bioRxiv Science⌕ Search

Biology subjects

Youngkin, A. E.

Publications and source records attributed to Youngkin, A. E..

2 recordsLinked to original sources

ALE Meta-Analysis Reveals Neural Substrates for the Impact of Prematurity on Executive Functioning in Children and Adults

Premature birth has known impacts on brain development, leading to sustained differences in cognitive function throughout the lifespan. Despite known deficits in executive functioning (EF) within individuals born premature, the extent to which neural engagement during executive functioning tasks differs between those born preterm and full-term is not fully understood. Additionally, it is unknown whether regions of differential engagement are the same in children and adults. This meta-analysis synthesizes fMRI results of activation differences between preterm and full-term subjects during executive functioning tasks in adult and child groups separately. Our results indicate that differences in neural engagement during EF tasks differ between pre-term (PT) and full term (FT) individuals in both age groups. Moreover, the regions affected contribute to well-known brain networks, including the fronto-striatal circuitry, the default mode network (DMN), and the salience network, all of which subserve broad EF capabilities. We found no differences between child and adult maps in a direct contrast, suggesting that effects of prematurity on executive functioning may persist from childhood into adulthood, although these findings should be interpreted in context of methodological limitations and potential confounding factors. This meta-analysis provides greater insight into the neural mechanisms behind EF disruption following premature birth. HighlightsO_LIDifferences in neural activation during executive function tasks exist in both children and adults with a history of premature birth. C_LIO_LIPT children show hyperactivity in fronto-striatal regions while PT adults show differential engagement of default mode network regions. C_LI

neuroscience↗

Atypical Alpha Oscillatory EEG Dynamics in Children with Angelman Syndrome

ObjectivesBiomarkers of atypical brain development are crucial for advancing clinical trials and guiding therapeutic interventions in Angelman syndrome (AS). Electroencephalography (EEG) captures well-characterized developmental changes in peak alpha frequency (PAF) that reflect underlying neural circuit maturation and may provide a sensitive metric for mapping atypical neural trajectories in AS. MethodWe analyzed EEG recordings from 159 children with AS (ages 1-15 years) and 185 age-matched typically developing (TD) controls. PAF was quantified using a well-established curve-fitting method applied to 1/f-corrected power spectra. To validate robustness, we further evaluated PAF using an alternative prominence-based peak detection approach across varying detection thresholds. ResultsSignificant disruptions in PAF were evident in children with AS. While over 90% of EEGs from TD children exhibited a clear alpha peak, fewer than 50% of EEGs from children with AS showed a detectable PAF. Furthermore, when PAF was present, its frequency was significantly lower in AS children and did not show the typical age-related increases observed in TD children. Validation analyses confirmed consistently lower rates of PAF detection in AS across varying sensitivity thresholds, demonstrating the robustness of these results. ConclusionsPAF is a robust and developmentally sensitive marker of disrupted neural maturation in children with Angelman syndrome. As a quantifiable and sensitive measure of neural disruptions in AS, PAF has the potential to complement and enhance existing clinical trial outcome assessments by providing an objective index of underlying brain function. Future analyses will explore individual differences related to PAF in AS, to better understand mechanistic insights to guide targeted therapeutic strategies.

neuroscience↗