Jonathan Ó Muircheartaigh

The cerebellum makes a critical contribution to cognitive and behavioural function, extending well beyond motor control, and is recognised as an important determinant of neurodevelopmental outcome. Despite this, little is known about the foundations of cerebellar functional organisation in early life. Addressing this gap is essential for establishing typical developmental trajectories against which atypical development can be assessed. Here, we analysed fMRI data from term-born neonates (n=155) scanned between 37 and 44 weeks postmenstrual age and mapped intra-cerebellar and cerebro-cerebellar functional connectivity across multiple levels of organisation. We identified 13 intrinsic connectivity networks (ICNs) within the neonatal cerebellum that recapitulated adult subdivisions, with two ICNs showing age-related increases in coverage and strength. Analysis of cerebro-cerebellar connectivity identified 15 sensory, motor and association cerebral clusters, seven increasing connectivity with age. Functional gradient analysis identified a continuous axis from somatomotor to association regions within intra-cerebellar and cerebro-cerebellar organisation, which became more pronounced with age. Together, these findings suggest that the foundations of adult cerebellar functional organisation are present at birth but undergo rapid and regionally heterogeneous maturation over the first weeks of postnatal life. This developmental framework provides a normative reference for understanding cerebellar development and its implications for later neurodevelopmental variation.

Background: Software tools can support MRI diagnosis of focal cortical dysplasias (FCDs) – subtle, surgically-treatable lesions that underlie drug-resistant focal epilepsy (DRFE). MELD-graph, a widely used open-source tool combining surface-based morphometry with a convolutional neural network, was developed using 1.5T and 3T MRI data. 7T MRI is increasingly used for lesion detection in DRFE. This study investigated whether MELD-graph is robust to domain shift at 7T. Methods: We collated paired 3T and 7T T1-weighted MRI, and FLAIR where available, from 23 patients with FCD (6 histologically-verified, 17 identified radiologically) and 39 healthy controls at four epilepsy centres. Manual lesion labels were used as ground truth. MELD-graph was run on 3T images, on 7T images with the default pipeline, and on 7T images with adaptations for 7T MRI (SPM bias-field correction, SynthStrip skull-stripping, sub-millimetric FreeSurfer reconstruction), with and without ComBat harmonisation. FCD detection performance and surface morphometry features were compared. Results: Sensitivity for FCD detection was 65% (15/23) at 3T, 48% (11/23) for 7T default and 52% (12/23) for 7T adapted, with Combat harmonisation. Among radiologically 3T-negative patients, 2/8 were detected at 3T and 3/8 at 7T; and among histologically confirmed FCD, 3/6 at 3T and 1/6 at 7T. Specificity was significantly lower at 7T (default 39%, adapted 45%) than 3T (76%). False-positives predominantly occurred in the basal temporal lobes. ComBat harmonisation improved specificity in all conditions and largely compensated for field-strength dependent differences in surface morphometry features. Adding FLAIR at 7T increased false-positive predictions. Conclusion: Sensitivity is comparable but specificity of MELD-graph is lower at 7T compared to 3T. Adaptations for 7T MRI can reduce segmentation errors but do not significantly improve FCD detection, while harmonisation improves performance. The adapted pipeline is released open-source. 7T MELD-graph outputs may inform radiologist review in challenging cases but require cautious interpretation.

Cortical folding of the brain is widely regarded as an interplay between genetic programming and biomechanical forces, closely linked to cytoarchitectonic regionalisation. Abnormal folding patterns are frequently observed in neurodevelopmental conditions and psychiatric disorders. However, significant inter-individual variability of secondary and tertiary folds obscures the detection of shape biomarkers and confounds the investigation of folding-functional relationships. Here, we investigate cortical folding heterogeneity at a fine scale, using Multimodal Surface Matching with Hierarchical Templates (MSM-HT), a hierarchical surface registration, to parse cortical folding patterns into a representative family of distinct anatomical templates. By applying this technique both to young adults from the Human Connectome Project (HCP) and neonates in the Developing HCP and Brain Imaging in Babies (BIBS) cohorts, we identify and characterise common lobe-wise folding patterns: observing consistency across both age groups, with neonatal samples showing less variation. Crucially, we highlight significant hemispheric asymmetry within the temporal lobe in adults, with a consistent trend in neonates. This study provides a critical step towards understanding brain asymmetry and complex relationships between folding and function, offering a robust framework to generalise the uncovered cortical folding motifs across datasets and developmental stages.

With the evolution of ultra-low-field MRI and the recognition of antenatal maternal anaemia as an important driver of altered neurodevelopment in toddlers and children, it is critical to determine whether these effects are detectable at ultra-low-field (64 mT) in infancy. The aim of this study was to assess the impact of antenatal maternal anaemia on infant brain structure across the first 2 years of life, using high-field (3 T) and ultra-low-field (64 mT) MRI. This neuroimaging substudy was embedded within Khula, an observational population-based birth cohort in South Africa. Pregnant women were enrolled antenatally and postnatally. Mother-child dyads (n = 394) were followed prospectively with a subsample attending neuroimaging at ∼3, 6, 12, 18 and 24 months of age. Anaemia was classified using World Health Organization thresholds, and neuroimaging data were processed using MiniMORPH. Linear mixed-effects models were used to investigate associations between antenatal maternal anaemia status and absolute regional infant brain volumes using high-field and ultra-low-field MRI. In repeated measures high-field (n = 195) and ultra-low-field (n = 341) infant neuroimaging subsamples, the prevalence of antenatal maternal anaemia was 28.24% (37/131) and 29.76% (61/205), respectively. Maternal anaemia in pregnancy was associated with altered child brain structure across both MRI systems, with group differences becoming detectable at ∼12 months. In the ultra-low-field subsample, infants born to anaemic mothers had 3.77% smaller intracranial volume (β = −0.24, P = 0.004) and 3.32% smaller putamen volumes (β = −0.18, P = 0.040) across the first 2 years of life. The interaction between antenatal maternal anaemia and age was significant for the caudate nucleus (β = −0.13, P = 0.038) and corpus callosum (β = −0.15, P = 0.007). Antenatal maternal anaemia was associated with 3.70% and 4.29% smaller caudate nucleus volumes at 18 and 24 months of age, respectively. Similarly, infants born to anaemic mothers had 4.39% smaller corpus callosum volumes by 12 months and 6.27% smaller corpus callosum volumes by 24 months. Postnatal child anaemia and antenatal maternal iron deficiency status were not associated with total or regional child brain volumes in the ultra-low-field subsample from this cohort. Maternal anaemia remained a robust predictor of volume differences in sensitivity analyses. This study is the first to demonstrate that the impact of maternal anaemia in pregnancy on child brain structure is detectable as early as infancy. The implications of this research are 2-fold: (i) informing the feasibility of ultra-low-field MRI in low- and middle-income countries and (ii) the timing and optimization of targeted recommendations for anaemia management in practice and policy.

Background: Hippocampal sclerosis (HS) is a common cause of drug-resistant focal epilepsy (DRFE) and amenable to neurosurgical treatment. Detection relies on MRI but can be challenging. 7 Tesla (T) ultra-high field MRI and automated MRI post-processing tools have independently been shown to improve radiological diagnosis of HS. However, combining these approaches remains underexplored. This study evaluated whether AID-HS, a tool for HS detection developed using 3T MRI, generalises to 7T MRI data. Methods: We collated a dataset of paired 3T and 7T T1-weighted MRI from four epilepsy centres, including 23 patients with HS, 39 healthy controls, and 23 individuals with focal cortical dysplasia as disease controls. Histopathology served as the gold standard for defining HS where available (n=7), otherwise radiological findings (n=16). AID-HS was applied to images acquired at both field strengths, and sensitivity and specificity for detection and lateralisation of HS were compared. Additionally, agreement of hippocampal features across 3T and 7T was evaluated. Results: We found no evidence of a difference in performance of AID-HS between 3T and 7T. Sensitivity for detection of unilateral HS was 63% (12/19) at 3T and 68% (13/19) at 7T (McNemar’s exact test p=1.0). Specificity in controls was 97% (60/62) at 3T and 100% (62/62) at 7T (p=0.5). Bilateral HS was correctly flagged in 3 of 4 cases using feature-based criteria, with high specificity in controls. Quantitative hippocampal features showed moderate to good agreement across field strengths (ICC 0.70 to 0.98), with small differences observed for volume and thickness estimates. Conclusion: AID-HS provides robust detection and lateralisation of HS across multiple 7T MRI centres, highlighting its potential to enhance lesion detection. Future work is needed to investigate whether models trained on 7T data can leverage the improved image quality for further gains in HS detection performance.

Background: Brain development is altered in neonates with congenital heart disease (CHD), with well‐characterised reductions in regional brain volumes and enlargement of CSF spaces. However, perioperative morphological changes remain incompletely understood. Purpose: To identify brain regions showing spatial patterns of coordinated expansion and contraction that differ between neonates with CHD after cardiac intervention and controls, assess perioperative changes and effects of perioperative risk factors, using Structural Covariance Component (SCC) analysis. Study Type: Prospective. Population: Forty‐one neonates with CHD (male = 20) who underwent cardiac surgery or catheterization and 359 healthy neonates (male = 185). Field Strength and Sequence: 3T T2‐weighted turbo‐spin‐echo sequence. Assessment: Images were motion‐corrected and reconstructed using a neonatal algorithm. Jacobian determinants calculated from non‐linear image registration to a template were input into an Independent Component Analysis to identify SCCs ( N = 40). SCC weightings were extracted, reflecting the degree to which the covariance pattern is expressed per neonate. Statistical Tests: Postoperative SCC weightings were compared to those of controls using a general linear model or robust regression. Perioperative change was assessed using a linear mixed effects model, and associations between perioperative differences and age at surgery, cardiopulmonary bypass duration, and postoperative pediatric intensive care unit stay were assessed using partial Spearman's rank correlation. Analyses were adjusted for covariates and corrected for multiple comparisons using False Discovery Rate, significant at p < 0.05. Results: Sixteen of the 40 SCCs showed significant differences between neonates with CHD after surgery and controls, including white matter, cortical‐ and deep gray matter, brainstem, and CSF ( f ² _partial = 0.02–0.04), with seven also showing significant perioperative change ( f ² _partial < 0.01–0.27). An additional nine SCCs only showed significant perioperative change ( f ² _partial < 0.01–0.14). Perioperative risk factors were not associated with perioperative change ( p > 0.463). Data Conclusion: This work highlights region‐specific postoperative alterations and perioperative changes in brain morphology of neonates with CHD. Evidence Level: 1. Technical Efficacy: Stage 3.

Neurotechnologies such as magnetic resonance imaging (electroencephalography (EEG), functional near-infrared spectroscopy (fNIRS), and MRI/functional(f)MRI) have become popular tools for the study of typical and atypical brain development. However, while rapid developmental changes, age‑specific anatomy and physiology, and methodological constraints uniquely affect the stability of these imaging measures, there is no document or resource that synthesises these issues across modalities. This white paper from the Respect4Neurodevelopment UK Network explores how reliability is currently assessed in pediatric neuroimaging and identifies outstanding knowledge gaps. To this goal, we combined a community survey among neuroimaging users and developers with a systematic literature review. There was broad recognition that reliability is an essential factor for translating neurotechnologies into personalized or clinical applications (n = 39 respondents). However, from a total of 1245 screened papers across modalities, there were only 15 that explicitly assessed EEG reliability during development, 16 for MRI/fMRI and 2 for fNIRS. The assessment of reliability thus has yet to become routine practice in the developmental neuroimaging field, challenged by the lack of standardized procedures, competing academic pressures, and lack of time and funding. These limitations need to be addressed to ensure that measurements in younger populations are reproducible enough for robust inference, clinical application, intervention, and large scale cohort studies. Our work provides a roadmap for the methodological advances and standardization alongside coordinated community efforts and institutional support that are critical to advance the next generation of reliable developmental neurotechnologies.

Background: Brain development is altered in neonates with congenital heart disease (CHD). However, development in the perioperative period remains incompletely understood. Purpose: This study used Structural Covariance Component (SCC) analysis to identify brain regions showing spatial patterns of coordinated expansion and contraction that differ between neonates with CHD after cardiac intervention and healthy controls, as well as pre-to postoperative changes and effects of perioperative risk factors. Study type: Prospective. Population: The cohort included 41 neonates with CHD who underwent cardiac surgery or catheterization and 359 healthy neonates. Field strength and sequence: 3 Tesla T2-weighted turbo-spin-echo sequence. Assessment: Brain MRI were motion-corrected and reconstructed using an established neonatal algorithm. Jacobian determinants calculated from non-linear registration of MRI to a neonatal template were input into an Independent Component Analysis to identify SCCs (N=40). SCC weightings were extracted, reflecting the degree to which the pattern of covariance is expressed in each neonate. Statistical tests: Postoperative SCC weightings were compared to healthy neonates using a general linear model or robust regression. Pre- and postoperative SCC weightings were compared using a linear mixed effect model. Pre- to postoperative differences were calculated and associations with age at surgery, cardiopulmonary bypass duration, and postoperative paediatric intensive care unit stay were assessed using partial spearman’s rank correlation. Analyses were adjusted for covariates and corrected for multiple comparisons using False Discovery Rate. Results: 16/40 SCCs showed significant differences between neonates with CHD after surgery and controls, including white matter, cortical- and deep grey matter, brainstem, and CSF regions, with seven also showing significant perioperative change. A further nine SCCs only showed significant perioperative change. Perioperative risk factors were not associated with perioperative change. Data conclusion: This data-driven approach highlights region-specific postoperative alterations and perioperative changes in brain morphology of neonates with CHD. Evidence level. 1. Technical Efficacy: Stage 3.

Objective: To compare intrathalamic morphometry in infants born preterm, with congenital heart disease (CHD) and typical controls and investigate associations with neurodevelopmental outcomes. Methods: 592 infants underwent T2-weighted brain MRI: 107 CHD [gestational age at birth (GA) ≥37.00 weeks], 126 preterm (GA 23.00-36.86), 359 controls (GA ≥37.00). We used data-driven structural covariance analysis to derive 8 components of coordinated expansion and contraction within the thalamus. Permutation testing was used to test associations between intrathalamic morphometry and group (control, CHD, preterm birth 2 ) in infants with CHD, and neurodevelopmental outcomes at 18-24 months. Results: Preterm infants born 2 was not associated with intrathalamic morphometry. Right posterior thalamus morphometry was associated with motor scores in preterm infants born 2 . Together, these findings suggest distinct thalamic phenotypes in prematurity and CHD.

Congenital heart disease (CHD) is associated with impaired early brain development and an increased risk of adverse neurodevelopmental outcomes. Previous studies have reported smaller hippocampal volumes in infants, children and adolescents with CHD. However, it is unclear whether specific subfields are differentially sensitive as hippocampal subfield morphometry has not been assessed in this population. The aims of this study were to test the hypothesis that infants with CHD deviate from typical hippocampal morphometry, using a normative modelling approach with reference data from 217 typically developing infants, and characterize the relationship between hippocampal morphometric measures and both cerebral oxygen delivery and neurodevelopmental outcomes in infants with CHD. Infants with CHD [60 preoperative and 29 postoperative, gestational age at birth median (range) 38.43 (36.71–40.57) weeks, postmenstrual age at scan 39.86 (37.14–45.71) weeks] and typically developing infants underwent brain MRI on a 3T scanner, and T2-weighted and inversion recovery T1-weighted imaging were acquired. Phase-contrast angiography was acquired in 53 infants with CHD before surgery, and cerebral oxygen delivery was calculated. Cognitive and motor abilities were assessed at 22 months (N = 52) using the Bayley Scales of Infant and Toddler Development-Third Edition. Volumes of the whole hippocampus, subiculum, cornu ammonis 1–4, dentate gyrus, and stratum radiatum lacunosum and moleculare were obtained by segmenting T1-weighted MRI data using a U-net model trained on infant data using HippUnfold. Normative curves were generated from the typically developing infants using two models: one for relative hippocampal volumes and one for hippocampal gyrification. Models accounted for the infant’s postmenstrual age at scan, postnatal age at scan and sex. The hippocampal gyrification model also accounted for hippocampal subfield volume. Z-scores representing the degree of positive or negative deviation from the normative mean were generated for infants with CHD. Relative volume z-scores were reduced for the bilateral cornu ammonis 4 and dentate gyrus (median Z-scores −0.45 to −0.82) and were increased for the left subiculum (mean Z-scores: preoperative 0.44; postoperative 0.51) in infants with CHD. Hippocampal gyrification was reduced in the bilateral subiculum, cornu ammonis 1–4 and dentate gyrus both pre- and postoperatively (mean Z-scores, −0.50 to −1.33). There was no significant relationship between preoperative hippocampal morphometric Z-scores and cerebral oxygen delivery or neurodevelopmental outcomes. Our findings suggest that hippocampal morphometry is altered in infants with CHD; however these effects are not uniform across the hippocampus.