Dynamic patterns of cortical expansion during folding of the preterm human brain

Human brain organoid: trends, evolution, and remaining challenges

Advanced brain organoids provide promising platforms for deciphering the cellular and molecular processes of human neural development and diseases. Although various studies and reviews have described developments and advancements in brain organoids, few studies have comprehensively summarized and analyzed the global trends in this area of neuroscience. To identify and further facilitate the development of cerebral organoids, we utilized bibliometrics and visualization methods to analyze the global trends and evolution of brain organoids in the last 10 years. First, annual publications, countries/regions, organizations, journals, authors, co-citations, and keywords relating to brain organoids were identified. The hotspots in this field were also systematically identified. Subsequently, current applications for brain organoids in neuroscience, including human neural development, neural disorders, infectious diseases, regenerative medicine, drug discovery, and toxicity assessment studies, are comprehensively discussed. Towards that end, several considerations regarding the current challenges in brain organoid research and future strategies to advance neuroscience will be presented to further promote their application in neurological research.

Measuring neuroplasticity in human development: the potential to inform the type and timing of mental health interventions

Neuroplasticity during sensitive periods, the molecular and cellular process of enduring neural change in response to external stimuli during windows of high environmental sensitivity, is crucial for adaptation to expected environments and has implications for psychiatry. Animal research has characterized the developmental sequence and neurobiological mechanisms that govern neuroplasticity, yet gaps in our ability to measure neuroplasticity in humans limit the clinical translation of these principles. Here, we present a roadmap for the development and validation of neuroimaging and electrophysiology measures that index neuroplasticity to begin to address these gaps. We argue that validation of measures to track neuroplasticity in humans will elucidate the etiology of mental illness and inform the type and timing of mental health interventions to optimize effectiveness. We outline criteria for evaluating putative neuroimaging measures of plasticity in humans including links to neurobiological mechanisms shown to govern plasticity in animal models, developmental change that reflects heightened early life plasticity, and prediction of neural and/or behavior change. These criteria are applied to three putative measures of neuroplasticity using electroencephalography (gamma oscillations, aperiodic exponent of power/frequency) or functional magnetic resonance imaging (amplitude of low frequency fluctuations). We discuss the use of these markers in psychiatry, envision future uses for clinical and developmental translation, and suggest steps to address the limitations of the current putative neuroimaging measures of plasticity. With additional work, we expect these markers will significantly impact mental health and be used to characterize mechanisms, devise new interventions, and optimize developmental trajectories to reduce psychopathology risk.

Surface-Based Morphometry Analysis of the Cerebral Cortex in Patients With Probable Idiopathic Rapid Eye Movement Sleep Behavior Disorder

INTRODUCTION

Strong indications support the notion that idiopathic rapid eye movement (REM) sleep behavior disorder (iRBD) acts as a precursor to multiple α-synucleinopathies, including Parkinson's disease and dementia with Lewy bodies. Despite numerous investigations into the alterations in cortical thickness and the volume of subcortical areas associated with this condition, comprehensive studies on the cortical surface morphology, focusing on gyrification and sulcal depth changes, are scarce. The purpose of this research was to explore the cortical surface morphology in individuals with probable iRBD (piRBD), to pinpoint early-phase diagnostic markers.

METHODS

This study included 30 piRBD patients confirmed using the RBD Screening Questionnaire (RBDSQ) and 33 control individuals selected from the Parkinson's Progression Markers Initiative (PPMI) database. They underwent neurophysiological tests and MRI scans. The FreeSurfer software was utilized to estimate cortical thickness (CTH), cortical and subcortical volumetry, local gyrification index (LGI), and sulcus depth (SD). Subsequently, these parameters were compared between the two groups. Additionally, linear correlation analysis was employed to estimate the relationship between brain morphological parameters and clinical parameters.

RESULTS

Compared to the healthy control (HC), piRBD patients exhibited a significant reduction in CTH, LGI, and cortical volume in the bilateral superior parietal, lateral occipital, orbitofrontal, temporo-occipital, bilateral rostral middle frontal, inferior parietal, and precentral brain regions. Moreover, a significant and notable correlation was observed between CTH and Geriatric Depression Scale (GDS), letter-number sequencing (LTNS), the Benton Judgment of Line Orientation (BJLO) test, and the symbol digit modalities test (SDMT) in several brain regions encompassing the motor cortex.

CONCLUSION

Patients with piRBD displayed widespread atrophy in various brain regions, predominantly covering the motor and sensory cortex. Furthermore, LGI could serve as a prognostic biomarker of disease's progression in piRBD.

Neuro-evolutionary evidence for a universal fractal primate brain shape

The cerebral cortex displays a bewildering diversity of shapes and sizes across and within species. Despite this diversity, we present a universal multi-scale description of primate cortices. We show that all cortical shapes can be described as a set of nested folds of different sizes. As neighbouring folds are gradually merged, the cortices of 11 primate species follow a common scale-free morphometric trajectory, that also overlaps with over 70 other mammalian species. Our results indicate that all cerebral cortices are approximations of the same archetypal fractal shape with a fractal dimension of df = 2.5. Importantly, this new understanding enables a more precise quantification of brain morphology as a function of scale. To demonstrate the importance of this new understanding, we show a scale-dependent effect of ageing on brain morphology. We observe a more than fourfold increase in effect size (from two standard deviations to eight standard deviations) at a spatial scale of approximately 2 mm compared to standard morphological analyses. Our new understanding may, therefore, generate superior biomarkers for a range of conditions in the future.

Children born very preterm experience altered cortical expansion over the first decade of life

The brain develops rapidly from the final trimester of gestation through childhood, with cortical surface area expanding greatly in the first decade of life. However, it is unclear exactly where and how cortical surface area changes after birth, or how prematurity affects these developmental trajectories. Fifty-two very preterm (gestational age at birth = 26 ± 1.6 weeks) and 41 full-term (gestational age at birth = 39 ± 1.2 weeks) infants were scanned using structural magnetic resonance imaging at term-equivalent age and again at 9/10 years of age. Individual cortical surface reconstructions were extracted for each scan. Infant and 9/10 cortical surfaces were aligned using anatomically constrained Multimodal Surface Matching (aMSM), a technique that allows calculation of local expansion gradients across the cortical surface for each individual subject. At the neonatal time point, very preterm infants had significantly smaller surface area than their full-term peers (P < 0.001), but at the age 9/10-year time point, very preterm and full-term children had comparable surface area (P > 0.05). Across all subjects, cortical expansion by age 9/10 years was most pronounced in frontal, temporal, and supramarginal/inferior parietal junction areas, which are key association cortices (P Spin < 0.001). Very preterm children showed greater cortical surface area expansion between term-equivalent age and age 9/10 compared to their full-term peers in the medial and lateral frontal areas, precuneus, and middle temporal/banks of the superior sulcus junction (P < 0.05). Furthermore, within the very preterm group, expansion was highly variable within the orbitofrontal cortex and posterior regions of the brain. By mapping these patterns across the cortex, we identify differences in association cortices that are known to be important for executive functioning, emotion processing, and social cognition. Additional longitudinal work will be needed to understand if increased expansion in very preterm children is adaptive, or if differences persist into adulthood.

A subset of brain regions within adult functional connectivity networks demonstrate high reliability across early development

The human cerebral cortex contains groups of areas that support sensory, motor, cognitive, and affective functions, often categorized as functional networks. These areas show stronger internal and weaker external functional connectivity (FC) and exhibit similar FC profiles within rather than between networks. Previous studies have demonstrated the development of these networks from nascent forms present before birth to their mature, adult-like topography in childhood. However, analyses often still use definitions based on adult functional networks. We aim to assess how this might lead to the misidentification of functional networks and explore potential consequences and solutions. Our findings suggest that even though adult networks provide only a marginally better than-chance description of the infant FC organization, misidentification was largely driven by specific areas. By restricting functional networks to areas showing adult-like network clustering, we observed consistent within-network FC both within and across scans and throughout development. Additionally, these areas were spatially closer to locations with low variability in network identity among adults. Our analysis aids in understanding the potential consequences of using adult networks "as is" and provides guidance for future research on selecting and utilizing functional network models based on the research question and scenario.

Association of maternal hypertension during pregnancy with brain structure and behavioral problems in early adolescence

Emerging evidence suggests an association between maternal hypertension during pregnancy and mental health in the offspring. However, less is known about the role of hypertensive pregnancy in behavioral symptoms and brain structures of the offspring as well as in their developmental changes. Here, we utilized neuroimaging and behavioral data from 11,878 participants aged 9-10 years and their 2-year follow-up from the Adolescent Brain Cognitive Development (ABCD) study to investigate the long-term effects of maternal hypertension during pregnancy on early adolescent behavior and brain anatomy. Specifically, adolescents born of mothers with maternal hypertension are at risk of long-lasting behavioral problems, as manifested by higher externalizing and internalizing behavior scores at both 9-10 years and 11-12 years. These participants additionally presented with a higher cortical thickness, particularly in the fronto-parieto-temporal areas at 9-10 years. Four regions, including the left parahippocampus, left lateral orbitofrontal lobe, right superior temporal lobe and right temporal pole, remained thicker 2 years later. These findings were partially validated in rats modeled with Nω-nitro-L-arginine methyl ester (L-NAME) preeclampsia. Therefore, clinicians and women who experience hypertension during pregnancy should be warned of this risk, and healthcare providers should recommend appropriate clinical interventions for pregnancy-induced hypertension.

Longitudinal MRI of the developing ferret brain reveals regional variations in timing and rate of growth

Normative ferret brain development was characterized using magnetic resonance imaging. Brain growth was longitudinally monitored in 10 ferrets (equal numbers of males and females) from postnatal day 8 (P8) through P38 in 6-d increments. Template T2-weighted images were constructed at each age, and these were manually segmented into 12 to 14 brain regions. A logistic growth model was used to fit data from whole brain volumes and 8 of the individual regions in both males and females. More protracted growth was found in males, which results in larger brains; however, sex differences were not apparent when results were corrected for body weight. Additionally, surface models of the developing cortical plate were registered to one another using the anatomically-constrained Multimodal Surface Matching algorithm. This, in turn, enabled local logistic growth parameters to be mapped across the cortical surface. A close similarity was observed between surface area expansion timing and previous reports of the transverse neurogenic gradient in ferrets. Regional variation in the extent of surface area expansion and the maximum expansion rate was also revealed. This characterization of normative brain growth over the period of cerebral cortex folding may serve as a reference for ferret studies of brain development.

Feature similarity gradients detect alterations in the neonatal cortex associated with preterm birth

The early life environment programmes cortical architecture and cognition across the life course. A measure of cortical organisation that integrates information from multimodal MRI and is unbound by arbitrary parcellations has proven elusive, which hampers efforts to uncover the perinatal origins of cortical health. Here, we use the Vogt-Bailey index to provide a fine-grained description of regional homogeneities and sharp variations in cortical microstructure based on feature gradients, and we investigate the impact of being born preterm on cortical development at term-equivalent age. Compared with term-born controls, preterm infants have a homogeneous microstructure in temporal and occipital lobes, and the medial parietal, cingulate, and frontal cortices, compared with term infants. These observations replicated across two independent datasets and were robust to differences that remain in the data after matching samples and alignment of processing and quality control strategies. We conclude that cortical microstructural architecture is altered in preterm infants in a spatially distributed rather than localised fashion.

Molecular signatures of cortical expansion in the human fetal brain

The third trimester of human gestation is characterised by rapid increases in brain volume and cortical surface area. A growing catalogue of cells in the prenatal brain has revealed remarkable molecular diversity across cortical areas.1,2 Despite this, little is known about how this translates into the patterns of differential cortical expansion observed in humans during the latter stages of gestation. Here we present a new resource, μBrain, to facilitate knowledge translation between molecular and anatomical descriptions of the prenatal developing brain. Built using generative artificial intelligence, μBrain is a three-dimensional cellular-resolution digital atlas combining publicly-available serial sections of the postmortem human brain at 21 weeks gestation3 with bulk tissue microarray data, sampled across 29 cortical regions and 5 transient tissue zones.4 Using μBrain, we evaluate the molecular signatures of preferentially-expanded cortical regions during human gestation, quantified in utero using magnetic resonance imaging (MRI). We find that differences in the rates of expansion across cortical areas during gestation respect anatomical and evolutionary boundaries between cortical types5 and are founded upon extended periods of upper-layer cortical neuron migration that continue beyond mid-gestation. We identify a set of genes that are upregulated from mid-gestation and highly expressed in rapidly expanding neocortex, which are implicated in genetic disorders with cognitive sequelae. Our findings demonstrate a spatial coupling between areal differences in the timing of neurogenesis and rates of expansion across the neocortical sheet during the prenatal epoch. The μBrain atlas is available from: https://garedaba.github.io/micro-brain/ and provides a new tool to comprehensively map early brain development across domains, model systems and resolution scales.

Scaling patterns of cortical folding and thickness in early human brain development in comparison with primates

Across mammalia, brain morphology follows specific scaling patterns. Bigger bodies have bigger brains, with surface area outpacing volume growth, resulting in increased foldedness. We have recently studied scaling rules of cortical thickness, both local and global, finding that the cortical thickness difference between thick gyri and thin sulci also increases with brain size and foldedness. Here, we investigate early brain development in humans, using subjects from the Developing Human Connectome Project, scanned shortly after pre-term or full-term birth, yielding magnetic resonance images of the brain from 29 to 43 postmenstrual weeks. While the global cortical thickness does not change significantly during this development period, its distribution does, with sulci thinning, while gyri thickening. By comparing our results with our recent work on humans and 11 non-human primate species, we also compare the trajectories of primate evolution with human development, noticing that the 2 trends are distinct for volume, surface area, cortical thickness, and gyrification index. Finally, we introduce the global shape index as a proxy for gyrification index; while correlating very strongly with gyrification index, it offers the advantage of being calculated only from local quantities without generating a convex hull or alpha surface.

Maternal Perinatal Stress Trajectories and Negative Affect and Amygdala Development in Offspring

OBJECTIVE

Maternal psychological stress during pregnancy is a common risk factor for psychiatric disorders in offspring, but little is known about how heterogeneity of stress trajectories during pregnancy affect brain systems and behavioral phenotypes in infancy. This study was designed to address this gap in knowledge.

METHODS

Maternal anxiety, stress, and depression were assessed at multiple time points during pregnancy in two independent low-risk mother-infant cohorts (N=115 and N=2,156). Trajectories in maternal stress levels in relation to infant negative affect were examined in both cohorts. Neonatal amygdala resting-state functional connectivity MRI was examined in a subset of one cohort (N=60) to explore the potential relationship between maternal stress trajectories and brain systems in infants relevant to negative affect.

RESULTS

Four distinct trajectory clusters, characterized by changing patterns of stress over time, and two magnitude clusters, characterized by severity of stress, were identified in the original mother-infant cohort (N=115). The magnitude clusters were not associated with infant outcomes. The trajectory characterized by increasing stress in late pregnancy was associated with blunted development of infant negative affect. This relationship was replicated in the second, larger cohort (N=2,156). In addition, the trajectories that included increasing or peak maternal stress in late pregnancy were related to stronger neonatal amygdala functional connectivity to the anterior insula and the ventromedial prefrontal cortex in the exploratory analysis.

CONCLUSIONS

The trajectory of maternal stress appears to be important for offspring brain and behavioral development. Understanding heterogeneity in trajectories of maternal stress and their influence on infant brain and behavioral development is critical to developing targeted interventions.

Examining the relationship between fetal cortical thickness, gestational age, and maternal psychological distress

In utero exposure to maternal stress, anxiety, and depression has been associated with reduced cortical thickness (CT), and CT changes, in turn, to adverse neuropsychiatric outcomes. Here, we investigated global and regional (G/RCT) changes associated with fetal exposure to maternal psychological distress in 265 brain MRI studies from 177 healthy fetuses of low-risk pregnant women. GCT was measured from cortical gray matter (CGM) voxels; RCT was estimated from 82 cortical regions. GCT and RCT in 87% of regions strongly correlated with GA. Fetal exposure was most strongly associated with RCT in the parahippocampal region, ventromedial prefrontal cortex, and supramarginal gyrus suggesting that cortical alterations commonly associated with prenatal exposure could emerge in-utero. However, we note that while regional fetal brain involvement conformed to patterns observed in newborns and children exposed to prenatal maternal psychological distress, the reported associations did not survive multiple comparisons correction. This could be because the effects are more subtle in this early developmental window or because majority of the pregnant women in our study did not experience high levels of maternal distress. It is our hope that the current findings will spur future hypothesis-driven studies that include a full spectrum of maternal mental health scores.

Normal sulcation and gyration in neonatal cranial sonography from 24 weeks gestational age until term: a pictorial essay

Cranial ultrasound remains the most practical and available imaging modality for evaluating the brain of neonates. This is a pictorial essay on preterm (≥24 weeks) and term neonates who had an unremarkable cranial ultrasound in the first week of life at St. Luke's Medical Center Quezon City and St. Luke's Medical Center Global City from January 2017 to December 2021. We present two images for each landmark week of gestation in this retrospective multicentric review. The first image is in the coronal plane depicting the foramen of Monro and the third ventricle and the second image is in the sagittal plane at the level of the caudothalamic groove. The goal is to create an easy-to-use reference for the typical appearance and progression of the normal sulcation and gyration of the neonatal brain on ultrasound, depending on the weekly gestational age. Having a reference atlas matched for gestational age is a helpful tool for screening a myriad of pathologies and is expected to help clinicians and radiologists involved in the care of neonates monitor the development of the brain.

Geodesic theory of long association fibers arrangement in the human fetal cortex

Association fibers connect different areas of the cerebral cortex over long distances and integrate information to achieve higher brain functions, particularly in humans. Prototyped association fibers are developed to the respective tangential direction throughout the cerebral hemispheres along the deepest border of the subplate during the fetal period. However, how guidance to remote areas is achieved is not known. Because the subplate is located below the cortical surface, the tangential direction of the fibers may be biased by the curved surface geometry due to Sylvian fissure and cortical poles. The fiber length can be minimized if the tracts follow the shortest paths (geodesics) of the curved surface. Here, we propose and examine a theory that geodesics guide the tangential direction of long association fibers by analyzing how geodesics are spatially distributed on the fetal human brains. We found that the geodesics were dense on the saddle-shaped surface of the perisylvian region and sparse on the dome-shaped cortical poles. The geodesics corresponded with the arrangement of five typical association fibers, supporting the theory. Thus, the geodesic theory provides directional guidance information for wiring remote areas and suggests that long association fibers emerge from minimizing their tangential length in fetal brains.

Mechanical hierarchy in the formation and modulation of cortical folding patterns

The important mechanical parameters and their hierarchy in the growth and folding of the human brain have not been thoroughly understood. In this study, we developed a multiscale mechanical model to investigate how the interplay between initial geometrical undulations, differential tangential growth in the cortical plate, and axonal connectivity form and regulate the folding patterns of the human brain in a hierarchical order. To do so, different growth scenarios with bilayer spherical models that features initial undulations on the cortex and uniform or heterogeneous distribution of axonal fibers in the white matter were developed, statistically analyzed, and validated by the imaging observations. The results showed that the differential tangential growth is the inducer of cortical folding, and in a hierarchal order, high-amplitude initial undulations on the surface and axonal fibers in the substrate regulate the folding patterns and determine the location of gyri and sulci. The locations with dense axonal fibers after folding settle in gyri rather than sulci. The statistical results also indicated that there is a strong correlation between the location of positive (outward) and negative (inward) initial undulations and the locations of gyri and sulci after folding, respectively. In addition, the locations of 3-hinge gyral folds are strongly correlated with the initial positive undulations and locations of dense axonal fibers. As another finding, it was revealed that there is a correlation between the density of axonal fibers and local gyrification index, which has been observed in imaging studies but not yet fundamentally explained. This study is the first step in understanding the linkage between abnormal gyrification (surface morphology) and disruption in connectivity that has been observed in some brain disorders such as Autism Spectrum Disorder. Moreover, the findings of the study directly contribute to the concept of the regularity and variability of folding patterns in individual human brains.

Heterogeneous growth of the insula shapes the human brain

The human cerebrum consists of a precise and stereotyped arrangement of lobes, primary gyri, and connectivity that underlies human cognition [P. Rakic, Nat. Rev. Neurosci. 10, 724-735 (2009)]. The development of this arrangement is less clear. Current models explain individual primary gyrification but largely do not account for the global configuration of the cerebral lobes [T. Tallinen, J. Y. Chung, J. S. Biggins, L. Mahadevan, Proc. Natl. Acad. Sci. U.S.A. 111, 12667-12672 (2014) and D. C. Van Essen, Nature 385, 313-318 (1997)]. The insula, buried in the depths of the Sylvian fissure, is unique in terms of gyral anatomy and size. Here, we quantitatively show that the insula has unique morphology and location in the cerebrum and that these key differences emerge during fetal development. Finally, we identify quantitative differences in developmental migration patterns to the insula that may underlie these differences. We calculated morphologic data in the insula and other lobes in adults (N = 107) and in an in utero fetal brain atlas (N = 81 healthy fetuses). In utero, the insula grows an order of magnitude slower than the other lobes and demonstrates shallower sulci, less curvature, and less surface complexity both in adults and progressively throughout fetal development. Spherical projection analysis demonstrates that the lenticular nuclei obstruct 60 to 70% of radial pathways from the ventricular zone (VZ) to the insula, forcing a curved migration to the insula in contrast to a direct radial pathway. Using fetal diffusion tractography, we identify radial glial fascicles that originate from the VZ and curve around the lenticular nuclei to form the insula. These results confirm existing models of radial migration to the cortex and illustrate findings that suggest differential insular and cerebral development, laying the groundwork to understand cerebral malformations and insular function and pathologies.

Development of cortical folds in the human brain: An attempt to review biological hypotheses, early neuroimaging investigations and functional correlates

The folding of the human brain mostly takes place in utero, making it challenging to study. After a few pioneer studies looking into it in post-mortem foetal specimen, modern approaches based on neuroimaging have allowed the community to investigate the folding process in vivo, its normal progression, its early disturbances, and its relationship to later functional outcomes. In this review article, we aimed to first give an overview of the current hypotheses on the mechanisms governing cortical folding. After describing the methodological difficulties raised by its study in fetuses, neonates and infants with magnetic resonance imaging (MRI), we reported our current understanding of sulcal pattern emergence in the developing brain. We then highlighted the functional relevance of early sulcal development, through recent insights about hemispheric asymmetries and early factors influencing this dynamic such as prematurity. Finally, we outlined how longitudinal studies have started to relate early folding markers and the child's sensorimotor and cognitive outcome. Through this review, we hope to raise awareness on the potential of studying early sulcal patterns both from a fundamental and clinical perspective, as a window into early neurodevelopment and plasticity in relation to growth in utero and postnatal environment of the child.

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. Here we investigated cortical asymmetries in 442 healthy term-born neonates using structural and functional magnetic resonance images from the Developing Human Connectome Project. Our results demonstrate that the neonatal cortex is markedly asymmetric in both structure and function. Cortical asymmetries observed in the term cohort were contextualized 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 1,110 healthy young adults from the Human Connectome Project. While associations with preterm birth and biological sex were minimal, significant differences exist between birth and adulthood.

Effects of stress-dependent growth on evolution of sulcal direction and curvature in models of cortical folding

The majority of human brain folding occurs during the third trimester of gestation. Although many studies have investigated the physical mechanisms of brain folding, a comprehensive understanding of this complex process has not yet been achieved. In mechanical terms, the "differential growth hypothesis" suggests that the formation of folds results from a difference in expansion rates between cortical and subcortical layers, which eventually leads to mechanical instability akin to buckling. It has also been observed that axons, a substantial component of subcortical tissue, can elongate or shrink under tensile or compressive stress, respectively. Previous work has proposed that this cell-scale behavior in aggregate can produce stress-dependent growth in the subcortical layers. The current study investigates the potential role of stress-dependent growth on cortical surface morphology, in particular the variations in folding direction and curvature over the course of development. Evolution of sulcal direction and mid-cortical surface curvature were calculated from finite element simulations of three-dimensional folding in four different initial geometries: (i) sphere; (ii) axisymmetric oblate spheroid; (iii) axisymmetric prolate spheroid; and (iv) triaxial spheroid. The results were compared to mid-cortical surface reconstructions from four preterm human infants, imaged and analyzed at four time points during the period of brain folding. Results indicate that models incorporating subcortical stress-dependent growth predict folding patterns that more closely resemble those in the developing human brain.

Statement of Significance

Cortical folding is a critical process in human brain development. Aberrant folding is associated with disorders such as autism and schizophrenia, yet our understanding of the physical mechanism of folding remains limited. Ultimately mechanical forces must shape the brain. An important question is whether mechanical forces simply deform tissue elastically, or whether stresses in the tissue modulate growth. Evidence from this paper, consisting of quantitative comparisons between patterns of folding in the developing human brain and corresponding patterns in simulations, supports a key role for stress-dependent growth in cortical folding.

iBEAT V2.0: a multisite-applicable, deep learning-based pipeline for infant cerebral cortical surface reconstruction

The human cerebral cortex undergoes dramatic and critical development during early postnatal stages. Benefiting from advances in neuroimaging, many infant brain magnetic resonance imaging (MRI) datasets have been collected from multiple imaging sites with different scanners and imaging protocols for the investigation of normal and abnormal early brain development. However, it is extremely challenging to precisely process and quantify infant brain development with these multisite imaging data because infant brain MRI scans exhibit (a) extremely low and dynamic tissue contrast caused by ongoing myelination and maturation and (b) inter-site data heterogeneity resulting from the use of diverse imaging protocols/scanners. Consequently, existing computational tools and pipelines typically perform poorly on infant MRI data. To address these challenges, we propose a robust, multisite-applicable, infant-tailored computational pipeline that leverages powerful deep learning techniques. The main functionality of the proposed pipeline includes preprocessing, brain skull stripping, tissue segmentation, topology correction, cortical surface reconstruction and measurement. Our pipeline can handle both T1w and T2w structural infant brain MR images well in a wide age range (from birth to 6 years of age) and is effective for different imaging protocols/scanners, despite being trained only on the data from the Baby Connectome Project. Extensive comparisons with existing methods on multisite, multimodal and multi-age datasets demonstrate superior effectiveness, accuracy and robustness of our pipeline. We have maintained a website, iBEAT Cloud, for users to process their images with our pipeline ( http://www.ibeat.cloud ), which has successfully processed over 16,000 infant MRI scans from more than 100 institutions with various imaging protocols/scanners.

Long-term learning transforms prefrontal cortex representations during working memory

The role of the lateral prefrontal cortex (lPFC) in working memory (WM) is debated. Non-human primate (NHP) electrophysiology shows that the lPFC stores WM representations, but human neuroimaging suggests that the lPFC controls WM content in sensory cortices. These accounts are confounded by differences in task training and stimulus exposure. We tested whether long-term training alters lPFC function by densely sampling WM activity using functional MRI. Over 3 months, participants trained on both a WM and serial reaction time (SRT) task, wherein fractal stimuli were embedded within sequences. WM performance improved for trained (but not novel) fractals and, neurally, delay activity increased in distributed lPFC voxels across learning. Item-level WM representations became detectable within lPFC patterns, and lPFC activity reflected sequence relationships from the SRT task. These findings demonstrate that human lPFC develops stimulus-selective responses with learning, and WM representations are shaped by long-term experience, which could reconcile competing accounts of WM functioning.

Morphological development of the human fetal striatum during the second trimester

The morphological development of the fetal striatum during the second trimester has remained poorly described. We manually segmented the striatum using 7.0-T MR images of the fetal specimens ranging from 14 to 22 gestational weeks. The global development of the striatum was evaluated by volume measurement. The absolute volume (Vabs) of the caudate nucleus (CN) increased linearly with gestational age, while the relative volume (Vrel) showed a quadratic growth. Both Vabs and Vrel of putamen increased linearly. Through shape analysis, the changes of local structure in developing striatum were specifically demonstrated. Except for the CN tail, the lateral and medial parts of the CN grew faster than the middle regions, with a clear rostral-caudal growth gradient as well as a distinct "outside-in" growth gradient. For putamen, the dorsal and ventral regions grew obviously faster than the other regions, with a dorsal-ventral bidirectional developmental pattern. The right CN was larger than the left, whereas there was no significant hemispheric asymmetry in the putamen. By establishing the developmental trajectories, spatial heterochrony, and hemispheric dimorphism of human fetal striatum, these data bring new insight into the fetal striatum development and provide detailed anatomical references for future striatal studies.

Maternal mental health and adverse birth outcomes

Recent research in economics emphasizes the role of in utero conditions for the health endowment at birth and in early childhood and for social as well as economic outcomes in later life. This paper analyzes the relation between maternal mental health during pregnancy and birth outcomes of the child. In particular, we analyze the relationship between maternal mental health during pregnancy and the probability of giving birth preterm (PT), having a newborn at low birth weight (LBW) or being small for gestational age (SGA). Based on large population-representative data from the German Socio-Economic Panel (SOEP) and cohort data from the National Educational Panel Study (NEPS), we present extensive descriptive evidence on the relationship between maternal mental health and preterm birth by carrying out OLS estimates controlling for a wide range of socioeconomic characteristics. In addition, we apply matching estimators and mother fixed effects models, which bring us closer toward a causal interpretation of estimates. In summary, the results uniformly provide evidence that poor maternal mental health is a risk factor for preterm birth and low birth weight in offspring. In contrast, we find no evidence for an relationship between maternal mental health and small for gestational age at birth.

Mapping developmental regionalization and patterns of cortical surface area from 29 post-menstrual weeks to 2 years of age

Surface area of the human cerebral cortex expands extremely dynamically and regionally heterogeneously from the third trimester of pregnancy to 2 y of age, reflecting the spatial heterogeneity of the underlying microstructural and functional development of the cerebral cortex. However, little is known about the developmental patterns and regionalization of cortical surface area during this critical stage, due to the lack of high-quality imaging data and accurate computational tools for pediatric brain MRI data. To fill this critical knowledge gap, by leveraging 1,037 high-quality MRI scans with the age between 29 post-menstrual weeks and 24 mo from 735 pediatric subjects in two complementary datasets, i.e., the Baby Connectome Project (BCP) and the developing Human Connectome Project (dHCP), and state-of-the-art dedicated image-processing tools, we unprecedentedly parcellate the cerebral cortex into a set of distinct subdivisions purely according to the developmental patterns of the cortical surface. Our discovered developmentally distinct subdivisions correspond well to structurally and functionally meaningful regions and reveal spatially contiguous, hierarchical, and bilaterally symmetric patterns of early cortical surface expansion. We also show that high-order association subdivisions, where cortical folds emerge later during prenatal stages, undergo more dramatic cortical surface expansion during infancy, compared with the central regions, especially the sensorimotor and insula cortices, thus forming a distinct central-pole division in early cortical surface expansion. These results provide an important reference for exploring and understanding dynamic early brain development in health and disease.

Modeling spatial, developmental, physiological, and topological constraints on human brain connectivity

The complex connectivity of nervous systems is thought to have been shaped by competitive selection pressures to minimize wiring costs and support adaptive function. Accordingly, recent modeling work indicates that stochastic processes, shaped by putative trade-offs between the cost and value of each connection, can successfully reproduce many topological properties of macroscale human connectomes measured with diffusion magnetic resonance imaging. Here, we derive a new formalism that more accurately captures the competing pressures of wiring cost minimization and topological complexity. We further show that model performance can be improved by accounting for developmental changes in brain geometry and associated wiring costs, and by using interregional transcriptional or microstructural similarity rather than topological wiring rules. However, all models struggled to capture topographical (i.e., spatial) network properties. Our findings highlight an important role for genetics in shaping macroscale brain connectivity and indicate that stochastic models offer an incomplete account of connectome organization.

Altered Cerebral Curvature in Preterm Infants Is Associated with the Common Genetic Variation Related to Autism Spectrum Disorder and Lipid Metabolism

Preterm births are often associated with neurodevelopmental impairment. In the critical developmental period of the fetal brain, preterm birth disrupts cortical maturation. Notably, preterm birth leads to alterations in the fronto-striatal and temporal lobes and the limbic region. Recent advances in MRI acquisition and analysis methods have revealed an integrated approach to the genetic influence on brain structure. Based on imaging studies, we hypothesized that the altered cortical structure observed after preterm birth is associated with common genetic variations. We found that the presence of the minor allele at rs1042778 in OXTR was associated with reduced curvature in the right medial orbitofrontal gyrus (p < 0.001). The presence of the minor allele at rs174576 in FADS2 (p < 0.001) or rs740603 in COMT (p < 0.001) was related to reduced curvature in the left posterior cingulate gyrus. This study provides biological insight into altered cortical curvature at term-equivalent age, suggesting that the common genetic variations related to autism spectrum disorder (ASD) and lipid metabolism may mediate vulnerability to early cortical dysmaturation in preterm infants.

Emerging 4D Printing Strategies for Next-Generation Tissue Regeneration and Medical Devices

The rapid development of 3D printing has led to considerable progress in the field of biomedical engineering. Notably, 4D printing provides a potential strategy to achieve a time-dependent physical change within tissue scaffolds or replicate the dynamic biological behaviors of native tissues for smart tissue regeneration and the fabrication of medical devices. The fabricated stimulus-responsive structures can offer dynamic, reprogrammable deformation or actuation to mimic complex physical, biochemical, and mechanical processes of native tissues. Although there is notable progress made in the development of the 4D printing approach for various biomedical applications, its more broad-scale adoption for clinical use and tissue engineering purposes is complicated by a notable limitation of printable smart materials and the simplistic nature of achievable responses possible with current sources of stimulation. In this review, the recent progress made in the field of 4D printing by discussing the various printing mechanisms that are achieved with great emphasis on smart ink mechanisms of 4D actuation, construct structural design, and printing technologies, is highlighted. Recent 4D printing studies which focus on the applications of tissue/organ regeneration and medical devices are then summarized. Finally, the current challenges and future perspectives of 4D printing are also discussed.

An ode to fetal, infant, and toddler neuroimaging: Chronicling early clinical to research applications with MRI, and an introduction to an academic society connecting the field

Fetal, infant, and toddler neuroimaging is commonly thought of as a development of modern times (last two decades). Yet, this field mobilized shortly after the discovery and implementation of MRI technology. Here, we provide a review of the parallel advancements in the fields of fetal, infant, and toddler neuroimaging, noting the shifts from clinical to research use, and the ongoing challenges in this fast-growing field. We chronicle the pioneering science of fetal, infant, and toddler neuroimaging, highlighting the early studies that set the stage for modern advances in imaging during this developmental period, and the large-scale multi-site efforts which ultimately led to the explosion of interest in the field today. Lastly, we consider the growing pains of the community and the need for an academic society that bridges expertise in developmental neuroscience, clinical science, as well as computational and biomedical engineering, to ensure special consideration of the vulnerable mother-offspring dyad (especially during pregnancy), data quality, and image processing tools that are created, rather than adapted, for the young brain.

Genetic Influences on Longitudinal Trajectories of Cortical Thickness and Surface Area during the First 2 Years of Life

Genetic influences on cortical thickness (CT) and surface area (SA) are known to vary across the life span. Little is known about the extent to which genetic factors influence CT and SA in infancy and toddlerhood. We performed the first longitudinal assessment of genetic influences on variation in CT and SA in 501 twins who were aged 0-2 years. We observed substantial additive genetic influences on both average CT (0.48 in neonates, 0.37 in 1-year-olds, and 0.44 in 2-year-olds) and total SA (0.59 in neonates, 0.74 in 1-year-olds, and 0.73 in 2-year-olds). In addition, we found strong heritability of the change in average CT (0.49) from neonates to 1-year-olds, but not from 1- to 2-year-olds. Moreover, we found strong genetic correlations for average CT (rG = 0.92) between 1- and 2-year-olds and strong genetic correlations for total SA across all timepoints (rG = 0.96 between neonates and 1-year-olds, rG = 1 between 1- and 2-year-olds). In addition, we found CT and SA are strongly genetic correlated at birth, but weaken over time. Overall, results suggest a dynamic genetic relationship between CT and SA during first 2 years of life and provide novel insights into how genetic influences shape the cortical structure during early brain development.

Cerebral cortex maldevelopment in syndromic craniosynostosis

AIM

To assess the relationship of surface area of the cerebral cortex to intracranial volume (ICV) in syndromic craniosynostosis.

METHOD

Records of 140 patients (64 males, 76 females; mean age 8y 6mo [SD 5y 6mo], range 1y 2mo-24y 2mo) with syndromic craniosynostosis were reviewed to include clinical and imaging data. Two hundred and three total magnetic resonance imaging (MRI) scans were evaluated in this study (148 patients with fibroblast growth factor receptor [FGFR], 19 patients with TWIST1, and 36 controls). MRIs were processed via FreeSurfer pipeline to determine total ICV and cortical surface area (CSA). Scaling coefficients were calculated from log-transformed data via mixed regression to account for multiple measurements, sex, syndrome, and age. Educational outcomes were reported by syndrome.

RESULTS

Mean ICV was greater in patients with FGFR (1519cm³ , SD 269cm³ , p=0.016) than in patients with TWIST1 (1304cm³ , SD 145cm³ ) or controls (1405cm³ , SD 158cm³ ). CSA was related to ICV by a scaling law with an exponent of 0.68 (95% confidence interval [CI] 0.61-0.76) in patients with FGFR compared to 0.81 (95% CI 0.50-1.12) in patients with TWIST1 and 0.77 (95% CI 0.61-0.93) in controls. Lobar analysis revealed reduced scaling in the parietal (0.50, 95% CI 0.42-0.59) and occipital (0.67, 95% CI 0.54-0.80) lobes of patients with FGFR compared with controls. Modified learning environments were needed more often in patients with FGFR.

INTERPRETATION

Despite adequate ICV in FGFR-mediated craniosynostosis, CSA development is reduced, indicating maldevelopment, particularly in parietal and occipital lobes. Modified education is also more common in patients with FGFR.

Shape variability of the central sulcus in the developing brain: a longitudinal descriptive and predictive study in preterm infants

Despite growing evidence of links between sulcation and function in the adult brain, the folding dynamics, occurring mostly before normal-term-birth, is vastly unknown. Looking into the development of cortical sulci in infants can give us keys to address fundamental questions: what is the sulcal shape variability in the developing brain? When are the shape features encoded? How are these morphological parameters related to further functional development? In this study, we aimed to investigate the shape variability of the developing central sulcus, which is the frontier between the primary somatosensory and motor cortices. We studied a cohort of 71 extremely preterm infants scanned twice using MRI - once around 30 weeks post-menstrual age (w PMA) and once at term-equivalent age, around 40w PMA -, in order to quantify the sulcus's shape variability using manifold learning, regardless of age-group or hemisphere. We then used these shape descriptors to evaluate the sulcus's variability at both ages and to assess hemispheric and age-group specificities. This led us to propose a description of ten shape features capturing the variability in the central sulcus of preterm infants. Our results suggested that most of these features (8/10) are encoded as early as 30w PMA. We unprecedentedly observed hemispheric asymmetries at both ages, and the one captured at term-equivalent age seems to correspond with the asymmetry pattern previously reported in adults. We further trained classifiers in order to explore the predictive value of these shape features on manual performance at 5 years of age (handedness and fine motor outcome). The central sulcus's shape alone showed a limited but relevant predictive capacity in both cases. The study of sulcal shape features during early neurodevelopment may participate to a better comprehension of the complex links between morphological and functional organization of the developing brain.

Computational models of cortical folding: A review of common approaches

The process of gyrification, by which the brain develops the intricate pattern of gyral hills and sulcal valleys, is the result of interactions between biological and mechanical processes during brain development. Researchers have developed a vast array of computational models in order to investigate cortical folding. This review aims to summarize these studies, focusing on five essential elements of the brain that affect development and gyrification and how they are represented in computational models: (i) the constraints of skull, meninges, and cerebrospinal fluid; (ii) heterogeneity of cortical layers and regions; (iii) anisotropic behavior of subcortical fiber tracts; (iv) material properties of brain tissue; and (v) the complex geometry of the brain. Finally, we highlight areas of need for future simulations of brain development.

Longitudinal Chinese Population Structural Fetal Brain Atlases Construction: toward precise fetal brain segmentation

In magnetic resonance imaging (MRI) studies of fetal brain development, structural brain atlases usually serve as essential references for the fetal population. Individual images are spatially normalized into a common or standard atlas space to extract regional information on volumetric or morphological brain variations. However, the existing fetal brain atlases are mostly based on MR images obtained from Caucasian populations and thus are not ideal for the characterization of the brains of the Chinese population due to neuroanatomical differences related to genetic factors. In this paper, we use an unbiased template construction algorithm to create a set of age-specific Chinese fetal atlases between 21-35 weeks of gestation from 115 normally developing fetal brains. Based on the 4D spatiotemporal atlas, the morphologically developmental patterns, e.g., cortical thickness, sulcal and gyral patterns, were quantified from in utero MRI. Additionally, after applying the Chinese fetal atlases and Caucasian fetal atlases to an independent Chinese pediatric dataset, we find that the Chinese fetal atlases result in significantly higher accuracy than the Caucasian fetal atlases in guiding brain tissue segmentation. These results suggest that the Chinese fetal brain atlases are necessary for quantitative analysis of the typical and atypical development of the Chinese fetal population in the future.

Deciphering and engineering tissue folding: A mechanical perspective

The folding of tissues/organs into complex shapes is a common phenomenon that occurs in organisms such as animals and plants, and is both structurally and functionally important. Deciphering the process of tissue folding and applying this knowledge to engineer folded systems would significantly advance the field of tissue engineering. Although early studies focused on investigating the biochemical signaling events that occur during the folding process, the physical or mechanical aspects of the process have received increasing attention in recent years. In this review, we will summarize recent findings on the mechanical aspects of folding and introduce strategies by which folding can be controlled in vitro. Emphasis will be placed on the folding events triggered by mechanical effects at the cellular and tissue levels and on the different cell- and biomaterial-based approaches used to recapitulate folding. Finally, we will provide a perspective on the development of engineering tissue folding toward preclinical and clinical translation. STATEMENT OF SIGNIFICANCE: Tissue folding is a common phenomenon in a variety of organisms including human, and has been shown to serve important structural and functional roles. Understanding how folding forms and applying the concept in tissue engineering would represent an advance of the research field. Recently, the physical or mechanical aspect of tissue folding has gained increasing attention. In this review, we will cover recent findings of the mechanical aspect of folding mechanisms, and introduce strategies to control the folding process in vitro. We will also provide a perspective on the future development of the field towards preclinical and clinical translation of various bio fabrication technologies.

Simulating Local Deformations in the Human Cortex Due to Blood Flow-Induced Changes in Mechanical Tissue Properties: Impact on Functional Magnetic Resonance Imaging

Investigating human brain tissue is challenging due to the complexity and the manifold interactions between structures across different scales. Increasing evidence suggests that brain function and microstructural features including biomechanical features are related. More importantly, the relationship between tissue mechanics and its influence on brain imaging results remains poorly understood. As an important example, the study of the brain tissue response to blood flow could have important theoretical and experimental consequences for functional magnetic resonance imaging (fMRI) at high spatial resolutions. Computational simulations, using realistic mechanical models can predict and characterize the brain tissue behavior and give us insights into the consequent potential biases or limitations of in vivo, high-resolution fMRI. In this manuscript, we used a two dimensional biomechanical simulation of an exemplary human gyrus to investigate the relationship between mechanical tissue properties and the respective changes induced by focal blood flow changes. The model is based on the changes in the brain’s stiffness and volume due to the vasodilation evoked by neural activity. Modeling an exemplary gyrus from a brain atlas we assessed the influence of different potential mechanisms: (i) a local increase in tissue stiffness (at the level of a single anatomical layer), (ii) an increase in local volume, and (iii) a combination of both effects. Our simulation results showed considerable tissue displacement because of these temporary changes in mechanical properties. We found that the local volume increase causes more deformation and consequently higher displacement of the gyrus. These displacements introduced considerable artifacts in our simulated fMRI measurements. Our results underline the necessity to consider and characterize the tissue displacement which could be responsible for fMRI artifacts.

Using Tertiary Sulci to Map the "Cognitive Globe" of Prefrontal Cortex

Stuss considered the human PFC as a "cognitive globe" [Stuss, D. T., & Benson, D. F. Neuropsychological studies of the frontal lobes. Psychological Bulletin, 95, 3-28, 1984] on which functions of the frontal lobe could be mapped. Here, we discuss classic and recent findings regarding the evolution, development, function, and cognitive role of shallow indentations or tertiary sulci in PFC, with the goal of using tertiary sulci to map the "cognitive globe" of PFC. First, we discuss lateral PFC (LPFC) tertiary sulci in classical anatomy and modern neuroimaging, as well as their development, with a focus on those within the middle frontal gyrus. Second, we discuss tertiary sulci in comparative neuroanatomy, focusing on primates. Third, we summarize recent findings showing the utility of tertiary sulci for understanding structural-functional relationships with functional network insights in ventromedial PFC and LPFC. Fourth, we revisit and update unresolved theoretical perspectives considered by C. Vogt and O. Vogt (Allgemeinere ergebnisse unserer hirnforschung. Journal für Psychologie und Neurologie, 25, 279-462, 1919) and F. Sanides (Structure and function of the human frontal lobe. Neuropsychologia, 2, 209-219, 1964) that tertiary sulci serve as landmarks for cortical gradients. Together, the consideration of these classic and recent findings indicate that tertiary sulci are situated in a unique position within the complexity of the "cognitive globe" of PFC: They are the smallest and shallowest of sulci in PFC, yet can offer insights that bridge spatial scales (microns to networks), modalities (functional connectivity to behavior), and species. As such, the map of tertiary sulci within each individual participant serves as a coordinate system specific to that individual on which functions may be further mapped. We conclude with new theoretical and methodological questions that, if answered in future research, will likely lead to mechanistic insight regarding the structure and function of human LPFC.

Enhanced detection of cortical atrophy in Alzheimer's disease using structural MRI with anatomically constrained longitudinal registration

Cortical atrophy is a defining feature of Alzheimer's disease (AD), often detectable before symptoms arise. In surface-based analyses, studies have commonly focused on cortical thinning while overlooking the impact of loss in surface area. To capture the impact of both cortical thinning and surface area loss, we used anatomically constrained Multimodal Surface Matching (aMSM), a recently developed tool for mapping change in surface area. We examined cortical atrophy over 2 years in cognitively normal subjects and subjects with diagnoses of stable mild cognitive impairment, mild cognitive impairment that converted to AD, and AD. Magnetic resonance imaging scans were segmented and registered to a common atlas using previously described techniques (FreeSurfer and ciftify), then longitudinally registered with aMSM. Changes in cortical thickness, surface area, and volume were mapped within each diagnostic group, and groups were compared statistically. Changes in thickness and surface area detected atrophy at similar levels of significance, though regions of atrophy somewhat differed. Furthermore, we found that surface area maps offered greater consistency across scanners (3.0 vs. 1.5 T). Comparisons to the FreeSurfer longitudinal pipeline and parcellation-based (region-of-interest) analysis suggest that aMSM may allow more robust detection of atrophy, particularly in earlier disease stages and using smaller sample sizes.

Age-specific structural fetal brain atlases construction and cortical development quantification for chinese population

In magnetic resonance imaging (MRI) studies of fetal brain development, structural brain atlases usually serve as essential references for the fetal population. Individual images are usually normalized into a common or standard space for analysis. However, the existing fetal brain atlases are mostly based on MR images obtained from Caucasian populations and thus are not ideal for the characterization of the fetal Chinese population due to neuroanatomical differences related to genetic factors. In this paper, we use an unbiased template construction algorithm to create a set of age-specific Chinese fetal atlases between 21-35 weeks of gestation from 115 normal fetal brains. Based on the 4D spatiotemporal atlas, the morphological development patterns, e.g., cortical thickness, cortical surface area, sulcal and gyral patterns, were quantified. The fetal brain abnormalities were detected when referencing the age-specific template. Additionally, a direct comparison of the Chinese fetal atlases and Caucasian fetal atlases reveals dramatic anatomical differences, mainly in the medial frontal and temporal regions. After applying the Chinese and Caucasian fetal atlases separately to an independent Chinese fetal brain dataset, we find that the Chinese fetal atlases result in significantly higher accuracy than the Caucasian fetal atlases in guiding brain tissue segmentation. These results suggest that the Chinese fetal brain atlases are necessary for quantitative analysis of the typical and atypical development of the Chinese fetal population in the future. The atlases with their parcellations are now publicly available at https://github.com/DeepBMI/FBA-Chinese.

Brain Shape Changes Associated With Cerebral Atrophy in Healthy Aging and Alzheimer's Disease

Both healthy and pathological brain aging are characterized by various degrees of cognitive decline that strongly correlate with morphological changes referred to as cerebral atrophy. These hallmark morphological changes include cortical thinning, white and gray matter volume loss, ventricular enlargement, and loss of gyrification all caused by a myriad of subcellular and cellular aging processes. While the biology of brain aging has been investigated extensively, the mechanics of brain aging remains vastly understudied. Here, we propose a multiphysics model that couples tissue atrophy and Alzheimer's disease biomarker progression. We adopt the multiplicative split of the deformation gradient into a shrinking and an elastic part. We model atrophy as region-specific isotropic shrinking and differentiate between a constant, tissue-dependent atrophy rate in healthy aging, and an atrophy rate in Alzheimer's disease that is proportional to the local biomarker concentration. Our finite element modeling approach delivers a computational framework to systematically study the spatiotemporal progression of cerebral atrophy and its regional effect on brain shape. We verify our results via comparison with cross-sectional medical imaging studies that reveal persistent age-related atrophy patterns. Our long-term goal is to develop a diagnostic tool able to differentiate between healthy and accelerated aging, typically observed in Alzheimer's disease and related dementias, in order to allow for earlier and more effective interventions.

The One-Stop Gyrification Station - Challenges and New Technologies

The evolution of the folded cortical surface is an iconic feature of the human brain shared by a subset of mammals and considered pivotal for the emergence of higher-order cognitive functions. While our understanding of the neurodevelopmental processes involved in corticogenesis has greatly advanced over the past 70 years of brain research, the fundamental mechanisms that result in gyrification, along with its originating cytoarchitectural location, remain largely unknown. This review brings together numerous approaches to this basic neurodevelopmental problem, constructing a narrative of how various models, techniques and tools have been applied to the study of gyrification thus far. After a brief discussion of core concepts and challenges within the field, we provide an analysis of the significant discoveries derived from the parallel use of model organisms such as the mouse, ferret, sheep and non-human primates, particularly with regard to how they have shaped our understanding of cortical folding. We then focus on the latest developments in the field and the complementary application of newly emerging technologies, such as cerebral organoids, advanced neuroimaging techniques, and atomic force microscopy. Particular emphasis is placed upon the use of novel computational and physical models in regard to the interplay of biological and physical forces in cortical folding.

Geometric deep learning on brain shape predicts sex and age

The complex relationship between the shape and function of the human brain remains elusive despite extensive studies of cortical folding over many decades. The analysis of cortical gyrification presents an opportunity to advance our knowledge about this relationship, and better understand the etiology of a variety of pathologies involving diverse degrees of cortical folding abnormalities. Hypothesis-driven surface-based approaches have been shown to be particularly efficient in their ability to accurately describe unique features of the folded sheet topology of the cortical ribbon. However, the utility of these approaches has been blunted by their reliance on manually defined features aiming to capture the relevant geometric properties of cortical folding. In this paper, we propose an entirely novel, data-driven deep-learning based method to analyze the brain's shape that eliminates this reliance on manual feature definition. This method builds on the emerging field of geometric deep-learning and uses traditional convolutional neural network architecture uniquely adapted to the surface representation of the cortical ribbon. This method is a complete departure from prior brain MRI CNN investigations, all of which have relied on three dimensional MRI data and interpreted features of the MRI signal for prediction. MRI data from 6410 healthy subjects obtained from 11 publicly available data repositories were used for analysis. Ages ranged from 6 to 89 years. Both inner and outer cortical surfaces were extracted using Freesurfer and then registered into MNI space. For purposes of method development, both a classification and regression challenge were introduced for network learning including sex and age prediction, respectively. Two independent graph convolutional neural networks (gCNNs) were trained, the first of which to predict subject's self-identified sex, the second of which to predict subject's age. Class Activation Maps (CAM) and Regression Activation Maps (RAM) were constructed respectively to map the topographic distribution of the most influential brain regions involved in the decision process for each gCNN. Using this approach, the gCNN was able to predict a subject's sex with an average accuracy of 87.99 % and achieved a Person's coefficient of correlation of 0.93 with an average absolute error 4.58 years when predicting a subject's age. We believe this shape-based convolutional classifier offers a novel, data-driven approach to define biomedically relevant features from the brain at both the population and single subject levels and therefore lays a critical foundation for future precision medicine applications.

Surface-based Cortical Morphometry, White Matter Hyperintensity, and Multidomain Cognitive Performance in Asymptomatic Carotid Stenosis

Carotid stenosis is a major contributor to vascular dementia. Recent studies suggest that even clinically "asymptomatic" carotid stenosis is linked with cognitive decline and neuroimaging changes. Here we examined surface-based cortical morphometry, white matter hyperintensity (WMH), and multidomain cognitive performance in unilateral severe (>70% narrowing) asymptomatic carotid stenosis (SACS). We included 24 SACS patients (19 males/5 females; 64.25 ± 7.18 years) and 24 comorbidities-matched controls (19 males/5 females; 67.16 ± 6.10 years), and measured cortical thickness, sulcal depth, gyrification, cortical complexity, and WMH loads with structural MRI images. The SACS patients exhibited: (1) thinner cortex in bilateral somatosensory/motor, bilateral inferior frontal, bilateral fusiform, and left lateral temporal areas; (2) shallower sulci in left lateral temporal, parietal, insular and somatosensory/motor areas; (3) both hyper- and hypo-gyrification in lateral temporal and frontal cortices; (4) lower complexity (fractal dimension) in left insular and right superior temporal areas. Further association analyses showed that the cortical alterations were significantly correlated with verbal memory and WMH burden in SACS. These results suggest that SACS patients present a left-dominated damage tendency, especially in the Perisylvian cortices that span across several large-scale systems of somatosensory/motor and language. Our findings also provide cortical anatomy evidence for cognitive impairment in SACS, suggesting a neuroanatomical predisposition to dementia and cerebrovascular events.

Morphological Development Trajectory and Structural Covariance Network of the Human Fetal Cortical Plate during the Early Second Trimester

During the early second trimester, the cortical plate, or "the developing cortex", undergoes immensely complex and rapid development to complete its major complement of neurons. However, morphological development of the cortical plate and the precise patterning of brain structural covariance networks during this period remain unexplored. In this study, we used 7.0 T high-resolution magnetic resonance images of brain specimens ranging from 14 to 22 gestational weeks to manually segment the cortical plate. Thickness, area expansion, and curvature (i.e., folding) across the cortical plate regions were computed, and correlations of thickness values among different cortical plate regions were measured to analyze fetal cortico-cortical structural covariance throughout development of the early second trimester. The cortical plate displayed significant increases in thickness and expansions in area throughout all regions but changes of curvature in only certain major sulci. The topological architecture and network properties of fetal brain covariance presented immature and inefficient organizations with low degree of integration and high degree of segregation. Altogether, our results provide novel insight on the developmental patterning of cortical plate thickness and the developmental origin of brain network architecture throughout the early second trimester.

MRI of the Neonatal Brain: A Review of Methodological Challenges and Neuroscientific Advances

In recent years, exploration of the developing brain has become a major focus for researchers and clinicians in an attempt to understand what allows children to acquire amazing and unique abilities, as well as the impact of early disruptions (eg, prematurity, neonatal insults) that can lead to a wide range of neurodevelopmental disorders. Noninvasive neuroimaging methods such as MRI are essential to establish links between the brain and behavioral changes in newborns and infants. In this review article, we aim to highlight recent and representative studies using the various techniques available: anatomical MRI, quantitative MRI (relaxometry, diffusion MRI), multiparametric approaches, and functional MRI. Today, protocols use 1.5 or 3T MRI scanners, and specialized methodologies have been put in place for data acquisition and processing to address the methodological challenges specific to this population, such as sensitivity to motion. MR sequences must be adapted to the brains of newborns and infants to obtain relevant good soft-tissue contrast, given the small size of the cerebral structures and the incomplete maturation of tissues. The use of age-specific image postprocessing tools is also essential, as signal and contrast differ from the adult brain. Appropriate methodologies then make it possible to explore multiple neurodevelopmental mechanisms in a precise way, and assess changes with age or differences between groups of subjects, particularly through large-scale projects. Although MRI measurements only indirectly reflect the complex series of dynamic processes observed throughout development at the molecular and cellular levels, this technique can provide information on brain morphology, structural connectivity, microstructural properties of gray and white matter, and on the functional architecture. Finally, MRI measures related to clinical, behavioral, and electrophysiological markers have a key role to play from a diagnostic and prognostic perspective in the implementation of early interventions to avoid long-term disabilities in children. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY STAGE: 1.

Growth and form, Lie algebras and special functions

The formation of a biological organism, or an organ within it, can often be regarded as the unfolding of successive equilibria of a mechanical system. In a mathematical model, these changes of equilibria may be considered to be responses of mechanically constrained systems to a change of a reference configuration and of a reference metric, which are in turn driven by genes and their expression. This paper brings together three major threads of research. These are: Lie-type symmetries of equations; models as well as data on growth and pattern formation; and the relation between Lie algebras (and groups) and special functions associated with them. We show that symmetry methods can be generalized to map between solutions to models with different reference metrics. In the case in which we attempt to obtain such equations, they seem too complicated to be of any immediate service to the community of researchers on cortical growth. However, models and data on growth may be used to obtain generators of these Lie algebras empirically and numerically. These generators result in new classes of special functions. The paper is an invitation to develop what we may call empirical Lie algebras and associated functions. The hypothesis that remains to be tested is whether the confluence of ideas described in the paper, namely the Lie algebraic-related consequences of pattern formation and growth, prove useful for deepened understanding of biological growth patterns.

The influence of biophysical parameters in a biomechanical model of cortical folding patterns

Abnormal cortical folding patterns, such as lissencephaly, pachygyria and polymicrogyria malformations, may be related to neurodevelopmental disorders. In this context, computational modeling is a powerful tool to provide a better understanding of the early brain folding process. Recent studies based on biomechanical modeling have shown that mechanical forces play a crucial role in the formation of cortical convolutions. However, the effect of biophysical parameters in these models remain unclear. In this paper, we investigate the effect of the cortical growth, the initial geometry and the initial cortical thickness on folding patterns. In addition, we not only use several descriptors of the folds such as the dimensionless mean curvature, the surface-based three-dimensional gyrification index and the sulcal depth, but also propose a new metric to quantify the folds orientation. The results demonstrate that the cortical growth mode does almost not affect the complexity degree of surface morphology; the variation in the initial geometry changes the folds orientation and depth, and in particular, the slenderer the shape is, the more folds along its longest axis could be seen and the deeper the sulci become. Moreover, the thinner the initial cortical thickness is, the higher the spatial frequency of the folds is, but the shallower the sulci become, which is in agreement with the previously reported effects of cortical thickness.

An inverse modelling study on the local volume changes during early morphoelastic growth of the fetal human brain

We take a data-driven approach to deducing the local volume changes accompanying early development of the fetal human brain. Our approach uses fetal brain atlas MRI data for the geometric changes in representative cases. Using a nonlinear continuum mechanics model of morphoelastic growth, we invert the deformation obtained from MRI registration to arrive at a field for the growth deformation gradient tensor. Our field inversion uses a combination of direct and adjoint methods for computing gradients of the objective function while constraining the optimization by the physics of morphoelastic growth. We thus infer a growth deformation gradient field that obeys the laws of morphoelastic growth. The errors between the MRI data and the forward displacement solution driven by the inverted growth deformation gradient field are found to be smaller than the reference displacement by well over an order of magnitude, and can be driven even lower. The results thus reproduce the three-dimensional growth during the early development of the fetal brain with controllable error. Our findings confirm that early growth is dominated by in plane cortical expansion rather than thickness increase.