Biology subjects

O'Muircheartaigh, J.

Publications and source records attributed to O'Muircheartaigh, J..

At least 19 recordsLinked to original sources

bioRxiv2026

Early development of cerebellar functional connectivity

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.

neuroscience↗

bioRxiv2026

Simultaneous EEG-fMRI investigation of sound sequence processing in human neonates

The ability to detect sensory regularities and their violations (i.e. deviance) is fundamental for learning and the orientation of attention across the lifespan. This starts from the prenatal period, where the environment is rich in regular patterns and deviations of auditory stimulation which likely provides the basis for the emergence of early learning capacities. Following birth, EEG recordings of brain activity have demonstrated that neonates detect violations of regularity and show a robust mismatch response to deviant auditory stimuli. However, it is unknown how this processing is integrated across wider regions within emergent brain networks. To gain comprehensive insight into both the temporal and spatial properties of the processing underlying sensory deviance detection in the neonatal brain, we acquired simultaneous EEG and fMRI data in sleeping neonates during an auditory oddball paradigm. A mismatch response was identified with EEG when a deviant sound appeared after a sequence of identical sounds but not when a sound was omitted, suggesting encoding of deviances that violated local sequence regularity, but not global sequence structure. Simultaneous fMRI demonstrated engagement of distributed cortical networks during sound sequence processing, encompassing temporal, sensori-motor, and inferior frontal cortices, as well as subcortical regions including the thalamus and hippocampus. Deviance detection was associated with activity in the superior and ventromedial (hippocampus and parahippocampus) parts of the temporal lobe, and the precentral gyrus. Together, these findings suggest that neonatal brain detects deviance in sound sequences through the encoding of local regularities, supported by distinct processing pathways within sensory and limbic systems. These insights help advance our understanding of early auditory learning mechanisms, with implications for understanding how atypical developmental trajectories may emerge in these substrates.

neuroscience↗

bioRxiv2025

Latent Representations of Early Brain Development: A Multivariate Normative Model of Brian Structure and Behaviour

Individual variation in neurodevelopment plays a central role in shaping cognitive abilities and behavioural profiles, influencing both typical functioning and risk for neurodevelopmental conditions. While much research has focused on characterising trajectories of brain structure changes during development, this typically entails assessing brain regions individually, overlooking the multivariate nature of neuroimaging data. In this study, we trained an autoencoder to map latent representations of childrens brain development using T1-weighted MRI scans from a paediatric cohort (n = 564, 55% male, mean age 4.90 years, age range [0.11,15.38]). This approach enabled us to establish multivariate normative models of brain structure, providing a more comprehensive framework for understanding neurodevelopmental variation. The latent space representation from this model effectively captured demographic variables (age and sex), while preserving both global and local structural features. The model accurately reconstructed the data, having mean reconstruction of 0.04 {+/-} 0.01, whilst also capturing demographic features with classification accuracy for sex of 84% {+/-} 4%, and a mean absolute error of 0.79 {+/-} 0.06 years for age prediction, highlighting its sensitivity to developmental changes. Further, we validated the approach using correlation analysis to show that deviations from the latent norms were significantly associated with multiple cognitive and behavioural measures, suggesting that variations in brain structure may reflect individual differences in neurodevelopment. Finally, we generated reference brain images that represent typical development and used them to visualise structural differences in individuals who deviate from this normative pattern. Our findings demonstrate that semi-supervised autoencoders, combined with multivariate normative modelling, offer a framework for characterizing neurodevelopmental trajectories. This approach can identify meaningful deviations associated with cognition and behaviour and has potential future applications across the lifespan.

developmental biology↗

bioRxiv2025

Functional covariance modes reveal aligned fetal and neonatal brain functional connectomes.

Spatially distributed functional networks are a fundamental property of brain organisation. While these networks are already present at full-term birth, establishing whether they exist before birth remains problematic, given the challenges inherent to in utero fMRI. Here, we introduce a seed-based functional covariance modes (FCMs) approach, which leverages inter-subject variability in connectivity between distinct regions and the rest of the brain to infer whole-brain network configurations. Unlike standard group-level independent component analysis, which consistently fails to reveal spatially distributed neural networks in fetal populations, FCMs successfully delineated a range of brain-wide functional networks in utero with high spatial fidelity to neonatal network maps, including bilateral organisation - a landmark feature of many neonatal functional networks. Furthermore, we demonstrated that bilateral fetal networks preferentially clustered along the brain midline and around cortical limbic territories. In contrast, single-hemisphere dominant networks mapped into areas associated with hemispheric functional asymmetry in the mature brain, including the highly lateralised language circuits. Together, these findings provide coherent evidence that the blueprint for the functional brain architecture, including its functional specialisation, is formed before birth.

neuroscience↗

bioRxiv2025

Motifs of brain cortical folding from birth to adulthood: structural asymmetry and folding-functional links

Cortical folding of 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 detection of shape biomarkers and confounds investigation of folding-functional relationships. Here we investigate cortical folding heterogeneity at fine scale, using novel hierarchical surface registration (MSM-HT) 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 characterize 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 for both adults and neonates, and show that improved correspondence of shape does not translate to improved areal correspondence, affirming previous studies that have pointed to dissociation of folding and functional organisation. 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.

neuroscience↗

bioRxiv2025

BabyPy: a brain-age model for infancy, childhood and adolescence

Withdrawal StatementThe authors have withdrawn this manuscript because during the peer-review process, they realised that their interpretation of the brain-age model presented in this paper was not fully accurate. While the analyses, statistics, and results remain valid, their interpretation of the internal test set performance metrics was inaccurate due to the non-linear shape of the distribution. In other words, although the overall R{superscript 2} is correctly reported as 0.80, this value does not capture the variability of the metrics across different age bins. For this reason, the authors are withdrawing the preprint. Therefore, the authors do not wish this work to be cited as reference for the project. The authors aim to re-run the analysis to provide a more robust version of the model and a new DOI will be linked on this page once the revised work is available. If you have any questions, please contact the corresponding author.

neuroscience↗

bioRxiv2025

Zero-phase-delay connectivity increases the reliability, concordance with structure, and prognostic ability of functional connectivity metrics

Neural populations synchronise their activity with either zero-phase-delay (activity in interacting regions occurs simultaneously) or a phase-delay (activity in one region follows the other). In electroencephalography and magnetoencephalography functional connectivity analyses, artefactual connectivity can also occur with zero-phase-delay. To minimise artefact, contemporary analyses typically exclude all zero-phase-delay interactions. However, the extent to which true interactions are resultingly lost - and the impact this has on the performance of functional connectivity metrics as biomarkers - remains unknown. Here, we show that most cortico-cortical functional connectivity occurs with zero- or near-zero phase-delay, even where such connectivity is unlikely to be artefactual. Including, rather than excluding, zero-phase-delay connectivity increases the reliability, convergence with neurobiology (structure-function concordance, homotopic interhemispheric connectivity, and age-related connectivity changes), and prognostic ability of functional connectivity metrics. We find that excluding zero-phase-delay connections penalises functional connectivity strength between the strongest structurally connected regions: stronger structural connections lead to functional connections with phase-delays closer to zero, mediated by a shorter signal propagation time. Our findings challenge generally accepted assumptions that zero-phase-exclusive methods are superior to zero-phase-inclusive methods.

neuroscience↗

bioRxiv2024

Verifying the concordance between motion corrected and conventional MPRAGE for pediatric morphometric analysis

PurposeTo validate a retrospective motion correction technique, Distributed and Incoherent Sample Orders for Reconstruction Deblurring using Encoding Redundancy (DISORDER), for pediatric brain morphometry. MethodsTwo T1-weighted MPRAGE 3D datasets were acquired at 3T in thirty-seven children, median age 7.75 years; one with conventional linear phase encoding and one using DISORDER. MPRAGE images were scored as motion-free or motion-corrupt. Cortical morphometry and regional brain volumes were measured with FreeSurfer, subcortical grey matter (GM) with FSL-FIRST, and hippocampal volumes with HippUnfold. Intraclass correlation coefficient (ICC) was used to determine agreement between the 2 MPRAGE acquisitions. Mann-Whitney U was used to test the difference between measures obtained using DISORDER and (i) motion-free and (ii) motion-corrupt conventional MPRAGE data. ResultsICC measures were good/excellent for most subcortical GM (motion-free, 0.75-0.96; motion-corrupt, 0.62-0.98) and regional brain volumes (motion-free 0.47-0.99; motion-corrupt, 0.54-0.99) between conventional MPRAGE and DISORDER data, except for the amygdala and nucleus accumbens (motion-free, 0.38-0.65; motion- corrupt, 0.1-0.42). However, these values were less consistent for motion-corrupt conventional MPRAGE data for hippocampal volumes (motion-free 0.65-0.99; motion-corrupt, 0.11-0.91) and cortical measures (motion-free 0.76-0.98; motion- corrupt, 0.09-0.74). Mann-Whitney U showed percentage differences in measures obtained with motion-corrupt conventional MPRAGE compared to DISORDER data were significantly greater than in those obtained using motion-free conventional MPRAGE data in 22/58 structures. ConclusionIn the absence of motion, morphometric measures obtained using DISORDER are largely consistent with those from conventional MPRAGE data, whereas improved reliability is obtained by DISORDER for motion-degraded scans. This study validates DISORDER for brain morphometric studies in children.

neuroscience↗

bioRxiv2024

The developing Human Connectome Project fetal functional MRI release: Methods and data structures

Recent advances in fetal fMRI present a new opportunity for neuroscience to study functional human brain connectivity at the time of its emergence. Progress in the field however has been hampered by the lack of openly available datasets that can be exploited by researchers across disciplines to develop methods that would address the unique challenges associated with imaging and analysing functional brain in utero, such as unconstrained head motion, dynamically evolving geometric distortions, or inherently low signal-to-noise ratio. Here we describe the developing Human Connectome Projects release of the largest open access fetal fMRI dataset to date, containing 275 scans from 255 fetuses and spanning the period of 20.86 to 38.29 post-menstrual weeks. We present a systematic approach to its pre-processing, implementing multi-band soft SENSE reconstruction, dynamic distortion corrections via phase unwrapping method, slice-to-volume reconstruction and a tailored temporal filtering model, with attention to the prominent sources of structured noise in the in utero fMRI. The dataset is accompanied with an advanced registration infrastructure, enabling group-level data fusion, and contains outputs from the main intermediate processing steps. This allows for various levels of data exploration by the imaging and neuroscientific community, starting from the development of robust pipelines for anatomical and temporal corrections to methods for elucidating the development of functional connectivity in utero. By providing a high-quality template for further method development and benchmarking, the release of the dataset will help to advance fetal fMRI to its deserved and timely place at the forefront of the efforts to build a life-long connectome of the human brain.

neuroscience↗

bioRxiv2023

Dynamic changes in subplate and cortical plate microstructure precede the onset of cortical folding in vivo

Cortical gyrification takes place predominantly during the second to third trimester, alongside other fundamental developmental processes, such as the development of white matter connections, lamination of the cortex and formation of neural circuits. The mechanistic biology that drives the formation cortical folding patterns remains an open question in neuroscience. In our previous work, we modelled the in utero diffusion signal to quantify the maturation of microstructure in transient fetal compartments, identifying patterns of change in diffusion metrics that reflect critical neurobiological transitions occurring in the second to third trimester. In this work, we apply the same modelling approach to explore whether microstructural maturation of these compartments is correlated with the process of gyrification. We quantify the relationship between sulcal depth and tissue anisotropy within the cortical plate (CP) and underlying subplate (SP), key transient fetal compartments often implicated in mechanistic hypotheses about the onset of gyrification. Using in utero high angular resolution multi-shell diffusion-weighted imaging (HARDI) from the Developing Human Connectome Project (dHCP), our analysis reveals that the anisotropic, tissue component of the diffusion signal in the SP and CP decreases immediately prior to the formation of sulcal pits in the fetal brain. By back-projecting a map of folded brain regions onto the unfolded brain, we find evidence for cytoarchitectural differences between gyral and sulcal areas in the late second trimester, suggesting that regional variation in the microstructure of transient fetal compartments precedes, and thus may have a mechanistic function, in the onset of cortical folding in the developing human brain.

neuroscience↗

bioRxiv2023

Gradient organisation of functional connectivity within resting state networks is present from 25 weeks gestation in the human fetal brain

During the third trimester of human gestation, the structure and function of the fetal brain is developing rapidly, laying the foundation for its connectivity framework across the lifespan. During this juncture, resting state functional MRI can be used to identify resting state networks (RSNs) which mature across gestation to resemble canonical RSNs at full term. However, the emergence of finer grain organisation of connectivity within these RSNs in the fetal brain is unknown. Using in-utero resting state fMRI, we performed connectopic mapping analysis to explore the presence of gradients in functional connectivity organisation of 11 cortical RSNs, known as connectopic maps in fetuses aged 25-37 weeks gestation (GW). We hypothesised that, if present, development of connectopic maps would be network specific in the third trimester of gestation, such that this property would be present within the earlier maturing primary sensory and motor networks before those associated with higher association function. In keeping with this, we found smooth connectopic maps in all of the studied RSNs from 25 GW, with the most spatially consistency across gestational age in the primary sensory and motor networks. Voxel-wise permutation testing of the connectopic maps identified local clusters of voxels within networks that significantly covaried with age, specifically in multisensory processing areas, suggesting multisensory processing may be developing during this period. Our analysis shows that functional gradient organisation is already established in the fetal brain and develops throughout gestation, which has strong implications for understanding how cortical organisation subserves the emergence of behaviour in the ensuing period.

neuroscience↗

bioRxiv2022

Widespread, depth-dependent microstructural damage in the cortex of children with drug resistant focal epilepsy: A quantitative T1 and T2 mapping study

ObjectiveTissue abnormalities in focal epilepsy may extend beyond the presumed focus. The underlying pathophysiology of these broader changes is unclear, and it is not known whether they result from ongoing disease processes, treatment-related side-effects, or whether they emerge earlier. Few studies have focused on the period of onset for most focal epilepsies, childhood. Fewer still have utilised quantitative MRI, which may provide a more sensitive and interpretable measure of tissue microstructural change. Here, we aimed to determine common spatial modes of changes in cortical architecture in children with heterogeneous drug-resistant focal epilepsy and, secondarily, whether changes were related to disease severity. MethodsTo assess cortical microstructure, quantitative T1 and T2 relaxometry (qT1 and qT2) was measured in 43 children with drug-resistant focal epilepsy [age-range=4-18 years] and 46 typically-developing children [age-range=2-18 years]. We assessed depth-dependent qT1 and qT2 values across the neocortex, as well as their gradient of change across cortical depths. We also determined whether global changes seen in group analyses were driven by focal pathologies in individual patients. Finally, as a proof-of-concept, we trained a classifier using qT1 and qT2 gradient maps from patients with radiologically-defined abnormalities (MRI-positive) and healthy controls, and tested if this could classify patients without reported radiological abnormalities (MRI-negative). ResultsWe uncovered depth-dependent qT1 and qT2 increases in widespread cortical areas in patients, likely representing microstructural alterations in myelin or gliosis. Changes did not correlate with disease severity measures, suggesting they may represent antecedent neurobiological alterations. Using a classifier trained with MRI-positive patients and controls, sensitivity was 62% at 100% specificity on held-out MRI-negative patients. SignificanceThese findings suggest the presence of a potential imaging endophenotype of focal epilepsy, detectable irrespective of radiologically-identified abnormalities, and potentially evident pre-symptomatically. Key PointsO_LIWe assessed cortical microstructure in children with focal epilepsy C_LIO_LIQuantitative T1 and T2 relaxometry (qT1 and qT2) was measured in the neocortex C_LIO_LIPatients showed extensive qT1/qT2 increases and intracortical organization changes C_LIO_LIAlterations may appear during cerebral development, prior to disease onset C_LI

neuroscience↗

bioRxiv2022

Neonatal brain dynamic functional connectivity: impact of preterm birth and association with early childhood neurodevelopment

Brain dynamic functional connectivity characterises transient connections between brain regions, changing over time. Features of brain dynamics have been linked to emotion and cognition in adult individuals, and atypical patterns have been associated with neurodevelopmental conditions such as autism. Although reliable functional brain networks have been consistently identified in neonates, little is known about the early development of dynamic functional connectivity. In this study we characterise dynamic functional connectivity with functional magnetic resonance imaging (fMRI) in the first few weeks of postnatal life in term-born (n = 324) and preterm-born (n = 66) individuals. We show that a dynamic landscape of brain connectivity is already established by the time of birth in the human brain, characterised by six transient states of neonatal functional connectivity with changing dynamics through the neonatal period. The pattern of dynamic connectivity is atypical in preterm-born infants, and associated with atypical social, sensory, and repetitive behaviours measured by the Quantitative Checklist for Autism in Toddlers (Q-CHAT) scores at 18 months of age.

neuroscience↗

bioRxiv2022

Comprehensive volumetric phenotyping of the neonatal brain in Down syndrome.

Down syndrome (DS) is the most common genetic cause of intellectual disability with a wide spectrum of neurodevelopmental outcomes. Magnetic resonance imaging (MRI) has been used to investigate differences in whole and/or regional brain volumes in DS from infancy to adulthood. However, to date, there have been relatively few in vivo neonatal brain imaging studies in DS, despite the presence of clearly identifiable characteristics at birth. Improved understanding of early brain development in DS is needed to assess phenotypic severity and identify appropriate time windows for early intervention. In this study, we used in vivo brain MRI to conduct a comprehensive volumetric phenotyping of the neonatal brain in DS. Using a robust cross-sectional reference sample of close to 500 preterm- to term-born control neonates, we have performed normative modelling and quantified volumetric deviation from the normative mean in 25 individual infants with DS [postmenstrual age at scan, median (range) = 40.57 (32.43 - 45.57) weeks], corrected for sex, age at scan and age from birth. We found that absolute whole brain volume was significantly reduced in neonates with DS (pFDR <0.0001), as were most underlying absolute tissue volumes, except for the lentiform nuclei and the extracerebral cerebrospinal fluid (eCSF), which were not significantly different, and the lateral ventricles, which were significantly enlarged (pFDR <0.0001). Relative volumes, adjusting for underlying differences in whole brain volume, revealed a dynamic shift in brain proportions in neonates with DS. In particular, the cerebellum, as well as the cingulate, frontal, insular and occipital white matter (WM) segments were significantly reduced in proportion (pFDR <0.0001). Conversely, deep grey matter (GM) structures, such as the thalami and lentiform nuclei, as well as CSF-filled compartments, such as the eCSF and the lateral ventricles were significantly enlarged in proportion (pFDR <0.0001). We also observed proportionally reduced frontal and occipital lobar volumes, in contrast with proportionally enlarged temporal and parietal lobar volumes. Lastly, we noted age-related volumetric differences between neonates with and without a congenital heart defect (CHD), indicating that there may be a baseline brain phenotype in neonates with DS, which is further altered in the presence of CHD. In summary, we provide a comprehensive volumetric phenotyping of the neonatal brain in DS and observe many features that appear to follow a developmental continuum, as noted in older age cohorts. There are currently no paediatric longitudinal neuroimaging investigations in DS, starting from the earliest time points, which greatly impedes our understanding of the developmental continuum of neuroanatomical parameters in DS. Whilst life expectancy of individuals with DS has greatly improved over the last few decades, early interventions may be essential to help improve outcomes and quality of life. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=93 SRC="FIGDIR/small/510205v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@15cc92aorg.highwire.dtl.DTLVardef@9af99dorg.highwire.dtl.DTLVardef@79b7dborg.highwire.dtl.DTLVardef@115adfc_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2022

Maturational networks of fetal brain activity

A key feature of the fetal period is the rapid emergence of organised patterns of spontaneous brain activity. However, characterising this process in utero using functional MRI is inherently challenging and requires analytical methods which can capture the constituent developmental transformations. Here, we introduce a novel analytical framework, termed "maturational networks" (matnets), that achieves this by modelling functional networks as an emerging property of the developing brain. Compared to standard network analysis methods that assume consistent patterns of connectivity across development, our method incorporates age-related changes in connectivity directly into network estimation. We test its performance in a large neonatal sample, finding that the matnets approach characterises adult-like features of functional network architecture with a greater specificity than a standard group-ICA approach; for example, our approach is able to identify a nearly complete default mode network. In the in-utero brain, matnets enables us to reveal the richness of emerging functional connections and the hierarchy of their maturational relationships with remarkable anatomical specificity. We show that the associative areas play a central role within prenatal functional architecture, therefore indicating that functional connections of high-level associative areas start emerging prior to exposure to the extra-utero environment.

neuroscience↗

bioRxiv2022

Development of neonatal brain functional centrality and alterations associated with preterm birth

Formation of the functional connectome in early life underpins future learning and behaviour. However, our understanding of how the functional organisation of brain regions into interconnected hubs (centrality) matures in the early postnatal period is limited, especially in response to factors associated with adverse neurodevelopmental outcomes such as preterm birth. We characterised voxel-wise functional centrality (weighted degree) in 366 neonates from the Developing Human Connectome Project. We tested the hypothesis that functional centrality matures with age at scan in term-born babies and is disrupted by preterm birth. Finally, we asked whether neonatal functional centrality predicts general neurodevelopmental outcomes at 18 months. We report an age-related increase in functional centrality predominantly within visual regions and decrease within motor and auditory regions in term-born infants. Preterm-born infants scanned at term equivalent age had higher functional centrality predominantly within visual regions and lower measures in motor regions. Functional centrality was not related to outcome at 18 months old. Thus, preterm birth appears to affect functional centrality in regions undergoing substantial development during the perinatal period. Our work raises the question of whether these alterations are adaptive or disruptive, and whether they predict neurodevelopmental characteristics that are more subtle or emerge later in life.

neuroscience↗

bioRxiv2021

Structural and functional asymmetry of the neonatal cerebral cortex

Features of brain asymmetry have been implicated in a broad range of cognitive processes; however, their origins are still poorly understood. Using a new left-right symmetric, spatiotemporal cortical surface atlas, we investigated cortical asymmetries in 442 healthy term-born neonates using structural and functional magnetic resonance images from the Developing Human Connectome Project. Cortical asymmetries observed in the term cohort were contextualised in two ways: by comparing them against cortical asymmetries observed in 103 preterm neonates scanned at term-equivalent age, and by comparing structural asymmetries against those observed in 1110 healthy young adults from the Human Connectome Project. Our results demonstrate that the neonatal cortex is markedly asymmetric in both structure and function, and while associations with preterm birth and biological sex were minimal, significant differences exist between birth and adulthood. Although these changes may represent experience-dependent developmental milestones, longitudinal studies across the lifespan are required to fully address these hypotheses.

neuroscience↗

bioRxiv2021

Neonatal multi-modal cortical profiles predict 18-month developmental outcomes

Developmental delays in infanthood often persist, turning into life-long difficulties, and coming at great cost for the individual and community. By examining the developing brain and its relation to developmental outcomes we can start to elucidate how the emergence of brain circuits is manifested in variability of infant motor, cognitive and behavioural capacities. In this study, we examined if cortical structural covariance at birth, indexing coordinated development, is related to later infant behaviour. We included 193 healthy term-born infants from the Developing Human Connectome Project (dHCP). An individual cortical connectivity matrix derived from morphological and microstructural features was computed for each subject (morphometric similarity networks, MSNs) and was used as input for the prediction of behavioural scores at 18 months using Connectome-Based Predictive Modeling (CPM). Neonatal MSNs successfully predicted social-emotional performance. Predictive edges were distributed between and within known functional cortical divisions with a specific important role for primary and posterior cortical regions. These results reveal that multi-modal neonatal cortical profiles showing coordinated maturation are related to developmental outcomes and that network organization at birth provides an early infrastructure for future functional skills.

neuroscience↗