Given their unique connectivity, a primary function of brain networks must be to transfer and integrate information. Therefore, the way in which information is integrated by individual nodes of the network may be an informative aspect of cognitive processing. Here we present a method inspired by telecommunications research that utilizes time–frequency fluctuations of neural activity to infer how information is integrated by individual nodes of the network. We use a queueing theoretical model to interpret empirical data in terms of information processing and integration. In particular, we demonstrate, in participants aged from 6 to 41 years, that the well-known face inversion phenomenon may be explained in terms of information integration. Our model suggests that inverted faces may be associated with shorter and more frequent neural integrative stages, indicating fractured processing and consistent with the notion that inverted faces are perceived by parts. Conversely, our model suggests that upright faces may be associated with a smaller number of sustained episodes of integration, indicating more involved processing, akin to holistic and configural processing. These differences in how upright and inverted faces are processed became more pronounced during development, indicating a gradual specialization for face perception. These effects were robustly expressed in the right fusiform gyrus (all groups), as well as right parahippocampal gyrus (children and adolescents only) and left inferior temporal cortex (adults only).

The specialness of faces is seen in the face inversion effect, which disrupts the configural, but not the analytic, processing of faces. Mooney faces, which are processed holistically, allowed us to determine the contribution of holistic processing to the face inversion effect. As inverted Mooney faces are difficult to recognize as faces, we also included an intermediary training period for Mooney face recognition for half of the subjects. Early face-sensitive ERPs (N170 and P1) and P2 were measured. Behavioral data showed an increase in correct responses to inverted and upright Mooney faces after the learning phase for the experimental group. No effects were seen on P1. N170 latency did not vary with stimulus type before the intermediary phase, however, N170 amplitude was consistently larger for upright than inverted Mooney faces. After the intermediary exercise, N170 was delayed for inverted compared to upright Mooney faces. In contrast, for both groups of subjects P2 amplitude was larger for nonface stimuli, and P2 amplitude decreased after the intermediate task only for the subjects trained to recognize Mooney faces. As the usual inversion effect seen with photographic faces (delayed and larger N170) was not seen with Mooney faces, these data suggest that this effect on N170 is due to the recruitment of analytic processing. P2 reflected learning and a deeper processing of the stimuli that were not identifiable as faces.

The effects of configural changes on faces were investigated in children to determine their role in encoding and recognition processes. Upright, inverted, and contrast-reversed unfamiliar faces were presented in blocks in which one-third of the pictures repeated immediately or after one intervening face. Subjects (8–16 years) responded to repeated faces; eventrelated potentials were recorded throughout the procedure. Recognition improved steadily with age and all components studied showed age effects reflecting differing maturation processes occurring until adulthood. All children were affected by inversion and contrast-reversal, and face-type effects were seen on latencies and amplitudes of early components (P1 and N170), as well as on later frontal amplitudes. The “old-new” repetition effects (larger amplitude for repeated stimuli) were found at frontal sites and were similar across age groups and face types, suggesting a general working memory system comparably involved in all age groups. These data demonstrate that (1) there is quantitative development in face processing, (2) both face encoding and recognition improve with age, but (3) only encoding is affected by configural changes. The data also suggest a gradual tuning of face processing towards the upright orientation.