The role of controlled attention and selective encoding for kindergarteners' learning

Selectivity in encoding, aspects of attentional control and their contribution to learning performance were explored in a sample of preschoolers. While the children are performing a learning task, their encoding of relevant and attention towards irrelevant information was recorded through an eye-tracking device. Recognition of target items was used as measure of learning outcome, and individual differences in resistance to interference and inhibition of attention to task-irrelevant stimuli (i.e. distractibility) were used as measures of executive control of attention. Results indicated well-developed selectivity during encoding in young children. Recognition performance was related to selective encoding and aspects of attentional control, explaining individual differences in learning. Copyright © 2011 John Wiley & Sons, Ltd.

Metacognitive monitoring and control in elementary school children: Their interrelations and their role for test performance

Contemporary models of self-regulated learning emphasize the role of distal motivational factors for student's achievement, on the one side, and the proximal role of metacognitive monitoring and control for learning and test outcomes, on the other side. In the present study, two larger samples of elementary school children (9- and 11-year-olds) were included and their mastery-oriented motivation, metacognitive monitoring and control skills were integrated into structural equation models testing and comparing the relative impact of these different constituents for self-regulated learning. For one, results indicate that the factorial structure of monitoring, control and mastery motivation was invariant across the two age groups. Of specific interest was the finding that there were age-dependent structural links between monitoring, control, and test performance (closer links in the older compared to the younger children), with high confidence yielding a direct and positive effect on test performance and a direct and negative effect on adequate control behavior in the achievement test. Mastery-oriented motivation was not found to be substantially associated with monitoring (confidence), control (detection and correction of errors), or test performance underlining the importance of proximal, metacognitive factors for test performance in elementary school children.

Executive functioning, metacognition, and self-perceived competence in elementary school children: An explorative study on their interrelations and their role for school achievement

In the present study, associations between executive functioning, metacognition, and self-perceived competence in the context of early academic outcomes were examined. A total of 209 children attending first grade were initially assessed in terms of their executive functioning and academic self-concept. One year later, children’s executive functioning, academic self-concept, metacognitive monitoring and control, as well as their achievement in mathematics and literacy were evaluated. Structural equation modeling revealed that executive functioning was significantly related to metacognitive control, both cross-sectionally and longitudinally, and that self-concept was substantially associated with metacognitive monitoring, both cross-sectionally and longitudinally. Individual differences in executive functioning and metacognitive control were significantly related to academic outcomes, with metacognitive control appearing to yield a more circumscribed influence on academic outcomes (only literacy) compared to executive functioning (literacy and mathematics).

Factors of Home Dream Recall and Nightmare Frequency in a Non-Student Sample

Home dream recall frequencies and nightmare frequencies show great inter-individual differences. Most of the studies trying to explain these differences, however, studied young participants, so these findings might not be true for persons older than 25 years. The present study investigated the relationship between dream recall, nightmare frequency, age, gender, sleep parameters, stress, and subjective health in a community-based sample (N = 455) with a mean age of about 55 years. Some of the factors that have been shown to be associated with dream recall and nightmare frequency were also associated with these variables in non-student sample like frequency of nocturnal awakenings, current stress, and tiredness during the day. We were not able to replicate the effect of sex-role orientation on dream recall and nightmare frequency, supporting the idea that age might mediate the effect of daytime variables on dream recall and nightmare frequency. As nightmare frequency was related to sleep quality, stress, health problems, and tiredness during the day, it would be desirable that clinicians include a question about nightmares in their anamneses.

Performance on auditory and visual temporal informationprocessing is related to psychometric intelligence

The present study investigated the relationship between psychometric intelligence and temporal resolution power (TRP) as simultaneously assessed by auditory and visual psychophysical timing tasks. In addition, three different theoretical models of the functional relationship between TRP and psychometric intelligence as assessed by means of the Adaptive Matrices Test (AMT) were developed. To test the validity of these models, structural equation modeling was applied. Empirical data supported a hierarchical model that assumed auditory and visual modality-specific temporal processing at a first level and amodal temporal processing at a second level. This second-order latent variable was substantially correlated with psychometric intelligence. Therefore, the relationship between psychometric intelligence and psychophysical timing performance can be explained best by a hierarchical model of temporal information processing.

Impartiality in humans is predicted by brain structure of dorsomedial prefrontal cortex.

The moral force of impartiality (i.e. the equal treatment of all human beings) is imperative for providing justice and fairness. Yet, in reality many people become partial during intergroup interactions; they demonstrate a preferential treatment of ingroup members and a discriminatory treatment of outgroup members. Some people, however, do not show this intergroup bias. The underlying sources of these inter-individual differences are poorly understood. Here we demonstrate that the larger the gray matter volume and thickness of the dorsomedial prefrontal cortex (DMPFC), the more individuals in the role of an uninvolved third-party impartially punish outgroup and ingroup perpetrators. Moreover, we show evidence for a possible mechanism that explains the impact of DMPFC's gray matter volume on impartiality, namely perspective-taking. Large gray matter volume of DMPFC seems to facilitate equal perspective-taking of all sides, which in turn leads to impartial behavior. This is the first evidence demonstrating that brain structure of the DMPFC constitutes an important source underlying an individual's propensity for impartiality.

A neural marker of costly punishment behavior

Human readiness to incur personal costs to punish norm violators is a key force in the maintenance of social norms. The willingness to punish is, however, characterized by vast individual heterogeneity that is poorly understood. In fact, this heterogeneity has so far defied explanations in terms of individual-level demographic or psychological variables. Here, we use resting electroencephalography, a stable measure of individual differences in cortical activity, to show that a highly specific neural marker--baseline cortical activity in the right prefrontal cortex--predicts individuals' punishment behavior. The analysis of task-independent individual variation in cortical baseline activity provides a new window into the neurobiology of decision making by bringing dispositional neural markers to the forefront of the analysis.

Self-control in social decision making: A neurobiological perspective

Self-control is defined as the process in which thoughts, emotions, or prepotent responses are inhibited to efficiently enact a more focal goal. Self-control not only allows for more adaptive individual decision making but also promotes adaptive social decision making. In this chapter, we examine a burgeoning area of interdisciplinary research: the neuroscience of self-control in social decision making. We examine research on self-control in complex social contexts examined from a social neuroscience perspective. We review correlational evidence from neuroimaging studies and causal evidence from neuromodulation studies (i.e., brain stimulation). We specifically highlight research that shows that self-control involves the lateral prefrontal cortex (PFC) across a number of social domains and behaviors. Research has also begun to directly integrate nonsocial with social forms of self-control, showing that the basic neurobiological processes involved in stopping a motor response appear to be involved in social contexts that require self-control. Further, neural traits, such as baseline activation in the lateral PFC, can explain sources of individual differences in self-control capacity. We explore whether techniques that change brain functioning could target neural mechanisms related to self-control capacity to potentially enhance self-control in social behavior. Finally, we discuss several research questions ripe for examination. We broadly suggest that future research can now turn to exploring how neural traits and situational affordances interact to impact self-control in social decision making in order to continue to elucidate the processes that allow people to maintain and realize stable goals in a dynamic and often uncertain social environment.

A Longitudinal Assessment of Sleep Timing, Circadian Phase, and Phase Angle of Entrainment across Human Adolescence

The aim of this descriptive analysis was to examine sleep timing, circadian phase, and phase angle of entrainment across adolescence in a longitudinal study design. Ninety-four adolescents participated; 38 (21 boys) were 9-10 years ("younger cohort") and 56 (30 boys) were 15-16 years ("older cohort") at the baseline assessment. Participants completed a baseline and then follow-up assessments approximately every six months for 2.5 years. At each assessment, participants wore a wrist actigraph for at least one week at home to measure self-selected sleep timing before salivary dim light melatonin onset (DLMO) phase - a marker of the circadian timing system - was measured in the laboratory. Weekday and weekend sleep onset and offset and weekend-weekday differences were derived from actigraphy. Phase angles were the time durations from DLMO to weekday sleep onset and offset times. Each cohort showed later sleep onset (weekend and weekday), later weekend sleep offset, and later DLMO with age. Weekday sleep offset shifted earlier with age in the younger cohort and later in the older cohort after age 17. Weekend-weekday sleep offset differences increased with age in the younger cohort and decreased in the older cohort after age 17. DLMO to sleep offset phase angle narrowed with age in the younger cohort and became broader in the older cohort. The older cohort had a wider sleep onset phase angle compared to the younger cohort; however, an age-related phase angle increase was seen in the younger cohort only. Individual differences were seen in these developmental trajectories. This descriptive study indicated that circadian phase and self-selected sleep delayed across adolescence, though school-day sleep offset advanced until no longer in high school, whereupon offset was later. Phase angle changes are described as an interaction of developmental changes in sleep regulation interacting with psychosocial factors (e.g., bedtime autonomy)

Why Some People Discount More than Others: Baseline Activation in the Dorsal PFC Mediates the Link between COMT Genotype and Impatient Choice

Individuals differ widely in how steeply they discount future rewards. The sources of these stable individual differences in delay discounting (DD) are largely unknown. One candidate is the COMT Val158Met polymorphism, known to modulate prefrontal dopamine levels and affect DD. To identify possible neural mechanisms by which this polymorphism may contribute to stable individual DD differences, we measured 73 participants' neural baseline activation using resting electroencephalogram (EEG). Such neural baseline activation measures are highly heritable and stable over time, thus an ideal endophenotype candidate to explain how genes may influence behavior via individual differences in neural function. After EEG-recording, participants made a series of incentive-compatible intertemporal choices to determine the steepness of their DD. We found that COMT significantly affected DD and that this effect was mediated by baseline activation level in the left dorsal prefrontal cortex (DPFC): (i) COMT had a significant effect on DD such that the number of Val alleles was positively correlated with steeper DD (higher numbers of Val alleles means greater COMT activity and thus lower dopamine levels). (ii) A whole-brain search identified a cluster in left DPFC where baseline activation was correlated with DD; lower activation was associated with steeper DD. (iii) COMT had a significant effect on the baseline activation level in this left DPFC cluster such that a higher number of Val alleles was associated with lower baseline activation. (iv) The effect of COMT on DD was explained by the mediating effect of neural baseline activation in the left DPFC cluster. Our study thus establishes baseline activation level in left DPFC as salient neural signature in the form of an endophenotype that mediates the link between COMT and DD.

Functional brain network efficiency predicts intelligence

The neuronal causes of individual differences in mental abilities such as intelligence are complex and profoundly important. Understanding these abilities has the potential to facilitate their enhancement. The purpose of this study was to identify the functional brain network characteristics and their relation to psychometric intelligence. In particular, we examined whether the functional network exhibits efficient small-world network attributes (high clustering and short path length) and whether these small-world network parameters are associated with intellectual performance. High-density resting state electroencephalography (EEG) was recorded in 74 healthy subjects to analyze graph-theoretical functional network characteristics at an intracortical level. Ravens advanced progressive matrices were used to assess intelligence. We found that the clustering coefficient and path length of the functional network are strongly related to intelligence. Thus, the more intelligent the subjects are the more the functional brain network resembles a small-world network. We further identified the parietal cortex as a main hub of this resting state network as indicated by increased degree centrality that is associated with higher intelligence. Taken together, this is the first study that substantiates the neural efficiency hypothesis as well as the Parieto-Frontal Integration Theory (P-FIT) of intelligence in the context of functional brain network characteristics. These theories are currently the most established intelligence theories in neuroscience. Our findings revealed robust evidence of an efficiently organized resting state functional brain network for highly productive cognitions.

Tonic activity level in the right prefrontal cortex predicts individuals' risk taking

Human risk taking is characterized by a large amount of individual heterogeneity. In this study, we applied resting-state electroencephalography, which captures stable individual differences in neural activity, before subjects performed a risk-taking task. Using a source-localization technique, we found that the baseline cortical activity in the right prefrontal cortex predicts individual risk-taking behavior. Individuals with higher baseline cortical activity in this brain area display more risk aversion than do other individuals. This finding demonstrates that neural characteristics that are stable over time can predict a highly complex behavior such as risk-taking behavior and furthermore suggests that hypoactivity in the right prefrontal cortex might serve as a dispositional indicator of lower regulatory abilities, which is expressed in greater risk-taking behavior.

Functional connectivity in BOLD and CBF data: similarity and reliability of resting brain networks

Resting-state functional connectivity (FC) fMRI (rs-fcMRI) offers an appealing approach to mapping the brain's intrinsic functional organization. Blood oxygen level dependent (BOLD) and arterial spin labeling (ASL) are the two main rs-fcMRI approaches to assess alterations in brain networks associated with individual differences, behavior and psychopathology. While the BOLD signal is stronger with a higher temporal resolution, ASL provides quantitative, direct measures of the physiology and metabolism of specific networks. This study systematically investigated the similarity and reliability of resting brain networks (RBNs) in BOLD and ASL. A 2×2×2 factorial design was employed where each subject underwent repeated BOLD and ASL rs-fcMRI scans on two occasions on two MRI scanners respectively. Both independent and joint FC analyses revealed common RBNs in ASL and BOLD rs-fcMRI with a moderate to high level of spatial overlap, verified by Dice Similarity Coefficients. Test-retest analyses indicated more reliable spatial network patterns in BOLD (average modal Intraclass Correlation Coefficients: 0.905±0.033 between-sessions; 0.885±0.052 between-scanners) than ASL (0.545±0.048; 0.575±0.059). Nevertheless, ASL provided highly reproducible (0.955±0.021; 0.970±0.011) network-specific CBF measurements. Moreover, we observed positive correlations between regional CBF and FC in core areas of all RBNs indicating a relationship between network connectivity and its baseline metabolism. Taken together, the combination of ASL and BOLD rs-fcMRI provides a powerful tool for characterizing the spatiotemporal and quantitative properties of RBNs. These findings pave the way for future BOLD and ASL rs-fcMRI studies in clinical populations that are carried out across time and scanners.

Relations among fluid intelligence, sensory discrimination and working memory in middle to late childhood – A latent variable approach

Two factors that have been suggested as key in explaining individual differences in fluid intelligence are working memory and sensory discrimination ability. A latent variable approach was used to explore the relative contributions of these two variables to individual differences in fluid intelligence in middle to late childhood. A sample of 263 children aged 7–12 years was examined. Correlational analyses showed that general discrimination ability (GDA)and working memory (WM) were related to each other and to fluid intelligence. Structural equation modeling showed that within both younger and older age groups and the sample as a whole, the relation between GDA and fluid intelligence could be accounted for by WM. While WM was able to predict variance in fluid intelligence above and beyond GDA, GDA was not able to explain significant amounts of variance in fluid intelligence, either in the whole sample or within the younger or older age group. We concluded that compared to GDA, WM should be considered the better predictor of individual differences in fluid intelligence in childhood. WM and fluid intelligence, while not being separable in middle childhood, develop at different rates, becoming more separable with age.