We were specifically interested in whether the animacy status of line-drawings in the unattended visual stream would affect visual statistical learning. There were four key findings. First, selective attention modulates visual statistical learning, with greater visual statistical learning for attended than for unattended information. Second, animacy does not affect visual statistical learning, with no differences found in visual statistical learning performance between the animate and inanimate condition. Third, awareness of regularities was associated with visual statistical learning of attended information. Fourth, participants used strategies (e.g., naming or labelling stimuli) during the visual statistical learning task. Further research is required to understand whether visual statistical learning is one of the adaptive functions that evolved from ancestral environments.

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Normative values and diagnostic optimisation of three social cognition measures for autism and schizophrenia diagnosis in a healthy adolescent and adult sample

Awareness of the importance of assessing social cognition skills under conditions showing atypical social behaviours has increased over the years. However, the evaluation of the psychometric properties of the measures and the availability of normative values for the clinical context are still limited. This study aims to revise, provide normative values, and evaluate the clinical validity of the Italian version of three social cognition measures: Advanced Theory of Mind (A-ToM) task, the Emotion Attribution Task (EAT), and the Social Situation Task (SST). Measures were administered to 580 adolescents and adult healthy controls (age range 14-50). We performed differential item functioning and Rasch analysis to revise each task, so normative data of the revised measures were calculated. Moreover, the revised measures were administered to 38 individuals with autism spectrum disorder (ASD) and 35 individuals with schizophrenia spectrum disorders (SSD): ASD and SSD were matched by age, gender, and IQ with a control sample to evaluate clinical validity. ROC analysis showed that the SST is the best measure differentiating between healthy and clinical groups, compared to the A-ToM (AUCASD = 0.70; AUCSSD = 0.65) and EAT (AUCASD = 0.67; AUCSSD = 0.50), which showed poorer performance. For SSD diagnosis, two SST subscales (Violation and Gravity score) indicated the best accuracy (AUCs of 0.88 and 0.84, respectively); for the ASD diagnosis, we propose a combined score between the SST subscale and A-ToM (AUC = 0.86). The results suggest that the proposed measures can be used to support the diagnostic process and clinical practice.

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Examining listeners’ perception of spoken words with different face masks

The COVID-19 pandemic made face masks part of daily life. While masks protect against the virus, it is important to understand the impact masks have on listeners' recognition of spoken words. We examined spoken word recognition under three different mask conditions (no mask; cloth mask; Kn95 mask) and in both easy (low density, high phonotactic probability) and hard (high density, low phonotactic probability) words in a lexical decision task. In Experiment 1, participants heard all words and nonwords under all three mask conditions. In Experiment 2, participants heard each word and nonword only once under one of the mask conditions. The reaction time and accuracy results were consistent between Experiments 1 and 2. The pattern of results was such that the no mask condition produced the fastest and most accurate responses followed by the Kn95 mask condition and the cloth mask condition, respectively. Furthermore, there was a trend towards a speed-accuracy trade-off with Word Type. Easy words produced faster but less accurate responses relative to hard words. The finding that cloth masks had a more detrimental impact on spoken word recognition than Kn95 masks is consistent with previous research, and the current results further demonstrate that this effect extends to individual word recognition tasks with only audio presentation.

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Put you in the problem: Effects of self-pronouns on mathematical problem-solving

Self-cues such as personal pronouns are known to elicit processing biases, such as attention capture and prioritisation in working memory. This may impact the performance of tasks that have a high attentional load like mathematical problem-solving. Here, we compared the speed and accuracy with which children solved numerical problems that included either the self-cue "you," or a different character name. First, we piloted a self-referencing manipulation with N = 52, 7 to 11 year-olds, testing performance on addition and subtraction problems that had either a single referent ("You"/"Sam") or more than one referent. We took into account operation and positioning of the pronoun and also measured performance on attention and working memory tasks. We found a robust accuracy advantage for problems that included "you," regardless of how many characters were included. The accuracy advantage for problems with a self-pronoun was not statistically associated with individual differences in attention or working memory. In our main study (9 to 11 year-olds, N = 144), we manipulated problem difficulty by creating consistently and inconsistently worded addition and subtraction problems. We found significantly higher speed and accuracy for problems that included "you." However, this effect varied by task difficulty, with the self-pronoun effect being strongest in the most difficult inconsistently worded, subtraction problems. The advantage of problems with a self-pronoun was not associated with individual differences in working memory. These findings suggest that self-cues like the pronoun "you" can be usefully applied in numerical processing tasks, an effect that may be attributable to the effects of self-cues on attention.

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Transcoding of French numbers for first- and second-language learners in third grade

Transcoding is the process of translating between spoken and written numbers, and it is correlated with other mathematical skills. In the present study, we investigated the link between French number writing of 49 students in the third grade (aged 7-9 years) and their language skills. Transcoding in French is of particular interest because the spoken number language system does not completely correspond to that of the written digits (e.g., quatre-vingt-dix [four-twenty-ten] and 90). We hypothesised that the complex linguistic structure of spoken numbers in French would be challenging for students who are learning to transcode. First and second French-language learners' accuracy and errors were recorded during a writing task of 3- to 7-digit numbers. Children also completed linguistic tests (e.g., receptive vocabulary, receptive syntax). Results showed that first- and second-language learners did not differ in their transcoding accuracy. Number size, decade complexity of stimulus number words in French (i.e., numbers containing a complex decade, operationalized as a number between soixante-dix, 70, and quatre-vingt-dix-neuf, 99), and receptive vocabulary predicted children's French transcoding skills. Students were more likely to produce errors (e.g., 68 or 6018 for 78) when they transcoded complex decade numbers compared with simple decade numbers. When an error was made on the complex decade portion of a number, it was likely a lexical error. In conclusion, third graders, both first- and second-language learners, found complex decade numbers challenging and their performance was related to their general vocabulary skills.

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What can evidence accumulation modelling tell us about human social cognition?

Evidence accumulation models are a series of computational models that provide an account for speeded decision-making. These models have been used extensively within the cognitive psychology literature to great success, allowing inferences to be drawn about the psychological processes that underlie cognition that are sometimes not available in a traditional analysis of accuracy or reaction time (RT). Despite this, there have been only a few applications of these models within the domain of social cognition. In this article, we explore several ways in which the study of human social information processing would benefit from application of evidence accumulation modelling. We begin first with a brief overview of the evidence accumulation modelling framework and their past success within the domain of cognitive psychology. We then highlight five ways in which social cognitive research would benefit from an evidence accumulation approach. This includes (1) greater specification of assumptions, (2) unambiguous comparisons across blocked task conditions, (3) quantifying and comparing the magnitude of effects in standardised measures, (4) a novel approach for studying individual differences, and (5) improved reproducibility and accessibility. These points are illustrated using examples from the domain of social attention. Finally, we outline several methodological and practical considerations, which should help researchers use evidence accumulation models productively. Ultimately, it will be seen that evidence accumulation modelling offers a well-developed, accessible, and commonly understood framework that can reveal inferences about cognition that may otherwise be out of reach in a traditional analysis of accuracy and RT. This approach, therefore, has the potential to substantially revise our understanding of social cognition.

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Unidirectional rating scales overestimate the illusory causation phenomenon

Illusory causation is a phenomenon in which people mistakenly perceive a causal relationship between a cue and outcome even though the contingency between them is actually zero. Illusory causation studies typically use a unidirectional causal rating scale, where one endpoint refers to no relationship and the other to a strongly positive causal relationship. This procedure may bias mean causal ratings in a positive direction, either by censoring negative ratings or by discouraging participants from giving the normative rating of zero which is at the bottom extreme of the scale. To test this possibility, we ran two experiments that directly compared the magnitude of causal illusions when assessed with a unidirectional (zero-positive) versus a bidirectional (negative-zero-positive) rating scale. Experiment 1 used high cue and outcome densities (both 75%), whereas Experiment 2 used neutral cue and outcome densities (both 50%). Across both experiments, we observed a larger illusory causation effect in the unidirectional group compared with the bidirectional group, despite both groups experiencing the same training trials. The causal illusions in Experiment 2 were observed despite participants accurately learning the conditional probabilities of the outcome occurring in both the presence and absence of the cue, suggesting that the illusion is driven by the inability to accurately integrate conditional probabilities to infer causal relationships. Our results indicate that although illusory causation is a genuine phenomenon that is observable with either a undirectional or a bidirectional rating scale, its magnitude may be overestimated when unidirectional rating scales are used.

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