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Mella, Allison Eve

University of British Columbia

Interrupted brain maturation from preterm birth increases the consequences of altered functional development (< 37 weeks gestational age (GA)). Mono-fractal analysis is an advanced functional magnetic resonance imaging (fMRI) analysis method that calculates the temporal auto-correlation characteristics from the blood oxygenation level dependent (BOLD) signal. This can be measured using the Hurst exponent (H). Our study goal was to measure H of the resting state-fMRI (rs-fMRI) BOLD signal to investigate alterations in brain signaling complexity at preterm age, term equivalent age and term healthy controls scanned at term age. Participant rs-fMRI and diffusion tensor imaging (DTI) data from 716 neonates born 23 to 43 weeks GA were obtained from the Developing Human Connectome Project. From the rsfMRI scans, independent component analysis was used to identify 13 resting state networks (RSNs). Temporal complexity was determined using H calculated from the power spectral density of the BOLD signal using Welch’s method. DTI scans from the preterm cohort were used to indirectly measure myelination with fractional anisotropy (FA) and radial diffusivity (RD) measurements. H in brain tissues and RSNs were assessed across gestational age and scan age, and Pearson's correlation was conducted between H and DTI measures. H significantly increased from preterm to TEA assessment, and earlier birth age contributed to lower H values. H begins below 0.5 at preterm age and crosses 0.5 at around term age in most regions. Motor and sensory networks were found to have the greatest increase in H. Correlations between DTI measures and H were moderate but significant, demonstrating somewhat parallel development of structural and functional systems. We found that H was an indicator for BOLD signal processing maturation in the infant brain. Accordingly, preterm infant signaling transforms from anticorrelated to correlated but is reduced by preterm birth compared to term born infants.

Text

2023-08-16

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/85491

Neuroscience

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/