The principal focus of our work is to identify the early signs of autism spectrum disorders (ASD) in order to improve developmental outcomes. Recent evidence suggests that the assessment of a wide range of skills and behaviors may help identify signs of ASD in the second year after birth, but the search for behavioral markers of ASD in the first 12 months has proven particularly challenging. This challenge is likely due to the limited behavioral repertoire of young infants, thus motivating the search for more sensitive biomarkers. Informed by our own (and others') work on the neural basis and early indicators of ASD, our overarching aim is to identify reliable biological markers of ASD in infants at ultra-high risk (UHR) for the disorder. Ultimately, we seek to (1) improve screening for ASD and the identification of infants who would benefit from early intervention and (2) elucidate the neural mechanisms underlying aberrant developmental trajectories.
We use an innovative, hypothesis driven, multi-modal approach employing eye tracking, pupillometry, electrophysiology (EEG), and magnetic resonance imaging (MRI) to track these infants' development in the first year, with a focus on social attention, implicit learning, and brain connectivity. Overall, we expect to detect altered developmental pathways in these interrelated domains in UHR infants, as compared to low risk infants (LR), and that the proposed measures will be predictive of an ASD diagnosis at 36 months.
The goal of our work on social attention is to quantify the development of attention to, and engagement with, socially-relevant stimuli, using eye-tracking and pupillometry paradigms capturing dynamic social interactions. The goal of our work on implicit learning is to examine its neural correlates using event related EEG and functional MRI. Stimuli consist of socially-relevant auditory stimuli (speech) and non-social visual stimuli (geometric shapes). Finally, the goals of our work on brain connectivity are to (1) characterize the development of functional and structural connectivity using EEG and MRI and (2) generate a prediction model of ASD by linking the proposed biomarkers in the first year after birth to key behavioral phenotypes as well as genetic risk factors. In this aim, we investigate the associations amongst the early biological markers previously described as well as their relations with previously identified behavioral indicators of ASD (e.g., orienting to own name, response to joint attention, reaction to others' distress) and relevant ASD risk genes (e.g., CNTNAP2, OXTR, MET).
The UCLA Infant Sibs project is part of an Autism Center of Excellent (ACE) grant funded by the National Institute of Child Health and Human Development (NICHD), one of only three ACE grants in the US. The ACE supports research using brain imaging technology to chart brain development among individuals having genes suspected of contributing to ASD. The ultimate goal is to link genetic variants to distinct patterns of brain development, structure and function in ASD. Researchers in this center also are investigating treatments that will improve social behavior and attention in infants and acquisition of language in older children with ASD. For more information, visit the Resources link above.