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Pugh, K. R.

Publications and source records attributed to Pugh, K. R..

2 recordsLinked to original sources

Dual language experience enhances neural activation variability during an fMRI reading and language task

Previous work has shown that experience speaking more than one language in childhood is associated with decreased intra-individual neural variability in electrophysiological responses during a low-level speech perception task. However, no study has yet evaluated the impact of dual language experience on variability in fMRI responses during a higher-level spoken and written language processing task. In the current study, we calculated trial-by-trial variability in neural activation during an fMRI task that involved deciding whether spoken or printed English words matched pictures of items. We compared trial-by-trial neural activation variability between two groups of 8-15 year-old children: a group of dual language learners (N = 24; 11 female) who were Spanish-dominant and acquiring English, and a group of monolingual learners who were English-dominant (N = 17; 9 female). We found that when controlling for a variety of language, general cognitive, and demographic measures, neural activation variability for printed words was greater in the dual language learners compared to the monolingual learners in the right middle frontal gyrus, a brain region previously associated with attentional control. This finding highlights how neural variability offers a window of opportunity to examine experience-dependent mechanisms during human development, and motivates future research on bilingual language processing.

neuroscience↗

The Healthy Brain Network Biobank: An open resource for transdiagnostic research in pediatric mental health and learning disorders

Technological and methodological innovations are equipping researchers with unprecedented capabilities for detecting and characterizing pathologic processes in the developing human brain. As a result, ambitions to achieve clinically useful tools to assist in the diagnosis and management of mental health and learning disorders are gaining momentum. To this end, it is critical to accrue large-scale multimodal datasets that capture a broad range of commonly encountered clinical psychopathology. The Child Mind Institute has launched the Healthy Brain Network (HBN), an ongoing initiative focused on creating and sharing a biobank of data from 10,000 New York area participants (ages 5-21). The HBN Biobank houses data about psychiatric, behavioral, cognitive, and lifestyle phenotypes, as well as multimodal brain imaging (resting and naturalistic viewing fMRI, diffusion MRI, morphometric MRI), electroencephalography, eye-tracking, voice and video recordings, genetics, and actigraphy. Here, we present the rationale, design and implementation of HBN protocols. We describe the first data release (n = 664) and the potential of the biobank to advance related areas (e.g., biophysical modeling, voice analysis).

neuroscience↗