Developmental Traits of Impulse Control Behavior in School Children under Controlled Attention, Motor Function, and Perception

This research surveyed the characteristics of the developmental traits of impulse control behavior in children through parent-report questionnaires. After matching for gender and attention behavior, as well as controlling for variables (motor and perception) which might confound impulse control, 710 participants (355 girls and 355 boys; grade, 1–5; age, 7–12 years) were recruited from a database of 1763 children. Results demonstrated that there was a significant difference between grade 1 and grade 5 in impulse control. Conversely, no significant differences were found when comparing other grades. The present findings indicate that a striking development of impulse control occurs from grade 4 to 5. Moreover, the plateau of impulse control development from grade 1 to 4 implies that a long transition period is needed to prepare children to develop future impulse control. In conclusion, the age-dependent maturation associated with stage-wise development is a critical characteristic of impulse control development in school age children. Further discussions are made regarding this characteristic, such as from the perspective of frontal lobe development.

Socio-economic Status and Attention Ability as Predictors of Early Geometry Skills of 60-72-Month-Old Children

The aims of this study are investigating the attention ability and geometry skills of 60-72-month-old children according to the socio-economic status and determining whether the attention ability significantly predicts the geometry skill when the socio-economic status is controlled. The accessible population of the research in the relational screening model consisted of 60-72-month-old children studying in Afyonkarahisar kindergartens and nursery classes in the 2018-2019 academic year. The sample of the study was randomly selected 310 children among 60-72-month-old children attending high, medium and low socio-economic status schools, volunteering to participate in the study. The "General Information Form" was used to collect data on children and their families in the study while the " Attention Gathering Skills Test for Five-year Old Children FTF-K" developed by Raatz and Möhling in 1971 and adapted by Gözüm (2017) to determine the attention status of children, and the "Early Geometry Skill Test” developed by Sezer (2015) to measure children's geometry skills were used. Chi-Square, One-Way ANOVA and Hierarchical Regression tests were used to analyze the data obtained from the research. In the light of the findings, it was found out that children's attention skills and early geometry skills differed according to socio-economic status and when the socio-economic status was controlled, attention ability was a positive and significant predictor of early geometry skills of 60-72-month-old children.

The relationship of physical fitness and motor competence with behavioral and neuroelectric indices of attention in preschool children

The present study examined the associations of physical fitness and motorcompetence with P3 and alpha desynchronization (ERD), two neuroelectric indices ofbrain development underlying controlled attention, in 4-6 year-old preschool children. Allparticipants completed physical fitness and motor competence test batteries and anauditory oddball task while electroencephalogram (EEG) was recorded. Resultsrevealed that increased muscular power, muscular endurance, physical fitness, andmotor competence were associated better attentional task performance. Analysis onneuroelectric indices showed that muscular endurance was related to increased P3amplitude, while the increases in physical fitness and motor competence wereassociated with greater upper alpha (10-12 Hz) ERD following the stimulus evaluationand response selection. Further, the negative associations of physical fitness and motorcompetence with task response time were mediated by the upper alpha ERD. Thesefindings highlight the importance of early childhood motor competence and physicalfitness, especially muscular endurance, to neurocognitive function.

The Relationship Between Childhood Stress and Distinct Stages of Dynamic Behavior Monitoring in Adults: Neural and Behavioral Correlates

Childhood adversity is a major risk factor for emotional and cognitive disorders later in adulthood. Behavior monitoring, one of the most important components of cognitive control, plays a crucial role in flexible interaction with the environment. Here, we test a novel conceptual model discriminating between two distinct dimensions of childhood adversity (i.e., deprivation and threat) and examine their relations to dynamic stages of behavior monitoring. Sixty young healthy adults participated in this study using event-related potentials (ERPs) and the dynamic stages of behavior monitoring including response inhibition, error detection, and post-error adjustments were investigated in a classical Go/NoGo task. Multiple regression analyses revealed that participants with higher severity of childhood adversity recruited more controlled attention, as indicated by larger (more negative) conflict detection-related NoGo-N2 amplitudes and larger (more negative) error detection-related ERN amplitudes. Higher severity of childhood abuse (an indicator of threat) was related to smaller (less positive) error appraisal-related Pe amplitudes on the neural level and subsequently lower post-error accuracy on the behavioral level. These results suggested that prefrontal-supported controlled attention is influenced by universal adversity in childhood while the error-related behavioral adjustment is mainly affected by childhood abuse, indicating the dimensions of deprivation and threat are at least partially distinct.

A New Memory Perspective on the Sentence Comprehension Deficits of School-Age Children With Developmental Language Disorder: Implications for Theory, Assessment, and Intervention

Purpose The nature of the relationship between memory and sentence comprehension in school-age children with developmental language disorder (DLD) has been unclear. We present a novel perspective that highlights the relational influences of fluid intelligence, controlled attention, working memory (WM), and long-term memory (LTM) on sentence comprehension in children with and without DLD. This perspective has new and important implications for theory, assessment, and intervention. Method We review a large-scale study of children with and without DLD that focused on the connections between cognition, memory, and sentence comprehension. We also summarize a new model of these relationships. Results Our new model suggests that WM serves as a conduit through which syntactic knowledge in LTM, controlled attention, and general pattern recognition indirectly influence sentence comprehension in both children with DLD and typically developing children. For typically developing children, language-based LTM and fluid intelligence indirectly influence sentence comprehension. However, for children with DLD, controlled attention plays a larger indirect role. Conclusions WM plays a key role in children's ability to apply their syntactic knowledge when comprehending canonical and noncanonical sentences. Our new model has important implications for the assessment of sentence comprehension and for the treatment of larger sentence comprehension deficits.

Testing the automaticity of an attentional bias towards predictive cues in human associative learning

It is well established that associative learning, such as learning new cue–outcome pairings, produces changes in attention: cues that are good predictors of relevant outcomes become prioritised compared with those that are non-predictive or redundant. However, there is controversy about whether such a learnt attentional bias results from a controlled orientation of attention, or whether it can be involuntary in nature. In three experiments, participants learned that cues of certain colours were predictive or non-predictive, and we assessed attention to cues using a dot-probe task. On dot-probe trials, participants were instructed to control attention by orienting towards a cue of a certain shape (target), while trying to ignore another cue (distractor). Although the colours of the cues were critical for the associative learning task, they were irrelevant for the dot-probe task. The results show that, even though participants’ controlled attention was focused on the target shape (as evident in response times and accuracy data), response times to the probe were slower (Experiments 1 and 2) and error rates were higher (Experiments 2 and 3) when the distractor was of a (previously) predictive colour. These data suggest that attention was captured involuntarily by the predictive value of the distractor, despite this being counterproductive to the task goal.

Quasi-compositional mapping from form to meaning: a neural network-based approach to capturing neural responses during human language comprehension

We argue that natural language can be usefully described as quasi-compositional and we suggest that deep learning-based neural language models bear long-term promise to capture how language conveys meaning. We also note that a successful account of human language processing should explain both the outcome of the comprehension process and the continuous internal processes underlying this performance. These points motivate our discussion of a neural network model of sentence comprehension, the Sentence Gestalt model, which we have used to account for the N400 component of the event-related brain potential (ERP), which tracks meaning processing as it happens in real time. The model, which shares features with recent deep learning-based language models, simulates N400 amplitude as the automatic update of a probabilistic representation of the situation or event described by the sentence, corresponding to a temporal difference learning signal at the level of meaning. We suggest that this process happens relatively automatically, and that sometimes a more-controlled attention-dependent process is necessary for successful comprehension, which may be reflected in the subsequent P600 ERP component. We relate this account to current deep learning models as well as classic linguistic theory, and use it to illustrate a domain general perspective on some specific linguistic operations postulated based on compositional analyses of natural language. This article is part of the theme issue ‘Towards mechanistic models of meaning composition’.

Initial Impressions of Others

“Initial impressions” join personality and social psychology like no other field of study—“personality” because impressions are about personalities and perceivers’ personalities affect these impressions; and “social” because social cognitive processes influence impression formation and sociocultural contexts have major effects on impressions. How people describe others is reviewed: terms used, how descriptions reveal theories about others, and importance of types and categories. Research on social cognitive processes underlying these descriptions is highlighted: automatic and controlled attention, effects of primes and their dependence on contexts, acquisition of valence, spontaneous inferences, and interplay of automatic and control processes. Accuracy of initial impressions is examined, as are what accuracy means and motivated biases and distortions. Perceiver features and relations between targets and perceivers are reviewed. Frameworks for understanding explanations, as distinct from descriptions, are detailed: attribution theory, theory of mind, and simulation theory, including synchrony and the role of embodied cognition and metaphor.