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It is unclear whether infants differentially process emotional faces in the brain at 5 months of age. Contradictory findings of previous research indicate that additional factors play a role in this process. The current study investigated whether five-month-old infants show differential brain activity between emotional faces. Furthermore, we explored the relation between emotional face processing and (I) stimulus characteristics, specifically the spatial frequency content, and (II) parent, child, and dyadic qualities of interaction characteristics. Face-sensitive components (i.e., N290, P400, Nc) in response to neutral and fearful faces that contained only lower or higher spatial frequencies were assessed. Quality of parent–child interaction was assessed with the Manchester Assessment of Caregiver Infant Interaction (MACI). The results show that, as a full group, none of the components differed between emotional expressions. However, when splitting the group based on median MACI scores, infants who showed high quality of interaction (i.e., more attentiveness to caregiver, positive and negative affect, and liveliness) processed emotions differently, whereas infants who showed low quality did not. These results indicate that a sub-group of infants show differential emotional face processing at 5 months of age, which seem to relate to quality of their behavior during the parent–child interaction.

Highlights • We report longitudinal ERP data of 80 infants in a face-discrimination task. • P1, N290, Nc are all sensitive to faces in five-month-olds. • P1, N290, Nc show equal face-categorization in infants tested longitudinally. • N290 shows less variation in face-categorization trajectories than P1 or Nc. • Visual ERPs increase in amplitude over infancy, but this is not face-specific., From infancy onwards, EEG is widely used to measure face-categorization, i.e. differential brain activity to faces versus non-face stimuli. Four ERP components likely signal infants’ face-sensitivity but reflect different underlying mechanisms: the P1, N290, P400, Nc. We test whether these components reveal similar developmental patterns from early to late infancy, using a longitudinal dataset of 80 infants tested at 5 and 10 months. The P1, N290, and the Nc show face-categorization already in 5-months-olds, a pattern which did not change over time. Development is visible as increased amplitudes in all components, but similar for face and non-face stimuli. By using Markov models, we illustrate that there are differences in the distribution of individual trajectories of face-categorization components from 5 to 10 months. Whereas individual trajectories appear more varied for the Nc and the P1, the N290 reveals a more consistent pattern: a larger proportion of 5-month-olds shows the dominant group response; a larger proportion of 10-month-olds remains in this group, and larger proportions of the alternative trajectories from 5- to 10-month-olds move towards the dominant group. This is vital information when one wants to examine individual differences in infant ERPs related to face-categorization.

Highlights • This article describes the rationale, design, and procedures of the YOUth cohort. • YOUth is set up to investigate what drives the development of social competence and self-regulation in children. • YOUth specifically investigates the role of neurocognitive development in child development. • YOUth has a flexible longitudinal design with repeated measurements throughout childhood, starting prenatally., Behavioral development in children shows large inter-individual variation, and is driven by the interplay between biological, psychological, and environmental processes. However, there is still little insight into how these processes interact. The YOUth cohort specifically focuses on two core characteristics of behavioral development: social competence and self-regulation. Social competence refers to the ability to engage in meaningful interactions with others, whereas self-regulation is the ability to control one’s emotions, behavior, and impulses, to balance between reactivity and control of the reaction, and to adjust to the prevailing environment. YOUth is an accelerated population-based longitudinal cohort study with repeated measurements, centering on two groups: YOUth Baby & Child and YOUth Child & Adolescent. YOUth Baby & Child aims to include 3,000 pregnant women, their partners and children, wheras YOUth Child & Adolescent aims to include 2,000 children aged between 8 and 10 years old and their parents. All participants will be followed for at least 6 years, and potentially longer. In this paper we describe in detail the design of this study, the population included, the determinants, intermediate neurocognitive measures and outcomes included in the study. Furthermore, we describe in detail the procedures of inclusion, informed consent, and study participation.

Functional Electroencephalography (EEG) networks in infants have been proposed as useful biomarkers for developmental brain disorders. However, the reliability of these networks and their characteristics has not been established. We evaluated the reliability of these networks and their characteristics in 10-month-old infants. Data were obtained during two EEG sessions 1 week apart and was subsequently analyzed at delta (0.5-3 Hz), theta (3-6 Hz), alpha1 (6-9 Hz), alpha2 (9-12 Hz), beta (12-25 Hz), and low gamma (25-45 Hz) frequency bands. Connectivity matrices were created by calculating the phase lag index between all channel pairs at given frequency bands. To determine the reliability of these connectivity matrices, intra-class correlations were calculated of global connectivity, local connectivity, and several graph characteristics. Comparing both sessions, global connectivity, as well as global graph characteristics (characteristic path length and average clustering coefficient) are highly reliable across multiple frequency bands; the alpha1 and theta band having the highest reliability in general. In contrast, local connectivity characteristics were less reliable across all frequency bands. We conclude that global connectivity measures are highly reliable over sessions. Local connectivity measures show lower reliability over sessions. This research therefore underlines the possibility of these global network characteristics to be used both as biomarkers of neurodevelopmental disorders, but also as important factors explaining development of typical behavior. [Abstract copyright: © 2019 The Authors. Brain and Behavior published by Wiley Periodicals, Inc.]

Research on social impairments in psychopathology has relied heavily on the face processing literature. However, although many sub-systems of facial information processing are described, recent evidence suggests that generalizability of these findings to social settings may be limited. The main argument is that in social interaction, the content of faces is more dynamic and dependent on the interplay between interaction partners, than the content of a non-responsive face (e.g. pictures or videos) as portrayed in a typical experiment. The question beckons whether gaze atypicalities to non-responsive faces in certain disorders generalize to faces in interaction. In the present study, a dual eye-tracking setup capable of recording gaze with high resolution was used to investigate how gaze behavior in interaction is related to traits of Autism Spectrum Disorder (ASD), and Social Anxiety Disorder (SAD). As clinical ASD and SAD groups have exhibited deficiencies in reciprocal social behavior, traits of these two conditions were assessed in a general population. We report that gaze behavior in interaction of individuals scoring high on ASD and SAD traits corroborates hypotheses posed in typical face-processing research using non-responsive stimuli. Moreover, our findings on the relation between paired gaze states (when and how often pairs look at each other’s eyes simultaneously or alternately) and ASD and SAD traits bear resemblance to prevailing models in the ASD literature (the ‘gaze aversion’ model) and SAD literature (the ‘vigilant-avoidance’ model). Pair-based analyses of gaze may reveal behavioral patterns crucial to our understanding of ASD and SAD, and more general to our understanding of eye movements as social signals in interaction.