Reliability of an automated gaze-controlled paradigm for capturing neural responses during visual and face processing in toddlerhood.

Electroencephalography (EEG) has substantial potential value for examining individual differences during early development. Current challenges in developmental EEG research include high dropout rates and low trial numbers, which may in part be due to passive stimulus presentation. Comparability is challenged by idiosyncratic processing pipelines. We present a novel toolbox ("Braintools") that uses gaze-contingent stimulus presentation and an automated processing pipeline suitable for measuring visual processing through low-density EEG recordings in the field. We tested the feasibility of this toolbox in 61 2.5- to 4-year olds, and computed test-retest reliability (1- to 2-week interval) of event-related potentials (ERP) associated with visual (P1) and face processing (N290, P400). Feasibility was good, with 52 toddlers providing some EEG data at the first session. Reliability values for ERP features were moderate when derived from 20 trials; this would allow inclusion of 79% of the 61 toddlers for the P1 and 82% for the N290 and P400. P1 amplitude/latency were more reliable across sessions than for the N290 and P400. Amplitudes were generally more reliable than latencies. Automated and standardized solutions to collection and analysis of event-related EEG data would allow efficient application in large-scale global health studies, opening significant potential for examining individual differences in development.

The Developing Human Connectome Project Neonatal Data Release.

The Developing Human Connectome Project has created a large open science resource which provides researchers with data for investigating typical and atypical brain development across the perinatal period. It has collected 1228 multimodal magnetic resonance imaging (MRI) brain datasets from 1173 fetal and/or neonatal participants, together with collateral demographic, clinical, family, neurocognitive and genomic data from 1173 participants, together with collateral demographic, clinical, family, neurocognitive and genomic data. All subjects were studied in utero and/or soon after birth on a single MRI scanner using specially developed scanning sequences which included novel motion-tolerant imaging methods. Imaging data are complemented by rich demographic, clinical, neurodevelopmental, and genomic information. The project is now releasing a large set of neonatal data; fetal data will be described and released separately. This release includes scans from 783 infants of whom: 583 were healthy infants born at term; as well as preterm infants; and infants at high risk of atypical neurocognitive development. Many infants were imaged more than once to provide longitudinal data, and the total number of datasets being released is 887. We now describe the dHCP image acquisition and processing protocols, summarize the available imaging and collateral data, and provide information on how the data can be accessed.

Social attention: What is it, how can we measure it, and what can it tell us about autism and ADHD?

Neurodevelopmental disorders like autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) affect 2-10% of children worldwide but are still poorly understood. Prospective studies of infants with an elevated familial likelihood of ASD or ADHD can provide insight into early mechanisms that canalize development down a typical or atypical course. Such work holds potential for earlier identification and intervention to support optimal outcomes in individuals with neurodevelopmental disorders. Disrupted attention may be involved in developmental trajectories to ASD and ADHD. Specifically, altered attention to social stimuli has been suggested as a possible endophenotype of ASD, lying between genetic factors impacting brain development and later symptoms. Similarly, changes in domain-general aspects of attention are commonly seen in ADHD and emerging evidence suggests these may begin in infancy. Could these patterns point to a common risk factor for both disorders? Or does social attention reflect the activity of a particular network of brain systems that is distinct to those underpinning general attention skills? One challenge to addressing such questions is our lack of understanding of the relation between social and general attention. In this chapter we review evidence from infants with later ASD and ADHD that illuminates this question.

Dynamic modulation of frontal theta power predicts cognitive ability in infancy.

Cognitive ability is a key factor that contributes to individual differences in life trajectories. Identifying early neural indicators of later cognitive ability may enable us to better elucidate the mechanisms that shape individual differences, eventually aiding identification of infants with an elevated likelihood of less optimal outcomes. A previous study associated a measure of neural activity (theta EEG) recorded at 12-months with non-verbal cognitive ability at ages two, three and seven in individuals with older siblings with autism (Jones et al., 2020). In a pre-registered study (https://osf.io/v5xrw/), we replicate and extend this finding in a younger, low-risk infant sample. EEG was recorded during presentation of a non-social video to a cohort of 6-month-old infants and behavioural data was collected at 6- and 9-months-old. Initial analyses replicated the finding that frontal theta power increases over the course of video viewing, extending this to 6-month-olds. Further, individual differences in the magnitude of this change significantly predicted non-verbal cognitive ability measured at 9-months, but not early executive function. Theta change at 6-months-old may therefore be an early indicator of later cognitive ability. This could have important implications for identification of, and interventions for, children at risk of poor cognitive outcomes.