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Ferrer, E., & McArdle, J. J. (2010). Longitudinal Modeling of Developmental Changes in Psychological Research.
Current Directions in Psychological Science, 19(3), 149-154.
In this article we provide a review of recent advances in longitudinal models for multivariate change. We first claim the need for dynamic modeling approaches as a way to evaluate psychological theories. We then describe one such approach, latent change score (LCS) models, and illustrate their utility with a summary of research findings in various areas of psychological science. We then highlight the most prominent features of LCS models. We conclude the article with suggestions for future research on multivariate models of change that can enhance our understanding of psychological science.
Johnson, W. (2010). Understanding the Genetics of Intelligence: Can Height Help? Can Corn Oil?
Current Directions in Psychological Science, 19(3), 177-182.
Although the subject is controversial, identifying the specific genes that contribute to general cognitive ability (GCA) has seemed to have good prospects, at least among psychological traits. GCA is reliably and validly measured and strongly heritable, and it shows genetically mediated physiological associations and developmental stability. To date, however, results have been disappointing. Human height shows these measurement characteristics even more strongly than GCA, yet data have indicated that no individual gene has more than trivial effects and this is also true for corn oil. The potential for environmental trigger of genetic expression, long recognized in evolutionary and developmental genetics, as applied to these seemingly disparate traits, can help us to understand the apparent contradiction between the heritability of intelligence and other psychological traits and the difficulty of identifying specific genetic effects.
Lavie, N. (2010). Attention, Distraction, and Cognitive Control Under Load.
Current Directions in Psychological Science, 19(3), 143-148.
The extent to which people can focus attention in the face of irrelevant distractions has been shown to critically depend on the level and type of information load involved in their current task. The ability to focus attention improves under task conditions of high perceptual load but deteriorates under conditions of high load on cognitive control processes such as working memory. I review recent research on the effects of load on visual awareness and brain activity, including changing effects over the life span, and I outline the consequences for distraction and inattention in daily life and in clinical populations.
DeYoung, C. G., Hirsh, J. B., Shane, M. S., Papademetris, X., Rajeevan, N., & Gray, J. R. (2010). Testing Predictions From Personality Neuroscience: Brain Structure and the Big Five.
Psychological Science, 21(6), 820-828.
We used a new theory of the biological basis of the Big Five personality traits to generate hypotheses about the association of each trait with the volume of different brain regions. Controlling for age, sex, and whole-brain volume, results from structural magnetic resonance imaging of 116 healthy adults supported our hypotheses for four of the five traits: Extraversion, Neuroticism, Agreeableness, and Conscientiousness. Extraversion covaried with volume of medial orbitofrontal cortex, a brain region involved in processing reward information. Neuroticism covaried with volume of brain regions associated with threat, punishment, and negative affect. Agreeableness covaried with volume in regions that process information about the intentions and mental states of other individuals. Conscientiousness covaried with volume in lateral prefrontal cortex, a region involved in planning and the voluntary control of behavior. These findings support our biologically based, explanatory model of the Big Five and demonstrate the potential of personality neuroscience (i.e., the systematic study of individual differences in personality using neuroscience methods) as a discipline
Goldstein, M. H., Waterfall, H. R., Lotem, A., Halpern, J. Y., Schwade, J. A., Onnis, L., & Edelman, S. (2010). General cognitive principles for learning structure in time and space.
Trends in Cognitive Sciences, 14(6), 249-258.
An understanding of how the human brain produces cognition ultimately depends on knowledge of large-scale brain organization. Although it has long been assumed that cognitive functions are attributable to the isolated operations of single brain areas, we demonstrate that the weight of evidence has now shifted in support of the view that cognition results from the dynamic interactions of distributed brain areas operating in large-scale networks. We review current research on structural and functional brain organization, and argue that the emerging science of large-scale brain networks provides a coherent framework for understanding of cognition. Critically, this framework allows a principled exploration of how cognitive functions emerge from, and are constrained by, core structural and functional networks of the brain.
Klingberg, T. (2010). Trainin and plasticity of working memory.
Trends in Cognitive Sciences, 14 (7), 317-324
Working memory (WM) capacity predicts performance in a wide range of cognitive tasks. Although WM capacity has been viewed as a constant trait, recent studies suggest that it can be improved by adaptive and extended training. This training is associated with changes in brain activity in frontal and parietal cortex and basal ganglia, as well as changes in dopamine receptor density. Transfer of the training effects to non-trained WM tasks is consistent with the notion of training-induced plasticity in a common neural network for WM. The observed training effects suggest that WM training could be used as a remediating intervention for individuals for whom low WM capacity is a limiting factor for academic performance or in everyday life.
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