Brain Maturational Imaging Markers in Neonates Reflect a Dual-Origin Model of Development
Poster No:
1036
Submission Type:
Late-Breaking Abstract Submission
Authors:
Clara Weber1, Logan Williams2, Emma Robinson3, Sofie Valk1
Institutions:
1Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Saxony, 2King’s College, London, United Kingdom, 3King's College London, London, London
First Author:
Co-Author(s):
Introduction:
The perinatal period is characterized by rapid changes in metabolism and environment that profoundly shape early neurodevelopment, highlighting the importance of examining imaging markers in this exceptional developmental stage. Recent research has revealed key organizational axes of brain structure that extend along anterior-posterior and inferior-superior directions (Valk et al., 2020). These patterns parallel the dual-origin hypothesis, which proposes that cortical development emerges from archi- and paleocortical origins (Goulas et al., 2019; Pandya et al., 2015). Here, we characterize early brain development in neonates and contextualize imaging marker differences between term- and preterm-born infants to dual-origin surface maps.
Methods:
Leveraging neuroimaging data from 552 neonates (447/105 term-/preterm-born, mean age: 1.3±1.4/8.9±4.7w; gestational age at birth (GAB): 39.9±1.2/31.9±3.6w, 44.9% female) in the developmental human connectome project (Hughes et al., 2017), we derived cortical thickness (CT) measures in 300 cortical parcels. Then, we calculated two types of structural covariance (CV), (i) group-level CV (CVg) as the correlation of CT metrics across subjects between all pairs of parcels (Valk et al., 2020), and (ii) individual CV (CVi), a measure of CT similarity between parcels calculated as CVi(j,k)=exp{-[CT(j)-CT(k)]^2/(2σ^2)}, where CT(j), CT(k) denote CT values in parcels j,k and σ=√[σ(j)+σ(k)], with σ(j), σ(k) denoting the standard deviation of CT values within parcels j,k (Wee et al., 2012). As such, CVg reflects CT trends across a population, whereas CVi mirrors spatial patterns of structural differentiation within individuals.
We then fit a model aggregating sex, age, GAB, and intracranial volume to surface markers (Larivière et al., 2022). To explore a dual-origin model, we delineated the hippocampus and piriform cortex parcels from the Glasser atlas (Glasser et al., 2016). Then, we calculated geodesic distance along the pial surface from these origin regions to each cortical vertex on a study-specific surface template, based on midthickness surfaces at 40 weeks postmenstrual age. Associations of effect size and gradient maps with these dual-origin distance patterns were assessed using Spearman's correlation, correcting for spatial autocorrelation in spin permutation tests (Alexander-Bloch et al., 2018; Vos de Wael et al., 2020).
We then fit a model aggregating sex, age, GAB, and intracranial volume to surface markers (Larivière et al., 2022). To explore a dual-origin model, we delineated the hippocampus and piriform cortex parcels from the Glasser atlas (Glasser et al., 2016). Then, we calculated geodesic distance along the pial surface from these origin regions to each cortical vertex on a study-specific surface template, based on midthickness surfaces at 40 weeks postmenstrual age. Associations of effect size and gradient maps with these dual-origin distance patterns were assessed using Spearman's correlation, correcting for spatial autocorrelation in spin permutation tests (Alexander-Bloch et al., 2018; Vos de Wael et al., 2020).
Results:
Using dimensionality reduction techniques, we extracted distinct organizational trajectories of CVg, and of a group average matrix of CVi. CVg gradients followed anterior-posterior and inferior-superior axes, reflecting broad population-level anatomical correlations, while CVi gradients extended between opercular-prefrontal and laterofrontal-inferioparietal regions, aligning more closely with cortical differentiation patterns at the individual level (Fig. 1a). In surface-based models, we identified widespread and significant CT increases and CVi decreases with age that were particularly prominent in sensory-motor areas (Fig. 1b). Effect size distribution between preterm- and term-born neonates emphasized the prefrontal area with relatively lower effect size in lateral temporal regions (Fig. 2a), revealing significant correlation to distance from the archi- and paleocortex (Fig. 2b). Likewise, secondary and tertiary gradients derived from CVi showed significant correlation to dual origin maps (G2: r=-0.295, p=0.037/r=-0.319, p=0.023, G3: r=0.346, p=0.008/r=0.355, p=0.004 for archi-/paleocortex). The primary gradient and CVg gradients did not show significant association with dual-origin maps.
·Figure 1
·Figure 2
Conclusions:
Our findings point toward differentiation across the cortex in early development emphasizing sensory-motor cortical regions, and highlight structural differences between term- and preterm neonates that appear to follow major axes of archi- and paleocorticofugal development. A future multimodal approach considering microarchitecture will further examine the biomolecular basis of this phenomenon.
Disorders of the Nervous System:
Neurodevelopmental/ Early Life (eg. ADHD, autism)
Lifespan Development:
Normal Brain Development: Fetus to Adolescence 1
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Cortical Anatomy and Brain Mapping 2
Keywords:
Cellular
Cortex
Cortical Layers
Development
PEDIATRIC
1|2Indicates the priority used for review
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