Mechanics of cortical folding: stress, growth and stability

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.

A bimodal taxonomy of adult human brain sulcal morphology related to timing of fetal sulcation and trans-sulcal gene expression gradients

We developed a computational pipeline (now provided as a resource) for measuring morphological similarity between cortical surface sulci to construct a sulcal phenotype network (SPN) from each magnetic resonance imaging (MRI) scan in an adult cohort (n = 34,725; 45-82 years). Networks estimated from pairwise similarities of 40 sulci on 5 morphological metrics comprised two clusters of sulci, represented also by the bimodal distribution of sulci on a linear-to-complex dimension. Linear sulci were more heritable and typically located in unimodal cortex, and complex sulci were less heritable and typically located in heteromodal cortex. Aligning these results with an independent fetal brain MRI cohort (n = 228; 21-36 gestational weeks), we found that linear sulci formed earlier, and the earliest and latest-forming sulci had the least between-adult variation. Using high-resolution maps of cortical gene expression, we found that linear sulcation is mechanistically underpinned by trans-sulcal gene expression gradients enriched for developmental processes.

Superior temporal sulcus folding, functional network connectivity, and autistic-like traits in a non-clinical population

BACKGROUND

Autistic-like traits (ALT) are prevalent across the general population and might be linked to some facets of a broader autism spectrum disorder (ASD) phenotype. Recent studies suggest an association of these traits with both genetic and brain structural markers in non-autistic individuals, showing similar spatial location of findings observed in ASD and thus suggesting a potential neurobiological continuum.

METHODS

In this study, we first tested an association of ALTs (assessed with the AQ questionnaire) with cortical complexity, a cortical surface marker of early neurodevelopment, and then the association with disrupted functional connectivity. We analysed structural T1-weighted and resting-state functional MRI scans in 250 psychiatrically healthy individuals without a history of early developmental disorders, in a first step using the CAT12 toolbox for cortical complexity analysis and in a second step we used regional cortical complexity findings to apply the CONN toolbox for seed-based functional connectivity analysis.

RESULTS

Our findings show a significant negative correlation of both AQ total and AQ attention switching subscores with left superior temporal sulcus (STS) cortical folding complexity, with the former being significantly correlated with STS to left lateral occipital cortex connectivity, while the latter showed significant positive correlation of STS to left inferior/middle frontal gyrus connectivity (n = 233; all p < 0.05, FWE cluster-level corrected). Additional analyses also revealed a significant correlation of AQ attention to detail subscores with STS to left lateral occipital cortex connectivity.

LIMITATIONS

Phenotyping might affect association results (e.g. choice of inventories); in addition, our study was limited to subclinical expressions of autistic-like traits.

CONCLUSIONS

Our findings provide further evidence for biological correlates of ALT even in the absence of clinical ASD, while establishing a link between structural variation of early developmental origin and functional connectivity.

Structural Magnetic Resonance Imaging-Based Surface Morphometry Analysis of Pediatric Down Syndrome

Down syndrome (DS) is a genetic disorder characterized by intellectual disability whose etiology includes an additional partial or full copy of chromosome 21. Brain surface morphometry analyses can potentially assist in providing a better understanding of structural brain differences, and may help characterize DS-specific neurodevelopment. We performed a retrospective surface morphometry study of 73 magnetic resonance imaging (MRI) examinations of DS patients (aged 1 day to 22 years) and compared them to a large cohort of 993 brain MRI examinations of neurotypical participants, aged 1 day to 32 years. Surface curvature measurements, absolute surface area measurements, and surface areas as a percentage of total brain surface area (%TBSA) were extracted from each brain region in each examination. Results demonstrate broad reductions in surface area and abnormalities of surface curvature measurements across the brain in DS. After adjusting our regional surface area measurements as %TBSA, abnormally increased presentation in DS relative to neurotypical controls was observed in the left precentral, bilateral entorhinal, left parahippocampal, and bilateral perirhinal cortices, as well as Brodmann's area 44 (left), and the right temporal pole. Findings suggest the presence of developmental abnormalities of regional %TBSA in DS that can be characterized from clinical MRI examinations.

Design of neural organoids engineered by mechanical forces

Neural organoids consist of three-dimensional tissue derived from pluripotent stem cells that could recapitulate key features of the human brain. During the past decade, organoid technology has evolved in the field of human brain science by increasing the quality and applicability of its products. Among them, a novel approach involving the design of neural organoids engineered by mechanical forces has emerged. This review describes previous approaches for the generation of neural organoids, the engineering of neural organoids by mechanical forces, and future challenges for the application of mechanical forces in the design of neural organoids.

A mechanical transition from tension to buckling underlies the jigsaw puzzle shape morphogenesis of histoblasts in the Drosophila epidermis

The polygonal shape of cells in proliferating epithelia is a result of the tensile forces of the cytoskeletal cortex and packing geometry set by the cell cycle. In the larval Drosophila epidermis, two cell populations, histoblasts and larval epithelial cells, compete for space as they grow on a limited body surface. They do so in the absence of cell divisions. We report a striking morphological transition of histoblasts during larval development, where they change from a tensed network configuration with straight cell outlines at the level of adherens junctions to a highly folded morphology. The apical surface of histoblasts shrinks while their growing adherens junctions fold, forming deep lobules. Volume increase of growing histoblasts is accommodated basally, compensating for the shrinking apical area. The folded geometry of apical junctions resembles elastic buckling, and we show that the imbalance between the shrinkage of the apical domain of histoblasts and the continuous growth of junctions triggers buckling. Our model is supported by laser dissections and optical tweezer experiments together with computer simulations. Our analysis pinpoints the ability of histoblasts to store mechanical energy to a much greater extent than most other epithelial cell types investigated so far, while retaining the ability to dissipate stress on the hours time scale. Finally, we propose a possible mechanism for size regulation of histoblast apical size through the lateral pressure of the epidermis, driven by the growth of cells on a limited surface. Buckling effectively compacts histoblasts at their apical plane and may serve to avoid physical harm to these adult epidermis precursors during larval life. Our work indicates that in growing nondividing cells, compressive forces, instead of tension, may drive cell morphology.

Growth directions and stiffness across cell layers determine whether tissues stay smooth or buckle

From smooth to buckled, nature exhibits organs of various shapes and forms. How cellular growth patterns produce smooth organ shapes such as leaves and sepals remains unclear. Here we show that unidirectional growth and comparable stiffness across both epidermal layers of Arabidopsis sepals are essential for smoothness. We identified a mutant with ectopic ASYMMETRIC LEAVES 2 (AS2) expression on the outer epidermis. Our analysis reveals that ectopic AS2 expression causes outer epidermal buckling at early stages of sepal development, due to conflicting growth directions and unequal epidermal stiffnesses. Aligning growth direction and increasing stiffness of the outer epidermis restores smoothness. Furthermore, buckling influences auxin efflux transporter protein PIN-FORMED 1 polarity to generate outgrowth in the later stages, suggesting that buckling is sufficient to initiate outgrowths. Our findings suggest that in addition to molecular cues influencing tissue mechanics, tissue mechanics can also modulate molecular signals, giving rise to well-defined shapes.

Axonal tension contributes to consistent fold placement

Cortical folding is a critical process during brain development, resulting in morphologies that are both consistent and distinct between individuals and species. While earlier studies have highlighted important aspects of cortical folding, most existing computational models, based on the differential growth theory, fall short of explaining why folds tend to appear in particular locations. The axon tension hypothesis may provide insight into this conundrum; however, there has been significant controversy about a potential role of axonal tension during the gyrification. The common opinion in the field is that axonal tension is inadequate to drive gyrification, but we currently run the risk of discarding this hypothesis without comprehensively studying the role of axonal tension. Here we propose a novel bi-layered finite element model incorporating the two theories, including characteristic axonal tension in the subcortex and differential cortical growth. We show that axon tension can serve as a perturbation sufficient to trigger buckling in simulations; similarly to other types of perturbations, the natural stability behavior of the system tends to determine some characteristics of the folding morphology (e.g. the wavelength) while the perturbation determines the location of folds. Certain geometries, however, can interact or compete with the natural stability of the system to change the wavelength. When multiple perturbations are present, they similarly compete with each other. We found that an axon bundle of reasonable size will overpower up to a 5% thickness perturbation (typical in the literature) and determine fold placement. Finally, when multiple axon tracts are present, even a slight difference in axon stiffness, representing the heterogeneity of axonal connections, is enough to significantly change the folding pattern. While the simulations presented here are a very simple representation of white matter connectivity, our findings point to urgent future research on the role of axon connectivity in cortical folding.

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.

Ventral temporal and posteromedial sulcal morphology in autism spectrum disorder

Two parallel research tracks link the morphology of small and shallow indentations, or sulci, of the cerebral cortex with functional features of the cortex and human cognition, respectively. The first track identified a relationship between the mid-fusiform sulcus (MFS) in ventral temporal cortex (VTC) and cognition in individuals with Autism Spectrum Disorder (ASD). The second track identified a new sulcus, the inframarginal sulcus (IFRMS), that serves as a tripartite landmark within the posteromedial cortex (PMC). As VTC and PMC are structurally and functionally different in ASD, here, we integrated these two tracks and tested if there are morphological differences in VTC and PMC sulci in a sample of young (5-17 years old) male participants (50 participants with ASD and 50 neurotypical controls). Our approach replicates and extends recent findings in four ways. First, regarding replication, the standard deviation (STD) of MFS cortical thickness (CT) was increased in ASD. Second, MFS length was shorter in ASD. Third, the CT STD effect extended to other VTC and to PMC sulci. Fourth, additional morphological features of VTC sulci (depth, surface area, gray matter volume) and PMC sulci (mean CT) were decreased in ASD, including putative tertiary sulci, which emerge last in gestation and continue to develop after birth. To our knowledge, this study is the most extensive comparison of the sulcal landscape (including putative tertiary sulci) in multiple cortical expanses between individuals with ASD and NTs based on manually defined sulci at the level of individual hemispheres, providing novel targets for future studies of neurodevelopmental disorders more broadly.

Sulcal variability in anterior lateral prefrontal cortex contributes to variability in reasoning performance among young adults

Identifying structure-function correspondences is a major goal among biologists, cognitive neuroscientists, and brain mappers. Recent studies have identified relationships between performance on cognitive tasks and the presence or absence of small, shallow indentations, or sulci, of the human brain. Building on the previous finding that the presence of the ventral para-intermediate frontal sulcus (pimfs-v) in the left anterior lateral prefrontal cortex (aLPFC) was related to reasoning task performance in children and adolescents, we tested whether this relationship extended to a different sample, age group, and reasoning task. As predicted, the presence of this aLPFC sulcus was also associated with higher reasoning scores in young adults (ages 22-36). These findings have not only direct developmental, but also evolutionary relevance-as recent work shows that the pimfs-v is exceedingly rare in chimpanzees. Thus, the pimfs-v is a key developmental, cognitive, and evolutionarily relevant feature that should be considered in future studies examining how the complex relationships among multiscale anatomical and functional features of the brain give rise to abstract thought.

Mechanics in the nervous system: From development to disease

Physical forces are ubiquitous in biological processes across scales and diverse contexts. This review highlights the significance of mechanical forces in nervous system development, homeostasis, and disease. We provide an overview of mechanical signals present in the nervous system and delve into mechanotransduction mechanisms translating these mechanical cues into biochemical signals. During development, mechanical cues regulate a plethora of processes, including cell proliferation, differentiation, migration, network formation, and cortex folding. Forces then continue exerting their influence on physiological processes, such as neuronal activity, glial cell function, and the interplay between these different cell types. Notably, changes in tissue mechanics manifest in neurodegenerative diseases and brain tumors, potentially offering new diagnostic and therapeutic target opportunities. Understanding the role of cellular forces and tissue mechanics in nervous system physiology and pathology adds a new facet to neurobiology, shedding new light on many processes that remain incompletely understood.

Using dropout based active learning and surrogate models in the inverse viscoelastic parameter identification of human brain tissue

Inverse mechanical parameter identification enables the characterization of ultrasoft materials, for which it is difficult to achieve homogeneous deformation states. However, this usually involves high computational costs that are mainly determined by the complexity of the forward model. While simulation methods like finite element models can capture nearly arbitrary geometries and implement involved constitutive equations, they are also computationally expensive. Machine learning models, such as neural networks, can help mitigate this problem when they are used as surrogate models replacing the complex high fidelity models. Thereby, they serve as a reduced order model after an initial training phase, where they learn the relation of in- and outputs of the high fidelity model. The generation of the required training data is computationally expensive due to the necessary simulation runs. Here, active learning techniques enable the selection of the "most rewarding" training points in terms of estimated gained accuracy for the trained model. In this work, we present a recurrent neural network that can well approximate the output of a viscoelastic finite element simulation while significantly speeding up the evaluation times. Additionally, we use Monte-Carlo dropout based active learning to identify highly informative training data. Finally, we showcase the potential of the developed pipeline by identifying viscoelastic material parameters for human brain tissue.

H3 Acetylation-Induced Basal Progenitor Generation and Neocortex Expansion Depends on the Transcription Factor Pax6

Enrichment of basal progenitors (BPs) in the developing neocortex is a central driver of cortical enlargement. The transcription factor Pax6 is known as an essential regulator in generation of BPs. H3 lysine 9 acetylation (H3K9ac) has emerged as a crucial epigenetic mechanism that activates the gene expression program required for BP pool amplification. In this current work, we applied immunohistochemistry, RNA sequencing, chromatin immunoprecipitation and sequencing, and the yeast two-hybrid assay to reveal that the BP-genic effect of H3 acetylation is dependent on Pax6 functionality in the developing mouse cortex. In the presence of Pax6, increased H3 acetylation caused BP pool expansion, leading to enhanced neurogenesis, which evoked expansion and quasi-convolution of the mouse neocortex. Interestingly, H3 acetylation activation exacerbates the BP depletion and corticogenesis reduction effect of Pax6 ablation in cortex-specific Pax6 mutants. Furthermore, we found that H3K9 acetyltransferase KAT2A/GCN5 interacts with Pax6 and potentiates Pax6-dependent transcriptional activity. This explains a genome-wide lack of H3K9ac, especially in the promoter regions of BP-genic genes, in the Pax6 mutant cortex. Together, these findings reveal a mechanistic coupling of H3 acetylation and Pax6 in orchestrating BP production and cortical expansion through the promotion of a BP gene expression program during cortical development.

A bipolar taxonomy of adult human brain sulcal morphology related to timing of fetal sulcation and trans-sulcal gene expression gradients

We developed a computational pipeline (now provided as a resource) for measuring morphological similarity between cortical surface sulci to construct a sulcal phenotype network (SPN) from each magnetic resonance imaging (MRI) scan in an adult cohort (N=34,725; 45-82 years). Networks estimated from pairwise similarities of 40 sulci on 5 morphological metrics comprised two clusters of sulci, represented also by the bipolar distribution of sulci on a linear-to-complex dimension. Linear sulci were more heritable and typically located in unimodal cortex; complex sulci were less heritable and typically located in heteromodal cortex. Aligning these results with an independent fetal brain MRI cohort (N=228; 21-36 gestational weeks), we found that linear sulci formed earlier, and the earliest and latest-forming sulci had the least between-adult variation. Using high-resolution maps of cortical gene expression, we found that linear sulcation is mechanistically underpinned by trans-sulcal gene expression gradients enriched for developmental processes.

Geometry-structure models for liquid crystal interfaces, drops and membranes: wrinkling, shape selection and dissipative shape evolution

We review our recent contributions to anisotropic soft matter models for liquid crystal interfaces, drops and membranes, emphasizing validations with experimental and biological data, and with related theory and simulation literature. The presentation aims to illustrate and characterize the rich output and future opportunities of using a methodology based on the liquid crystal-membrane shape equation applied to static and dynamic pattern formation phenomena. The geometry of static and kinetic shapes is usually described with dimensional curvatures that co-mingle shape and curvedness. In this review, we systematically show how the application of a novel decoupled shape-curvedness framework to practical and ubiquitous soft matter phenomena, such as the shape of drops and tactoids and bending of evolving membranes, leads to deeper quantitative insights than when using traditional dimensional mean and Gaussian curvatures. The review focuses only on (1) statics of wrinkling and shape selection in liquid crystal interfaces and membranes; (2) kinetics and dissipative dynamics of shape evolution in membranes; and (3) computational methods for shape selection and shape evolution; due to various limitations other important topics are excluded. Finally, the outlook follows a similar structure. The main results include: (1) single and multiple wavelength corrugations in liquid crystal interfaces appear naturally in the presence of surface splay and bend orientation distortions with scaling laws governed by ratios of anchoring-to-isotropic tension energy; adding membrane elasticity to liquid crystal anchoring generates multiple scales wrinkling as in tulips; drops of liquid crystals encapsulates in membranes can adopt, according to the ratios of anchoring/tension/bending, families of shapes as multilobal, tactoidal, and serrated as observed in biological cells. (2) Mapping the liquid crystal director to a membrane unit normal. The dissipative shape evolution model with irreversible thermodynamics for flows dominated by bending rates, yields new insights. The model explains the kinetic stability of cylinders, while spheres and saddles are attractors. The model also adds to the evolving understanding of outer hair cells in the inner ear. (3) Computational soft matter geometry includes solving shape equations, trajectories on energy and orientation landscapes, and shape-curvedness evolutions on entropy production landscape with efficient numerical methods and adaptive approaches.

Multi-scale measurement of stiffness in the developing ferret brain

Cortical folding is an important process during brain development, and aberrant folding is linked to disorders such as autism and schizophrenia. Changes in cell numbers, size, and morphology have been proposed to exert forces that control the folding process, but these changes may also influence the mechanical properties of developing brain tissue. Currently, the changes in tissue stiffness during brain folding are unknown. Here, we report stiffness in the developing ferret brain across multiple length scales, emphasizing changes in folding cortical tissue. Using rheometry to measure the bulk properties of brain tissue, we found that overall brain stiffness increases with age over the period of cortical folding. Using atomic force microscopy to target the cortical plate, we found that the occipital cortex increases in stiffness as well as stiffness heterogeneity over the course of development and folding. These findings can help to elucidate the mechanics of the cortical folding process by clarifying the concurrent evolution of tissue properties.

Anatomical correlates and nomenclature of the chiropteran endocranial cast

Bats form a diverse group of mammals that are highly specialized in active flight and ultrasound echolocation. These specializations rely on adaptations that reflect on their morphoanatomy and have been tentatively linked to brain morphology and volumetry. Despite their small size and fragility, bat crania and natural braincase casts ("endocasts") have been preserved in the fossil record, which allows for investigating brain evolution and inferring paleobiology. Advances in imaging techniques have allowed virtual extraction of internal structures, assuming that the shape of the endocast reflects soft organ morphology. However, there is no direct correspondence between the endocast and internal structures because meninges and vascular tissues mark the inner braincase together with the brain they surround, resulting in a mosaic morphology of the endocast. The hypothesis suggesting that the endocast reflects the brain in terms of both external shape and volume has drastic implications when addressing brain evolution, but it has been rarely discussed. To date, only a single study addressed the correspondence between the brain and braincase in bats. Taking advantage of the advent of imaging techniques, we reviewed the anatomical, neuroanatomical, and angiological literature and compare this knowledge available on bat's braincase anatomy with anatomical observations using a sample of endocranial casts representing most modern bat families. Such comparison allows to propose a Chiroptera-scale nomenclature for future descriptions and comparisons among bat endocasts. Describing the imprints of the tissues surrounding the brain also allows to address to what extent brain features can be blurred or hidden (e.g., hypophysis, epiphysis, colliculi, flocculus). Furthermore, this approach encourages further study to formally test the proposed hypotheses.

DNA damage and repair: underlying mechanisms leading to microcephaly

DNA-damaging agents and endogenous DNA damage constantly harm genome integrity. Under genotoxic stress conditions, the DNA damage response (DDR) machinery is crucial in repairing lesions and preventing mutations in the basic structure of the DNA. Different repair pathways are implicated in the resolution of such lesions. For instance, the non-homologous DNA end joining and homologous recombination pathways are central cellular mechanisms by which eukaryotic cells maintain genome integrity. However, defects in these pathways are often associated with neurological disorders, indicating the pivotal role of DDR in normal brain development. Moreover, the brain is the most sensitive organ affected by DNA-damaging agents compared to other tissues during the prenatal period. The accumulation of lesions is believed to induce cell death, reduce proliferation and premature differentiation of neural stem and progenitor cells, and reduce brain size (microcephaly). Microcephaly is mainly caused by genetic mutations, especially genes encoding proteins involved in centrosomes and DNA repair pathways. However, it can also be induced by exposure to ionizing radiation and intrauterine infections such as the Zika virus. This review explains mammalian cortical development and the major DNA repair pathways that may lead to microcephaly when impaired. Next, we discuss the mechanisms and possible exposures leading to DNA damage and p53 hyperactivation culminating in microcephaly.

Aberrant pace of cortical neuron development in brain organoids from patients with 22q11.2 deletion syndrome and schizophrenia

Adults and children afflicted with the 22q11.2 deletion syndrome (22q11.2DS) exhibit cognitive, social, and emotional impairments, and are at significantly heightened risk for schizophrenia (SCZ). The impact of this deletion on early human brain development, however, has remained unclear. Here we harness organoid models of the developing human cerebral cortex, cultivated from subjects with 22q11.2DS and SCZ, as well as unaffected control samples, to identify cell-type-specific developmental abnormalities arising from this genomic lesion. Leveraging single-cell RNA-sequencing in conjunction with experimental validation, we find that the loss of genes within the 22q11.2 locus leads to a delayed development of cortical neurons. This compromised development was reflected in an elevated proportion of actively proliferating neural progenitor cells, coupled with a decreased fraction of more mature neurons. Furthermore, we identify perturbed molecular imprints linked to neuronal maturation, observe the presence of sparser neurites, and note a blunted amplitude in glutamate-induced Ca2+ transients. The aberrant transcription program underlying impaired development contains molecular signatures significantly enriched in neuropsychiatric genetic liability. MicroRNA profiling and target gene investigation suggest that microRNA dysregulation may drive perturbations of genes governing the pace at which maturation unfolds. Using protein-protein interaction network analysis we define complementary effects stemming from additional genes residing within the deleted locus. Our study uncovers reproducible neurodevelopmental and molecular alterations due to 22q11.2 deletions. These findings have the potential to facilitate disease modeling and promote the pursuit of therapeutic interventions.

Inverse identification of region-specific hyperelastic material parameters for human brain tissue

The identification of material parameters accurately describing the region-dependent mechanical behavior of human brain tissue is crucial for computational models used to assist, e.g., the development of safety equipment like helmets or the planning and execution of brain surgery. While the division of the human brain into different anatomical regions is well established, knowledge about regions with distinct mechanical properties remains limited. Here, we establish an inverse parameter identification scheme using a hyperelastic Ogden model and experimental data from multi-modal testing of tissue from 19 anatomical human brain regions to identify mechanically distinct regions and provide the corresponding material parameters. We assign the 19 anatomical regions to nine governing regions based on similar parameters and microstructures. Statistical analyses confirm differences between the regions and indicate that at least the corpus callosum and the corona radiata should be assigned different material parameters in computational models of the human brain. We provide a total of four parameter sets based on the two initial Poisson's ratios of 0.45 and 0.49 as well as the pre- and unconditioned experimental responses, respectively. Our results highlight the close interrelation between the Poisson's ratio and the remaining model parameters. The identified parameters will contribute to more precise computational models enabling spatially resolved predictions of the stress and strain states in human brains under complex mechanical loading conditions.

Loss of Twist1 and balanced retinoic acid signaling from the meninges causes cortical folding in mice

Secondary lissencephaly evolved in mice due to effects on neurogenesis and the tangential distribution of neurons. Signaling pathways that help maintain lissencephaly are still poorly understood. We show that inactivating Twist1 in the primitive meninges causes cortical folding in mice. Cell proliferation in the meninges is reduced, causing loss of arachnoid fibroblasts that express Raldh2, an enzyme required for retinoic acid synthesis. Regionalized loss of Raldh2 in the dorsolateral meninges is first detected when folding begins. The ventricular zone expands and the forebrain lengthens at this time due to expansion of apical radial glia. As the cortex expands, regionalized differences in the levels of neurogenesis are coupled with changes to the tangential distribution of neurons. Consequentially, cortical growth at and adjacent to the midline accelerates with respect to more dorsolateral regions, resulting in cortical buckling and folding. Maternal retinoic acid supplementation suppresses cortical folding by normalizing forebrain length, neurogenesis and the tangential distribution of neurons. These results suggest that Twist1 and balanced retinoic acid signaling from the meninges are required to maintain normal levels of neurogenesis and lissencephaly in mice.

Genetic insights into human cortical organization and development through genome-wide analyses of 2,347 neuroimaging phenotypes

Our understanding of the genetics of the human cerebral cortex is limited both in terms of the diversity and the anatomical granularity of brain structural phenotypes. Here we conducted a genome-wide association meta-analysis of 13 structural and diffusion magnetic resonance imaging-derived cortical phenotypes, measured globally and at 180 bilaterally averaged regions in 36,663 individuals and identified 4,349 experiment-wide significant loci. These phenotypes include cortical thickness, surface area, gray matter volume, measures of folding, neurite density and water diffusion. We identified four genetic latent structures and causal relationships between surface area and some measures of cortical folding. These latent structures partly relate to different underlying gene expression trajectories during development and are enriched for different cell types. We also identified differential enrichment for neurodevelopmental and constrained genes and demonstrate that common genetic variants associated with cortical expansion are associated with cephalic disorders. Finally, we identified complex interphenotype and inter-regional genetic relationships among the 13 phenotypes, reflecting the developmental differences among them. Together, these analyses identify distinct genetic organizational principles of the cortex and their correlates with neurodevelopment.

The Control of Cortical Folding: Multiple Mechanisms, Multiple Models

The cerebral cortex develops through a carefully conscripted series of cellular and molecular events that culminate in the production of highly specialized neuronal and glial cells. During development, cortical neurons and glia acquire a precise cellular arrangement and architecture to support higher-order cognitive functioning. Decades of study using rodent models, naturally gyrencephalic animal models, human pathology specimens, and, recently, human cerebral organoids, reveal that rodents recapitulate some but not all the cellular and molecular features of human cortices. Whereas rodent cortices are smooth-surfaced or lissencephalic, larger mammals, including humans and nonhuman primates, have highly folded/gyrencephalic cortices that accommodate an expansion in neuronal mass and increase in surface area. Several genes have evolved to drive cortical gyrification, arising from gene duplications or de novo origins, or by alterations to the structure/function of ancestral genes or their gene regulatory regions. Primary cortical folds arise in stereotypical locations, prefigured by a molecular "blueprint" that is set up by several signaling pathways (e.g., Notch, Fgf, Wnt, PI3K, Shh) and influenced by the extracellular matrix. Mutations that affect neural progenitor cell proliferation and/or neurogenesis, predominantly of upper-layer neurons, perturb cortical gyrification. Below we review the molecular drivers of cortical folding and their roles in disease.

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.

Mapping Genetic Topography of Cortical Thickness and Surface Area in Neonatal Brains

Adult twin neuroimaging studies have revealed that cortical thickness (CT) and surface area (SA) are differentially influenced by genetic information, leading to their spatially distinct genetic patterning and topography. However, the postnatal origins of the genetic topography of CT and SA remain unclear, given the dramatic cortical development from neonates to adults. To fill this critical gap, this study unprecedentedly explored how genetic information differentially regulates the spatial topography of CT and SA in the neonatal brain by leveraging brain magnetic resonance (MR) images from 202 twin neonates with minimal influence by the complicated postnatal environmental factors. We capitalized on infant-dedicated computational tools and a data-driven spectral clustering method to parcellate the cerebral cortex into a set of distinct regions purely according to the genetic correlation of cortical vertices in terms of CT and SA, respectively, and accordingly created the first genetically informed cortical parcellation maps of neonatal brains. Both genetic parcellation maps exhibit bilaterally symmetric and hierarchical patterns, but distinct spatial layouts. For CT, regions with closer genetic relationships demonstrate an anterior-posterior (A-P) division, while for SA, regions with greater genetic proximity are typically within the same lobe. Certain genetically informed regions exhibit strong similarities between neonates and adults, with the most striking similarities in the medial surface in terms of SA, despite their overall substantial differences in genetic parcellation maps. These results greatly advance our understanding of the development of genetic influences on the spatial patterning of cortical morphology.SIGNIFICANCE STATEMENT Genetic influences on cortical thickness (CT) and surface area (SA) are complex and could evolve throughout the lifespan. However, studies revealing distinct genetic topography of CT and SA have been limited to adults. Using brain structural magnetic resonance (MR) images of twins, we unprecedentedly discovered the distinct genetically-informed parcellation maps of CT and SA in neonatal brains, respectively. Each genetic parcellation map comprises a distinct spatial layout of cortical regions, where vertices within the same region share high genetic correlation. These genetic parcellation maps of CT and SA of neonates largely differ from those of adults, despite their highly remarkable similarities in the medial cortex of SA. These discoveries provide important insights into the genetic organization of the early cerebral cortex development.

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.

An integrated finite element method and machine learning algorithm for brain morphology prediction

The human brain development experiences a complex evolving cortical folding from a smooth surface to a convoluted ensemble of folds. Computational modeling of brain development has played an essential role in better understanding the process of cortical folding, but still leaves many questions to be answered. A major challenge faced by computational models is how to create massive brain developmental simulations with affordable computational sources to complement neuroimaging data and provide reliable predictions for brain folding. In this study, we leveraged the power of machine learning in data augmentation and prediction to develop a machine-learning-based finite element surrogate model to expedite brain computational simulations, predict brain folding morphology, and explore the underlying folding mechanism. To do so, massive finite element method (FEM) mechanical models were run to simulate brain development using the predefined brain patch growth models with adjustable surface curvature. Then, a GAN-based machine learning model was trained and validated with these produced computational data to predict brain folding morphology given a predefined initial configuration. The results indicate that the machine learning models can predict the complex morphology of folding patterns, including 3-hinge gyral folds. The close agreement between the folding patterns observed in FEM results and those predicted by machine learning models validate the feasibility of the proposed approach, offering a promising avenue to predict the brain development with given fetal brain configurations.

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.

Sulcal morphology of posteromedial cortex substantially differs between humans and chimpanzees

Recent studies identify a surprising coupling between evolutionarily new sulci and the functional organization of human posteromedial cortex (PMC). Yet, no study has compared this modern PMC sulcal patterning between humans and non-human hominoids. To fill this gap in knowledge, we first manually defined over 2500 PMC sulci in 120 chimpanzee (Pan Troglodytes) hemispheres and 144 human hemispheres. We uncovered four new sulci, and quantitatively identified species differences in sulcal incidence, depth, and surface area. Interestingly, some sulci are more common in humans and others, in chimpanzees. Further, we found that the prominent marginal ramus of the cingulate sulcus differs significantly between species. Contrary to classic observations, the present results reveal that the surface anatomy of PMC substantially differs between humans and chimpanzees-findings which lay a foundation for better understanding the evolution of neuroanatomical-functional and neuroanatomical-behavioral relationships in this highly expanded region of the human cerebral cortex.

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.

Brain morphometry points to emerging patterns of psychosis, depression, and anxiety vulnerability over a 2-year period in childhood

BACKGROUND

Gray matter morphometry studies have lent seminal insights into the etiology of mental illness. Existing research has primarily focused on adults and then, typically on a single disorder. Examining brain characteristics in late childhood, when the brain is preparing to undergo significant adolescent reorganization and various forms of serious psychopathology are just first emerging, may allow for a unique and highly important perspective of overlapping and unique pathogenesis.

METHODS

A total of 8645 youth were recruited as part of the Adolescent Brain and Cognitive Development study. Magnetic resonance imaging scans were collected, and psychotic-like experiences (PLEs), depressive, and anxiety symptoms were assessed three times over a 2-year period. Cortical thickness, surface area, and subcortical volume were used to predict baseline symptomatology and symptom progression over time.

RESULTS

Some features could possibly signal common vulnerability, predicting progression across forms of psychopathology (e.g. superior frontal and middle temporal regions). However, there was a specific predictive value for emerging PLEs (lateral occipital and precentral thickness), anxiety (parietal thickness/area and cingulate), and depression (e.g. parahippocampal and inferior temporal).

CONCLUSION

Findings indicate common and distinct patterns of vulnerability for varying forms of psychopathology are present during late childhood, before the adolescent reorganization, and have direct relevance for informing novel conceptual models along with early prevention and intervention efforts.

Mechanics of axon growth and damage: A systematic review of computational models

Normal axon development depends on the action of mechanical forces both generated within the cytoskeleton and outside the cell, but forces of large magnitude or rate cause damage instead. Computational models aid scientists in studying the role of mechanical forces in axon growth and damage. These studies use simulations to evaluate how different sources of force generation within the cytoskeleton interact with each other to regulate axon elongation and retraction. Furthermore, mathematical models can help optimize externally applied tension to promote axon growth without causing damage. Finally, scientists also use simulations of axon damage to investigate how forces are distributed among different components of the axon and how the tissue surrounding an axon influences its susceptibility to injury. In this review, we discuss how computational studies complement experimental studies in the areas of axon growth, regeneration, and damage.

Associations with youth psychotic-like experiences over time: Evidence for trans-symptom and specific cognitive and neural risk factors

The current study examined whether impairments in cognitive and neural factors at baseline (ages 9-10) predict initial levels or changes in psychotic-like experiences (PLEs) and whether such impairments generalize to other psychopathology symptoms (i.e., internalizing and externalizing symptoms). Using unique longitudinal Adolescent Brain Cognitive Development Study data, the study examined three time points from ages 9 to 13. Univariate latent growth models examined associations between baseline cognitive and neural metrics with symptom measures using discovery (n = 5,926) and replication (n = 5,952) data sets. For symptom measures (i.e., PLEs, internalizing, externalizing), we examined mean initial levels (i.e., intercepts) and changes over time (i.e., slopes). Predictors included neuropsychological test performance, global structural MRI, and several a priori within-network resting-state functional connectivity metrics. Results showed a pattern whereby baseline cognitive and brain metric impairments showed the strongest associations with PLEs over time. Lower cognitive, volume, surface area, and cingulo-opercular within-network connectivity metrics showed associations with increased PLEs and higher initial levels of externalizing and internalizing symptoms. Several metrics were uniquely associated with PLEs, including lower cortical thickness with higher initial PLEs and lower default mode network connectivity with increased PLEs slopes. Neural and cognitive impairments in middle childhood were broadly associated with increased PLEs over time, and showed stronger associations with PLEs compared with other psychopathology symptoms. The current study also identified markers potentially uniquely associated with PLEs (e.g., cortical thickness). Impairments in broad cognitive metrics, brain volume and surface area, and a network associated with information integration may represent risk factors for general psychopathology. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The fractal brain: scale-invariance in structure and dynamics

The past 40 years have witnessed extensive research on fractal structure and scale-free dynamics in the brain. Although considerable progress has been made, a comprehensive picture has yet to emerge, and needs further linking to a mechanistic account of brain function. Here, we review these concepts, connecting observations across different levels of organization, from both a structural and functional perspective. We argue that, paradoxically, the level of cortical circuits is the least understood from a structural point of view and perhaps the best studied from a dynamical one. We further link observations about scale-freeness and fractality with evidence that the environment provides constraints that may explain the usefulness of fractal structure and scale-free dynamics in the brain. Moreover, we discuss evidence that behavior exhibits scale-free properties, likely emerging from similarly organized brain dynamics, enabling an organism to thrive in an environment that shares the same organizational principles. Finally, we review the sparse evidence for and try to speculate on the functional consequences of fractality and scale-freeness for brain computation. These properties may endow the brain with computational capabilities that transcend current models of neural computation and could hold the key to unraveling how the brain constructs percepts and generates behavior.

Growth anisotropy of the extracellular matrix shapes a developing organ

Final organ size and shape result from volume expansion by growth and shape changes by contractility. Complex morphologies can also arise from differences in growth rate between tissues. We address here how differential growth guides the morphogenesis of the growing Drosophila wing imaginal disc. We report that 3D morphology results from elastic deformation due to differential growth anisotropy between the epithelial cell layer and its enveloping extracellular matrix (ECM). While the tissue layer grows in plane, growth of the bottom ECM occurs in 3D and is reduced in magnitude, thereby causing geometric frustration and tissue bending. The elasticity, growth anisotropy and morphogenesis of the organ are fully captured by a mechanical bilayer model. Moreover, differential expression of the Matrix metalloproteinase MMP2 controls growth anisotropy of the ECM envelope. This study shows that the ECM is a controllable mechanical constraint whose intrinsic growth anisotropy directs tissue morphogenesis in a developing organ.

Morphological Abnormalities in Early-Onset Schizophrenia Revealed by Structural Magnetic Resonance Imaging

Schizophrenia is a pathological condition characterized by delusions, hallucinations, and a lack of motivation. In this study, we performed a morphological analysis of regional biomarkers in early-onset schizophrenia, including cortical thicknesses, surface areas, surface curvature, and volumes extracted from T1-weighted structural magnetic resonance imaging (MRI) and compared these findings with a large cohort of neurotypical controls. Results demonstrate statistically significant abnormal presentation of the curvature of select brain regions in early-onset schizophrenia with large effect sizes, inclusive of the pars orbitalis, pars triangularis, posterior cingulate cortex, frontal pole, orbital gyrus, lateral orbitofrontal gyrus, inferior occipital gyrus, as well as in medial occipito-temporal, lingual, and insular sulci. We also observed reduced regional volumes, surface areas, and variability of cortical thicknesses in early-onset schizophrenia relative to neurotypical controls in the lingual, transverse temporal, cuneus, and parahippocampal cortices that did not reach our stringent standard for statistical significance and should be confirmed in future studies with higher statistical power. These results imply that abnormal neurodevelopment associated with early-onset schizophrenia can be characterized with structural MRI and may reflect abnormal and possibly accelerated pruning of the cortex in schizophrenia.

Mechanobiological approaches to synthetic morphogenesis: learning by building

Tissue morphogenesis occurs in a complex physicochemical microenvironment with limited experimental accessibility. This often prevents a clear identification of the processes that govern the formation of a given functional shape. By applying state-of-the-art methods to minimal tissue systems, synthetic morphogenesis aims to engineer the discrete events that are necessary and sufficient to build specific tissue shapes. Here, we review recent advances in synthetic morphogenesis, highlighting how a combination of microfabrication and mechanobiology is fostering our understanding of how tissues are built.

Individual electric field predicts functional connectivity changes after anodal transcranial direct-current stimulation in chronic stroke

The neuromodulation effect of anodal tDCS is not thoroughly studied, and the heterogeneous profile of stroke individuals with brain lesions would further complicate the stimulation outcomes. This study aimed to investigate the functional changes in sensorimotor areas induced by anodal tDCS and whether individual electric field could predict the functional outcomes. Twenty-five chronic stroke survivors were recruited and divided into tDCS group (n = 12) and sham group (n = 13). Increased functional connectivity (FC) within the surrounding areas of ipsilesional primary motor cortex (M1) was only observed after anodal tDCS. Averaged FC among the ipsilesional sensorimotor regions was observed to be increased after anodal tDCS (t(11) = 2.57, p = 0.026), but not after sham tDCS (t(12) = 0.69, p = 0.50). Partial least square analysis identified positive correlations between electric field (EF) strength normal to the ipsilesional M1 surface and individual FC changes in tDCS group (r = 0.84, p < 0.001) but not in sham group (r = 0.21, p = 0.5). Our results indicated anodal tDCS facilitates the FC within the ipsilesional sensorimotor network in chronic stroke subjects, and individual electric field predicts the functional outcomes.

Expansion of ring-shaped supracellular contractile cables induces epithelial sheet folding

The folding of epithelial cell sheets is a fundamental process that sculpts developing tissues and organs into their proper shapes required for normal physiological functions. In the absence of detailed biochemical regulations, the epithelial sheet folding may simply proceed through buckling due to mechanical compression arising extrinsically from the surroundings or intrinsically within the sheets. Previous studies hypothesized that the formation of an expanding supracellular actomyosin ring within epithelial sheets could result in compression that ultimately leads to epithelial folding during tracheal development in the Drosophila (fruit fly) embryo. However, the exact mechanism by which the formation of epithelial folds is coordinated by the ring expansion remains unclear. Using a vertex-based mechanical model, here I systematically study the dependence of epithelial fold formation on the physical properties of expanding supracellular contractile rings. The simulations show that depending on the contractile strength, epithelial cell sheets can undergo distinct patterns of folding during ring expansion. The formation of folds in particular is robust against fluctuations in the ring properties such as ring numbers and tensions. These findings provide a systematic view to understand how the expansion of supracellular contractile rings in epithelial sheets mediates epithelial folding morphogenesis.

Emerging biomaterials and technologies to control stem cell fate and patterning in engineered 3D tissues and organoids

The ability to create complex three-dimensional cellular models that can effectively replicate the structure and function of human organs and tissues in vitro has the potential to revolutionize medicine. Such models could facilitate the interrogation of developmental and disease processes underpinning fundamental discovery science, vastly accelerate drug development and screening, or even be used to create tissues for implantation into the body. Realization of this potential, however, requires the recreation of complex biochemical, biophysical, and cellular patterns of 3D tissues and remains a key challenge in the field. Recent advances are being driven by improved knowledge of tissue morphogenesis and architecture and technological developments in bioengineering and materials science that can create the multidimensional and dynamic systems required to produce complex tissue microenvironments. In this article, we discuss challenges for in vitro models of tissues and organs and summarize the current state-of-the art in biomaterials and bioengineered systems that aim to address these challenges. This includes both top-down technologies, such as 3D photopatterning, magnetism, acoustic forces, and cell origami, as well as bottom-up patterning using 3D bioprinting, microfluidics, cell sheet technology, or composite scaffolds. We illustrate the varying ways that these can be applied to suit the needs of different tissues and applications by focussing on specific examples of patterning the bone-tendon interface, kidney organoids, and brain cancer models. Finally, we discuss the challenges and future prospects in applying materials science and bioengineering to develop high-quality 3D tissue structures for in vitro studies.

Mapping brain mechanical property maturation from childhood to adulthood

Magnetic resonance elastography (MRE) is a phase contrast MRI technique which uses external palpation to create maps of brain mechanical properties noninvasively and in vivo. These mechanical properties are sensitive to tissue microstructure and reflect tissue integrity. MRE has been used extensively to study aging and neurodegeneration, and to assess individual cognitive differences in adults, but little is known about mechanical properties of the pediatric brain. Here we use high-resolution MRE imaging in participants of ages ranging from childhood to adulthood to understand brain mechanical properties across brain maturation. We find that brain mechanical properties differ considerably between childhood and adulthood, and that neuroanatomical subregions have differing maturational trajectories. Overall, we observe lower brain stiffness and greater brain damping ratio with increasing age from 5 to 35 years. Gray and white matter change differently during maturation, with larger changes occurring in gray matter for both stiffness and damping ratio. We also found that subregions of cortical and subcortical gray matter change differently, with the caudate and thalamus changing the most with age in both stiffness and damping ratio, while cortical subregions have different relationships with age, even between neighboring regions. Understanding how brain mechanical properties mature using high-resolution MRE will allow for a deeper understanding of the neural substrates supporting brain function at this age and can inform future studies of atypical maturation.

Harsh and Inconsistent Parental Discipline Is Associated With Altered Cortical Development in Children

BACKGROUND

A growing body of evidence suggests that parenting behaviors may affect child mental health via altering brain development. There is a scarcity of research, however, that has investigated associations between parenting behavior and brain structure using longitudinal magnetic resonance imaging. This study aimed to investigate associations between parenting behaviors and structural brain development across the transition from childhood to adolescence.

METHODS

Participants were 246 children who provided 436 magnetic resonance imaging datasets covering the age range from 8 to 13 years. Parents (94% mothers) completed self-report measures of parenting behavior, and both children and parents reported on child mental health. Factor analysis was used to identify dimensions of parental behavior. Linear mixed-effects models investigated associations between parenting behaviors and age-related change in cortical thickness and surface area and subcortical volume. Mediation models tested whether brain changes mediated associations between parenting behaviors and changes in internalizing/externalizing symptoms.

RESULTS

Hypothesized associations between parenting and amygdala, hippocampal, and frontal trajectories were not supported. Rather, higher levels of parent harsh/inconsistent discipline were associated with decreases in surface area in medial parietal and temporal pole regions and reduced cortical thinning in medial parietal regions. Some effects were present in female but not male children. There were no associations between these neurodevelopmental alterations and symptoms.

CONCLUSIONS

This study provides insight into the links between parenting behavior and child neurodevelopment. Given the functions of implicated regions, findings may suggest that parental harsh/inconsistent discipline affects the development of neural circuits subserving sensorimotor and social functioning in children.

Variability and concordance of sulcal patterns in the orbitofrontal cortex: A twin study

Sulcogyral patterns have been identified in the orbitofrontal cortex (OFC) based on the continuity of the medial and lateral orbital sulci. Pattern types are named according to their frequency in the population, with Type I present in ∼60%, Type II in ∼25%, Type III in ∼10%, and Type IV in ∼5%. Previous work has demonstrated that psychiatric conditions with high estimated heritability (e.g. schizophrenia, bipolar disorder) are associated with reduced frequency of Type I patterns, but the general heritability of the OFC sulcogyral patterns is unknown. We examined concordance of OFC patterns in 304 monozygotic (MZ) twins relative to 172 dizygotic (DZ) twins using structural magnetic resonance imaging data. We find that the frequency of pattern types within MZ and DZ twins are similar and bilateral concordance rates across all pattern types in DZ twins were 14% and 21% for MZ twins. Results from follow-up analyses confirm that continuity in the rostral-caudal direction is an important source of variability within the OFC, and subtype analyses indicate that variability is present in other sulci that are not represented by overall OFC pattern type. Overall, these results suggest that OFC sulcogyral patterns may reflect important variance that is not genetic in origin.

Prenatal caffeine exposure: association with neurodevelopmental outcomes in 9- to 11-year-old children

BACKGROUND

Despite the widespread use of caffeine including consumption during pregnancy, the effect of prenatal caffeine exposure on child brain development and behavior is unclear.

METHODS

To address this, we used data from the Adolescent Brain and Cognitive Development Study (n = 11,875 children aged 9-11 years from 22 sites across the United States). We explored the associations between prenatal caffeine exposure and various developmental outcomes including birth outcomes, physical health, behavior problems, cognition, substance use and brain structure in children, and evaluated dose effects.

RESULTS

Among 9,978 children (4,745 females) who had valid data for prenatal caffeine exposure and whose mothers did not use drugs of abuse after knowing of pregnancy, 4,170 (41.79%) had no prenatal caffeine exposure, 2,292 (22.97%) had daily, 1,933 (19.37%) had weekly, and 1,583 (15.86%) had less than weekly exposures. Prenatal caffeine exposure including the widely recommended 'safe' dose was associated with greater externalizing problems, whereas greater BMI and soda consumption were only observed in children with high dose exposures (3+ per day). Notably, the effect size for association of externalizing problems with prenatal caffeine exposure was comparable with that reported for prenatal alcohol (The American Journal of Psychiatry, 177, 2020 and 1060) and prenatal cannabis (JAMA Psychiatry, 78, 2020 and 64) exposures from previous ABCD publications. Additionally, prenatal caffeine exposure was associated with brain structural changes that included greater posterior and lower frontal cortical thickness and altered parietooccipital sulcal depth.

CONCLUSIONS

The recommended 'safe' dose of caffeine during pregnancy should be carefully studied to assess whether the behavioral and brain correlates observed here are clinically relevant and determine whether it needs adjustment. Because of the high prevalence of caffeine use in the general population, studies on prenatal exposure to drugs of abuse should include prenatal caffeine use as a covariate.

The roles of inter-tissue adhesion in development and morphological evolution

The study of how neighboring tissues physically interact with each other, inter-tissue adhesion, is an emerging field at the interface of cell biology, biophysics and developmental biology. Inter-tissue adhesion can be mediated by either cell-extracellular matrix adhesion or cell-cell adhesion, and both the mechanisms and consequences of inter-tissue adhesion have been studied in vivo in numerous vertebrate and invertebrate species. In this Review, we discuss recent progress in understanding the many functions of inter-tissue adhesion in development and evolution. Inter-tissue adhesion can couple the motion of adjacent tissues, be the source of mechanical resistance that constrains morphogenesis, and transmit tension required for normal development. Tissue-tissue adhesion can also create mechanical instability that leads to tissue folding or looping. Transient inter-tissue adhesion can facilitate tissue invasion, and weak tissue adhesion can generate friction that shapes and positions tissues within the embryo. Lastly, we review studies that reveal how inter-tissue adhesion contributes to the diversification of animal morphologies.

Differentiating distinct and converging neural correlates of types of systemic environmental exposures

Systemic environmental disadvantage relates to a host of health and functional outcomes. Specific structural factors have seldom been linked to neural structure, however, clouding understanding of putative mechanisms. Examining relations during childhood/preadolescence, a dynamic period of neurodevelopment, could aid bridge this gap. A total of 10,213 youth were recruited from the Adolescent Brain and Cognitive Development study. Self-report and objective measures (Census and Federal bureau of investigation metrics extracted using geocoding) of environmental exposures were used, including stimulation indexing lack of safety and high attentional demands, discrepancy indexing social exclusion/lack of belonging, and deprivation indexing lack of environmental enrichment. Environmental measures were related to cortical thickness, surface area, and subcortical volume regions, controlling for other environmental exposures and accounting for other brain regions. Self-report (|β| = .04-.09) and objective (|β| = .02-.06) environmental domains related to area/thickness in overlapping (e.g., insula, caudal anterior cingulate), and unique regions (e.g., for discrepancy, rostral anterior and isthmus cingulate, implicated in socioemotional functions; for stimulation, precuneus, critical for cue reactivity and integration of environmental cues; and for deprivation, superior frontal, integral to executive functioning). For stimulation and discrepancy exposures, self-report and objective measures showed similarities in correlate regions, while deprivation exposures evidenced distinct correlates for self-report and objective measures. Results represent a necessary step toward broader work aimed at establishing mechanisms and correlates of structural disadvantage, highlighting the relevance of going beyond aggregate models by considering types of environmental factors, and the need to incorporate both subjective and objective measurements in these efforts.

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.

A network approach to the topological organization of the Brodmann map

Brain morphology is the result of functional factors associated with cortical areas, but it is also influenced by structural aspects due to physical and spatial constraints. Despite the noticeable advances in brain mapping, Brodmann's map is still used in many research fields that rely on macroscopic cortical features for practical or theoretical issues. Here, the topological relationships among the Brodmann areas were modelled according to the principles of network analysis, in order to provide a synthetic view of their spatial properties following a criterion of contiguity. The model evidences the importance of the parieto-temporal region in terms of biological burden and topological complexity. The retrosplenial region is particularly influenced by spatial constraints, and the cingulate cortex occupies a position that bridges the anterior and posterior topological blocks. Such spatial framework should be taken into account when dealing with brain morphology in both ontogeny and phylogeny. This article is protected by copyright. All rights reserved.

Cortical thickness systematically varies with curvature and depth in healthy human brains

Cortical thickness varies throughout the cortex in a systematic way. However, it is challenging to investigate the patterns of cortical thickness due to the intricate geometry of the cortex. The cortex has a folded nature both in radial and tangential directions which forms not only gyri and sulci but also tangential folds and intersections. In this article, cortical curvature and depth are used to characterize the spatial distribution of the cortical thickness with much higher resolution than conventional regional atlases. To do this, a computational pipeline was developed that is capable of calculating a variety of quantitative measures such as surface area, cortical thickness, curvature (mean curvature, Gaussian curvature, shape index, intrinsic curvature index, and folding index), and sulcal depth. By analyzing 501 neurotypical adult human subjects from the ABIDE-I dataset, we show that cortex has a very organized structure and cortical thickness is strongly correlated with local shape. Our results indicate that cortical thickness consistently increases along the gyral-sulcal spectrum from concave to convex shape, encompassing the saddle shape along the way. Additionally, tangential folds influence cortical thickness in a similar way as gyral and sulcal folds; outer folds are consistently thicker than inner.