Modeling the interrelationships between brain activity and trait attention measures to predict individual differences in reaction times in children during a Go/No-Go task


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Abstract

Many researchers are utilizing event-related potentials (ERPs) to better understand brain-behavior relationships across development. The present study demonstrates how structural equation modeling (SEM) techniques can be used to refine descriptions of brain-behavior relationships in a sample of neurotypical children. We developed an exploratory latent variable model in which trait measures of maturation and attention are related to neural processing and task behaviors obtained during a cued Go/No-Go task. Model findings are compared to results of traditional analysis techniques such as bivariate correlations. The data suggest that more sophisticated statistical approaches are beneficial to accurately interpreting the nature of brain-behavior relationships.HighlightsMultivariate statistics can examine a constellation of complex interrelationships.Validation of a factor structure for the Test of Everyday Attention for Children.Attention is not related to E-wave or reaction time within the latent variable model.Age predicts maturation of selective ERP components (N2, P3) and task reaction time.

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