Abstract
From the genetic side, giftedness in cognitive development is the result of contribution of many common genetic variants of small effect size, so called polygenicity (Spain et al., 2016). From the environmental side, educationalists have argued for the importance of the environment for sustaining early potential in children, showing that bright poor children are held back in their subsequent development (Feinstein, 2003a). Such correlational data need to be complemented by mechanistic models showing how gifted development results from the respective genetic and environmental influences. A neurocomputational model of cognitive development is presented, using artificial neural networks to simulate the development of a population of children. Variability was produced by many small differences in neurocomputational parameters each influenced by multiple artificial genes, instantiating a polygenic model, and by variations in the level of stimulation from the environment. The simulations captured several key empirical phenomena, including the non-linearity of developmental trajectories, asymmetries in the characteristics of the upper and lower tails of the population distribution, and the potential of poor environments to hold back bright children. At a computational level, ‘gifted’ networks tended to have higher capacity, higher plasticity, less noisy neural processing, a lower impact of regressive events, and a richer environment. However, individual instances presented heterogeneous contributions of these neurocomputational factors, suggesting giftedness has diverse causes.
Highlights
The causes of giftedness in cognitive or physical abilities are complex, involving both genetic and environmental contributions (Sternberg & Davidson, 2005)
The upper tail appears to be driven by the same genetic influences that operate throughout the rest of the population distribution, with the discontinuity at the lower extreme being the sole exception (Shakeshaft et al, 2015)
It has been argued that the requirement for many beneficial circumstances to align points to a multiplicative model of influences on giftedness, where the absence of any one would scupper the gifted outcome (Lykken, 2006)
Summary
The causes of giftedness in cognitive or physical abilities are complex, involving both genetic and environmental contributions (Sternberg & Davidson, 2005). Evidence from twin studies in several countries suggested a genetic contribution to cognitive performance in the high range (Haworth et al, 2009). In these data, genetic influences explained 50% of the variance in those performing in the top 15% of population distributions. Molecular genetics using genome wide association (GWA) analyses suggest that the causes of low performance in the bottom tail of the distribution and high performance in the upper tail may be different, at least for intelligence. The wider picture is that genetic contributions to intelligence stem from many common genetic variations each of small effect, known as the ‘polygenic’ model
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