Annual Research Review: Not just a small adult brain: understanding later neurodevelopment through imaging the neonatal brain

Batalle, Dafnis; Edwards, A. David; O’Muircheartaigh, Jonathan

doi:10.1111/jcpp.12838

Cited by 80 publications

(64 citation statements)

References 232 publications

(269 reference statements)

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“…During the second and third trimesters of pregnancy, there is a phase of rapid brain maturation characterised by volumetric growth, increases in cortical complexity, white matter organization and myelination [1]. Early exposure to extrauterine life due to preterm birth affects around 11% of births, and is closely associated with neurodevelopmental, cognitive and psychiatric impairment [2,3,4], and alterations to development [5] that are apparent using in vivo imaging techniques. At the macro scale, these alterations can be characterised by charting white matter connections between brain regions using diffusion MRI (dMRI) [6,7,8,9,10,11,12].…”

Section: Introductionmentioning

confidence: 99%

Hierarchical complexity of the macro-scale neonatal brain

Blesa

Galdi

Cox³

et al. 2020

Preprint

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The human adult structural connectome has a rich topology composed of nodal hierarchies containing highly diverse connectivity patterns, aligned to the diverse range of functional specialisations in the brain. The emergence of this hierarchical complexity in human development is unknown. Here, we substantiate the hierarchical tiers and complexity of brain networks in the newborn period, assess correspondences with hierarchical complexity in adulthood, and investigate the effect of preterm birth, a leading cause of neurocognitive impairment and atypical brain development, on hierarchical complexity. We report that the neonatal and adult structural connectomes are both composed of distinct hierarchical tiers. Consistency of ROIs is found at both ends of this hierarchy during early life and in adulthood, but significant differences are evident in intermediate tiers. The neonatal connectome is hierarchically complex in term born neonates, but hierarchically complexity is altered in association with preterm birth. This is mainly due to diversity of connectivity patterns in Tier 3, which is comprised of regions that underlie sensorimotor processing and its integration with cognitive information. For neonates and adults, the highest tier (comprising hub regions) is ordered, rather than complex, with more homogeneous connectivity patterns in structural hubs. This suggests that the brain develops first a more rigid hierarchical structure in hub regions allowing for the development of greater and more diverse functional specialisation in lower level regions, while connectivity underpinning this diversity is dysmature in infants born preterm.

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Section: Introductionmentioning

confidence: 99%

Hierarchical complexity of the macro-scale neonatal brain

Blesa

Galdi

Cox³

et al. 2020

Preprint

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“…However, neonatal brains are not simply small adult brains (Batalle et al, 2017a), and this renders the above paradigm problematic. The rapid growth and changes in brain morphology during the neonatal period, as well as fast alterations in tissue composition that alter imaging contrast over time , render it challenging to ensure correspondence between template-driven ROIs and tractography protocols at different stages of development (Serag et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Non-Negative Data-Driven Mapping of Structural Connections in the Neonatal Brain

Thompson

Mohammadi‐Nejad

Glasser³

et al. 2020

Preprint

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Mapping connections in the neonatal brain can provide insight into the crucial early stages of neurodevelopment that shape brain organisation and lay the foundations for cognition and behaviour. Diffusion MRI and tractography provide unique opportunities for such explorations, through estimation of white matter bundles and brain connectivity. Atlas-based tractography protocols, i.e. a priori defined sets of masks and logical operations in a template space, have been commonly used in the adult brain to drive such explorations. However, rapid growth and maturation of the brain during early development make it challenging to ensure correspondence and validity of such atlas-based tractography approaches in the developing brain. An alternative can be provided by data-driven methods, which do not depend on predefined regions of interest. Here, we develop a novel data-driven framework to extract white matter bundles and their associated grey matter networks from neonatal tractography data, based on non-negative matrix factorisation that is inherently suited to the non-negative nature of structural connectivity data. We also develop a non-negative dual regression framework to map group-level components to individual subjects. Using in-silico simulations, we evaluate the accuracy of our approach in extracting connectivity components and compare with an alternative data-driven method, independent component analysis. We apply non-negative matrix factorisation to whole-brain connectivity obtained from publicly available datasets from the Developing Human Connectome Project, yielding grey matter components and their corresponding white matter bundles. We assess the validity and interpretability of these components against traditional tractography results and grey matter networks obtained from resting-state fMRI in the same subjects. We subsequently use them to generate a parcellation of the neonatal cortex using data from 323 new-born babies and we assess the robustness and reproducibility of this connectivity-driven parcellation.

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“…However, we use ANTs to register the functional parcels to each neonate's native space, which has been shown to be highly effective and reliable (Tustison et al, 2014). These limitations can only be overcome by scanning participants from all samples within the same study, and by functionally defining regions of interest individually, which may not be reliable in a sample of newborns (see Batalle et al, 2018 for a review of neuroimaging methods in adults vs. neonates).…”

Section: Discussionmentioning

confidence: 99%

Developmental changes in connectivity between the amygdala subnuclei and occipitotemporal cortex

Hansen

Saygin

2019

Preprint

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Word Count: 9326, including main body and references AMYGDALA SUBNUCLEI CONNECTIVITY 2 Abstract The amygdala, a subcortical structure known for social and emotional processing, can be subdivided into multiple nuclei with unique functions and connectivity patterns. Tracer studies in adult macaques have shown that the lateral and basal amygdala subnuclei decrease in connectivity to visual cortical areas moving from anterior to posterior, and that infants have similar adult-like projections plus additional connections that are refined with development. Can we delineate the connectivity between the amygdala subnuclei and occipitotemporal cortex in humans, and will it show similar developmental differences as macaques? If so, what functional regions may be contributing to this pattern of connectivity? To address these questions, we anatomically defined the lateral and basal amygdala subnuclei in 20 adult subjects, 27 kids (aged 7-8), and 15 neonates. We then defined the occipitotemporal region in each individual's native anatomy, and split this entire region into five equal sections from anterior to posterior. We also defined visual functional parcellations in the occipitotemporal cortex (e.g. FFA, PPA) and anatomically defined primary visual cortex (i.e., V1). Using Diffusion Weighted Imaging data, we ran probabilistic tractography with FSL between the amygdala subnuclei as seeds and the occipitotemporal cortical parcellations as targets. Results showed that like macaques, the mean connectivity across subjects to the occipitotemporal cortex significantly decreased on a gradient from anterior to posterior, and that connectivity in kids and neonates was adult-like but became more refined across development. Further, refinement of connectivity to mid and posterior occipitotemporal cortex was largely driven by anterior PPA, LO, and V1, with connectivity to higher order visual areas increasing with age. The functional maturation of these regions may contribute to the continued refinement of these connections, in line with Interactive Specialization hypotheses of brain development.

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Annual Research Review: Not just a small adult brain: understanding later neurodevelopment through imaging the neonatal brain

Cited by 80 publications

References 232 publications

Hierarchical complexity of the macro-scale neonatal brain

Hierarchical complexity of the macro-scale neonatal brain

Non-Negative Data-Driven Mapping of Structural Connections in the Neonatal Brain

Developmental changes in connectivity between the amygdala subnuclei and occipitotemporal cortex

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