Scores on cognitive tasks used in intelligence tests correlate positively with each other, that is, they display a positive manifold of correlations. The positive manifold is often explained by positing a dominant latent variable, the g factor, associated with a single quantitative cognitive or biological process or capacity. In this article, a new explanation of the positive manifold based on a dynamical model is proposed, in which reciprocal causation or mutualism plays a central role. It is shown that the positive manifold emerges purely by positive beneficial interactions between cognitive processes during development. A single underlying g factor plays no role in the model. The model offers explanations of important findings in intelligence research, such as the hierarchical factor structure of intelligence, the low predictability of intelligence from early childhood performance, the integration/differentiation effect, the increase in heritability of g, and the Jensen effect, and is consistent with current explanations of the Flynn effect.

After 1 year of adjuvant therapy, tamoxifen use is associated with statistically significant lower functioning in verbal memory and executive functioning, whereas exemestane use is not associated with statistically significant lower cognitive functioning in postmenopausal patients with BC. Our results accentuate the need to include assessments of cognitive effects of adjuvant endocrine treatment in long-term safety studies.

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In the standard Iowa Gambling Task (IGT), participants have to choose repeatedly from four options. Each option is characterized by a constant gain, and by the frequency and amount of a probabilistic loss. Crone and van der Molen (2004) reported that school-aged children and even adolescents show marked deficits in IGT performance. In this study, we have re-analyzed the data with a multivariate normal mixture analysis to show that these developmental changes can be explained by a shift from unidimensional to multidimensional proportional reasoning (Siegler, 1981; Jansen & van der Maas, 2002). More specifically, the results show a gradual shift with increasing age from (a) guessing with a slight tendency to consider frequency of loss to (b) focusing on frequency of loss, to (c) considering both frequency and amount of probabilistic loss. In the latter case, participants only considered options with low-frequency loss and then chose the option with the lowest amount of loss. Performance improved in a reversed task, in which punishment was placed up front and gain was delivered unexpectedly. In this reversed task, young children are guessing with already a slight tendency to consider both the frequency and amount of gain; this strategy becomes more pronounced with age. We argue that these findings have important implications for the interpretation of IGT performance, as well as for methods to analyze this performance.

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Adolescence is often described as a period of increased risk taking relative to both childhood and adulthood. This inflection in risky choice behavior has been attributed to a neurobiological imbalance between earlier developing motivational systems and later developing top-down control regions. Yet few studies have decomposed risky choice to investigate the underlying mechanisms or tracked their differential developmental trajectory. The current study uses a risk-return decomposition to more precisely assess the development of processes underlying risky choice and to link them more directly to specific neural mechanisms. This decomposition specifies the influence of changing risks (outcome variability) and changing returns (expected value) on the choices of children, adolescents, and adults in a dynamic risky choice task, the Columbia Card Task. Behaviorally, risk aversion increased across age groups, with adults uniformly risk averse and adolescents showing substantial individual differences in risk sensitivity, ranging from risk seeking to risk averse. Neurally, we observed an adolescent peak in risk-related activation in the anterior insula and dorsal medial PFC. Return sensitivity, on the other hand, increased monotonically across age groups and was associated with increased activation in the ventral medial PFC and posterior cingulate cortex with age. Our results implicate adolescence as a developmental phase of increased neural risk sensitivity. Importantly, this work shows that using a behaviorally validated decision-making framework allows a precise operationalization of key constructs underlying risky choice that inform the interpretation of results.

Advantageous decision making progressively develops into early adulthood, most specifically in complex and motivationally salient decision situations in which direct feedback on gains and losses is provided (Figner & Weber, 2011). However, the factors that underlie this developmental improvement in decision making are still not well understood. The current study therefore investigates 2 potential factors, long-term memory and working memory, by assigning a large developmental sample (7-29 years of age) to a condition with either high or low demands on long-term and working memory. The first condition featured an age-adapted version of the Iowa Gambling Task (IGT; Bechara, Damasio, Damasio, & Anderson, 1994; i.e., a noninformed situation), whereas the second condition provided an external store where explicit information on gains, losses, and probabilities per choice option was presented (i.e., an informed situation). Consistent with previous developmental IGT studies, children up to age 12 did not learn to prefer advantageous options in the noninformed condition. In contrast, all age groups learned to prefer the advantageous options in the informed conditions, although a slight developmental increase in advantageous decision making remained. These results indicate that lowering dependence on long-term and working memory improves children's advantageous decision making. The results additionally suggest that other factors, like inhibitory control processes, may play an additional role in the development of advantageous decision making.

ADHD has been associated with various forms of risky real life decision making, for example risky driving, unsafe sex and substance abuse. However, results from laboratory studies on decision making deficits in ADHD have been inconsistent, probably because of between study differences. We therefore performed a meta-regression analysis in which 37 studies (n ADHD=1175; n Control=1222) were included, containing 52 effect sizes. The overall analysis yielded a small to medium effect size (standardized mean difference=.36, p<.001, 95% CI [.22, .51]), indicating that groups with ADHD showed more risky decision making than control groups. There was a trend for a moderating influence of co-morbid Disruptive Behavior Disorders (DBD): studies including more participants with co-morbid DBD had larger effect sizes. No moderating influence of co-morbid internalizing disorders, age or task explicitness was found. These results indicate that ADHD is related to increased risky decision making in laboratory settings, which tended to be more pronounced if ADHD is accompanied by DBD. We therefore argue that risky decision making should have a more prominent role in research on the neuropsychological and -biological mechanisms of ADHD, which can be useful in ADHD assessment and intervention.