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Understanding genetic, neurophysiological, and experiential influences on the development of executive functioning: the need for developmental models

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Abstract Flexibility is a cornerstone of adaptive behavior and is made possible by a family of processes referred to collectively as executive functions. Executive functions vary in efficacy from individual to individual and also across developmental time. Infants and young children, for example, have difficulty flexibly adapting their behavior, and often repeat actions that are no longer appropriate. And although older children do not typically make such striking errors, they have more difficulty exercising control than adolescents and adults. Such developmental variability parallels (at least in some respects) inter‐individual variability in executive functions. Individuals who suffer damage or dysfunction in regions of the prefrontal cortex, for example, often experience difficulty in flexibly adapting their behavior to changes in context. As well, genetic differences between individuals are strongly associated with differences in executive control. Parallels between developmental and inter‐individual variability suggest hypotheses about possible mechanisms underlying the development of executive functions but carry risks when interpreted improperly. Overcoming these pitfalls will require mechanistic characterizations of executive functioning that are more deeply rooted in developmental principles. Copyright © 2010 John Wiley & Sons, Ltd. This article is categorized under: Psychology > Brain Function and Dysfunction Psychology > Development and Aging

A selection of tasks commonly used to study executive functioning early in development. (a) In the A not B task, 7‐ to 12‐month‐old infants retrieve a hidden toy from one location (A) and then watch as the toy is hidden at a second location (B). Correct retrieval requires that infants actively maintain the recent hiding location and inhibit searching at A. (b) In the Dimensional Change Card Sort, preschool‐aged children sort bivalent cards one way (e.g. by color) and then are instructed to switch and sort the cards in a new way (i.e. by shape). Correct switching requires that children actively maintain the new rule and inhibit attention to previously relevant stimulus features. (c) In the Simon task, children respond to the identity but not the spatial location of the stimulus. Correct responses demand that children inhibit irrelevant stimulus–response mappings. (d) Age‐related decrease in interference effects in the Simon task adopted from Davidson et al.7 illustrates developmental changes commonly observed in executive functioning tasks. Note, one group of 6‐year‐olds were administered a protocol designed for young children, and a second group were administered a protocol designed for older children and adults.

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Neural network model of Dimensional Change Card Sort task performance. Activity presented to various input units as shown in the bottom 5 rows of the figure, propagates through the network by means of feedforward connections and establishes a bias to sort by features that are deemed relevant in pre‐switch trials. The network's ability to overcome this bias and correctly switch in post‐switch trials depends on how well prefrontal cortex (PFC) units actively maintain a representation of the post‐switch sorting rule. The model provides a mechanistic account of how inhibitory control is achieved and how the development of PFC leads to improvements in EF. R = red, B = blue, T = truck, F = flower, C = color, S = shape.

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Cross‐twin correlations for gray and white measures in neuroanatomic regions of interest. Correlations for monozygotic (MZ) and dizygotic (DZ) twins are given, as are correlations for younger (MZY, DZY) and older (MZO, DZO) twin pairs. In general, the data reveal increasing correlations for MZ twins and decreasing correlations for DZ twins over time, as is predicted by gene–environment interaction models of development.

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Age‐related changes in heritability of gray matter thickness for younger and older children. Columns (a) and (b) show areas that are significantly heritable for younger (a) and older (b) children. Column (c) is a map of differences in heritability, created by subtracting values of the younger group from those of the older group. Arrows indicate regions where heritability changed over development, which includes increases in the heritability of thickness of dorsolateral prefrontal and posterior parietal cortices (see Ref 61, figure 5, p. 170).

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The executive control network as revealed by switching. (a) Brain regions activated by switching include dorsolateral prefrontal cortex, inferior frontal junction, dorsal pre‐motor cortex, anterior cingulate cortex/pre‐supplementary motor area, anterior insula, posterior parietal cortex, and thalamus. Signal timecourses extracted from regions within the network show greater temporal coupling (b) than regions that fall outside the network (c), suggesting that executive functioning is not localized but emerges out of the interaction of a distributed set of brain regions.

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Brain structures associated with executive functioning in humans along: (a) lateral and (b) medial surfaces. 1, Superior frontal gyrus; 2, superior frontal sulcus; 3, middle frontal gyrus; 4, inferior frontal sulcus; 5, inferior frontal gyrus; 5′, inferior frontal gyrus, pars triangularis; 5′′, inferior frontal gyrus, pars opercularis; 6, superior parietal lobule; 7, intraparietal sulcus; 8, anterior cingulate cortex; 9, cingulate sulcus; 10, central sulcus (note: this structure is not commonly associated with EF, but is identified only as an important landmark); 11, anterior insular cortex; and 12, thalamus.

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