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Functional connectivity studies have demonstrated that creative thinking builds upon an interplay of multiple neural networks involving the cognitive control system. Theoretically, cognitive control has generally been discussed as the common basis underlying the positive relationship between creative thinking and intelligence. However, the literature still lacks a detailed investigation of the association patterns between cognitive control, the factors of creative thinking as measured by divergent thinking (DT) tasks, i.e., fluency and originality, and intelligence, both fluid and crystallized. In the present study, we explored these relationships at the behavioral and the neural level, based on N = 77 young adults. We focused on brain-signal complexity (BSC), parameterized by multi-scale entropy (MSE), as measured during a verbal DT and a cognitive control task. We demonstrated that MSE is a sensitive neural indicator of originality as well as inhibition. Then, we explore the relationships between MSE and factor scores indicating DT and intelligence. In a series of across-scalp analyses, we show that the overall MSE measured during a DT task, as well as MSE measured in cognitive control states, are associated with fluency and originality at specific scalp locations, but not with fluid and crystallized intelligence. The present explorative study broadens our understanding of the relationship between creative thinking, intelligence, and cognitive control from the perspective of BSC and has the potential to inspire future BSC-related theories of creative thinking.

The study of socio-cognitive abilities emerged from intelligence research, and their specificity remains controversial until today. In recent years, the psychometric structure of face cognition (FC)--a basic facet of socio-cognitive abilities--was extensively studied. In this review, we summarize and discuss the divergent psychometric structures of FC in easy and difficult tasks. While accuracy in difficult tasks was consistently shown to be face-specific, the evidence for easy tasks was inconsistent. The structure of response speed in easy tasks was mostly--but not always--unitary across object categories, including faces. Here, we compare studies to identify characteristics leading to face specificity in easy tasks. The following pattern emerges: in easy tasks, face specificity is found when modeling speed in a "single task"; however, when modeling speed across "multiple," "different" easy tasks, only a unitary factor structure is reported. In difficult tasks, however, face specificity occurs in both single task approaches and task batteries. This suggests different cognitive mechanisms behind face specificity in easy and difficult tasks. In easy tasks, face specificity relies on isolated cognitive sub-processes such as face identity recognition. In difficult tasks, face-specific and task-independent cognitive processes are employed. We propose a descriptive model and argue for FC to be integrated into common taxonomies of intelligence.

The self, like the concept of central "gravity", facilitates the processing of information that is directly relevant to the self. This phenomenon is known as the self-prioritization effect. However, it remains unclear whether the self-prioritization effect extends to the processing of emotional facial expressions. To fill this gap, we used a self-association paradigm to investigate the impact of self-relevance on the recognition of emotional facial expressions while controlling for confounding factors such as familiarity and overlearning. Using a large and diverse sample, we replicated the effect of self-relevance on face processing but found no evidence for a modulation of self-relevance on facial emotion recognition. We propose two potential theoretical explanations to account for these findings and emphasize that further research with different experimental designs and a multitasks measurement approach is needed to understand this mechanism fully. Overall, our study contributes to the literature on the parallel cognitive processing of self-relevance and facial emotion recognition, with implications for both social and cognitive psychology.

Recent research on individual differences in object cognition (OC) focused on determining how objects group together, and what type of processing lies behind the clusters--a single domain-general or multiple domain-specific processes. The expertise hypothesis suggests that all object categories are processed by the same mechanism that is responsible for differentiating visually similar objects. This ability is expected to be more specifically expressed in processing objects for which people have higher expertise. The domain-specificity hypothesis postulates that different object categories, for example, living versus nonliving objects, are processed employing different mechanisms. In the present study we aimed to study (a) how multiple objects group together in terms of individual differences; (b) the expertise hypothesis based on up-to-date statistical methods of modeling individual differences; (c) whether task difficulty influences the structure of individual differences in OC. We applied a memory task to N = 186 participants, by using multiple, theoretically chosen object categories divided into five groups--living/mobile (fish, butterflies), living/immobile (flowers, leaves), nonliving/mobile (cars, motorbikes), nonliving/immobile (houses, chairs) and faces--and report three main findings. (a) In terms of individual differences, the factor space of OC can be accounted by three factors--general OC factor along with a specific Vehicle and Face factor; (b) there is no clear evidence for the expertise hypothesis; and (c) task difficulty does not influence the OC structure. We conclude that domain-specific mechanisms in object processing cannot be dismissed.

This study investigated the adjustment behaviour of hearing aid (HA) users participating in a semi-supervised self-adjustment fine-tuning procedure for HAs. The aim was to link behaviour with the reproducibility and duration of the adjustments. Participants used a two-dimensional user interface to identify their HA gain preferences while listening to realistic sound scenes presented in a laboratory environment. The interface allowed participants to adjust amplitude (vertical axis) and spectral slope (horizontal axis) simultaneously. Participants were clustered according to their interaction with the user interface, and their search directions were analysed. Twenty older experienced HA users were invited to participate in this study. We identified four different archetypes of adjustment behaviour (curious, cautious, semi-browsing, and full-on browsing) by analysing the trace points of all measurements for each participant. Furthermore, participants used predominantly horizontal or vertical paths when searching for their preference. Neither the archetype, nor the search directions, nor the participants' technology commitment was predictive of the reproducibility or the adjustment duration. The findings suggest that enforcement of a specific adjustment behaviour or search direction is not necessary to obtain fast, reliable self-adjustments. Furthermore, no strict requirements with respect to technology commitment are necessary. [ABSTRACT FROM AUTHOR]

People remember what they deem important. In line with research suggesting that lower-class (vs. higher class) individuals spontaneously appraise other people as more relevant, we show that social class is associated with the habitual use of face memory. We find that lower-class (vs. higher class) participants exhibit better incidental memory for faces (i.e., spontaneous memory for faces they had not been instructed to memorize; Studies 1 and 2). No social-class differences emerge for faces participants are instructed to learn (Study 2), suggesting that this pattern reflects class-based relevance appraisals rather than memory ability. Study 3 extends our findings to eyewitness identification. Lower-class (vs. higher-class) participants' eyewitness accuracy is less impacted by the explicit relevance of a target (clearly relevant thief vs. incidental bystander). Integrative data analysis shows a robust negative association between social class and spontaneous face memory. Preregistration (Studies 1 and 3) and cross-cultural replication (Study 2) further strengthen the results. [ABSTRACT FROM AUTHOR]