Neurophysiological variability masks differences in functional neuroanatomical networks and their effectiveness to modulate response inhibition between children and adults.

Abstract

Executive functions are well-known to undergo developmental changes from childhood to adulthood. Considerable efforts have been made to elucidate the affected system neurophysiological mechanisms. But while it is well-known that developmental changes affect intra-individual variability, this potential bias has largely been neglected when investigating the neurophysiology underlying developmental differences between children and adults. We hypothesize that due to differences in intra-individual variability of neural processes between children and adults, reliable group differences will only be evident after accounting for intra-individual variability in neurophysiological processes. We, therefore, investigate response-inhibition processes as an important instance of executive control in children (between 10 and 14years) and adults (between 20 and 29years) and decompose EEG data on the basis of the latency and temporal variability. This was combined with source localization. Children showed more impulsive behavior than adults. Importantly, a reliable match between the neurophysiological and behavioral data could only be found when accounting for intra-individual variability in the EEG data. These decomposed data showed that children and adults use similar neurophysiological mechanisms at the response selection level to accomplish inhibitory control, but seem to engage different neuroanatomical structures to do so according to source localization results: In adults, these processes were related to the medial frontal cortex. In children, the same processes were reflected in a shift of the scalp topography and related to the superior parietal cortex. These shifts in neural networks were associated with lower effectiveness in exerting inhibitory control. However, these differences in the functional neuroanatomical architecture can only be seen when intra-individual variability is taken into account.