Project Summary/Abstract
Developmental language impairments are common in the general population, affecting approximately 1 in 10
children. Despite this prevalence, little is known about the etiology of language difficulties observed in conditions
such as Autism Spectrum Disorder (ASD). Earlier therapeutic interventions for language impairments have
consistently been associated with better language and social outcomes, making it important to develop a better
understanding of the neural apparatus supporting successful language acquisition during the first year of life.
This project will improve our understanding of language development by longitudinally examining how neural
language processing and language network connectivity before an infant’s first birthday relate to later trajectories
of receptive and expressive language skills.
This proposal will leverage data from two ongoing NIH-funded longitudinal studies to examine the neural
processing of native vs. non-native language (Aim 1), functional connectivity within language networks (Aim 2),
and the structure of white matter tracts supporting cross-talk between language hubs (Aim 3). Language delays
have been associated with aberrant language-related neural activity and network connectivity in both typically
and atypically developing populations. Yet although newborns can already distinguish their native language from
other languages, no study has longitudinally examined the neural signatures of native language learning in early
infancy. Importantly, infant imaging studies have seldom employed adequate sample sizes and repeated
observations necessary for rigorous assessment of neurodevelopmental changes in brain connectivity within
language networks. Here, fMRI data collected with a stimulus-evoked language paradigm as part of the UCLA
ACE (NICHD P50 HD055784) will be used to chart neural responses associated with native language learning
during the first year of life in infants at high and low risk for ASD. Longitudinal resting-state fMRI and Diffusion
Tensor Imaging (DTI) data from the Baby Connectome Project (1U01MH110274) will be used to thoroughly
characterize the early development of functional and structural connectivity, respectively, across brain regions
implicated in language processing. Finally, across all aims, differences in brain activity and connectivity during
infancy will be related to later language trajectories to identify early predictors of atypical language development.
The candidate, Lauren Wagner, will carry out these studies as a Neuroscience graduate student at UCLA under
the tutelage of Drs. Mirella Dapretto and Lucina Uddin who, together, have vast expertise in neurodevelopment,
pediatric imaging, language development, advanced neuroimaging methods, and ASD. UCLA’s infrastructure,
collaborative environment, and research training resources offer the candidate an ideal training environment in
which to carry out these aims. This F31 NRSA Fellowship will provide the applicant with comprehensive training
in MRI, statistical modeling, teaching, and dissemination of results that, altogether, will lay the foundation for a
successful academic research career focusing on neurodevelopmental disorders affecting language acquisition.