Role of axonal fibers in the cortical folding patterns: A tale of variability and regularity

Unique longitudinal contributions of sulcal interruptions to reading acquisition in children

A growing body of literature indicates strong associations between indentations of the cerebral cortex (i.e., sulci) and individual differences in cognitive performance. Interruptions, or gaps, of sulci (historically known as pli de passage) are particularly intriguing as previous work suggests that these interruptions have a causal effect on cognitive development. Here, we tested how the presence and morphology of sulcal interruptions in the left posterior occipitotemporal sulcus (pOTS) longitudinally impact the development of a culturally-acquired skill: reading. Forty-three children were successfully followed from age 5 in kindergarten, at the onset of literacy instruction, to ages 7 and 8 with assessments of cognitive, pre-literacy, and literacy skills, as well as MRI anatomical scans at ages 5 and 8. Crucially, we demonstrate that the presence of a left pOTS gap at 5 years is a specific and robust longitudinal predictor of better future reading skills in children, with large observed benefits on reading behavior ranging from letter knowledge to reading comprehension. The effect of left pOTS interruptions on reading acquisition accumulated through time, and was larger than the impact of benchmark cognitive and familial predictors of reading ability and disability. Finally, we show that increased local U-fiber white matter connectivity associated with such sulcal interruptions possibly underlie these behavioral benefits, by providing a computational advantage. To our knowledge, this is the first quantitative evidence supporting a potential integrative gray-white matter mechanism underlying the cognitive benefits of macro-anatomical differences in sulcal morphology related to longitudinal improvements in a culturally-acquired skill.

Are numerical abilities determined at early age? A brain morphology study in children and adolescents with and without developmental dyscalculia

The intraparietal sulcus (IPS) has been associated with numerical processing. A recent study reported that the IPS sulcal pattern was associated with arithmetic and symbolic number abilities in children and adults. In the present study, we evaluated the link between numerical abilities and the IPS sulcal pattern in children with Developmental Dyscalculia (DD) and typically developing children (TD), extending previous analyses considering other sulcal features and the postcentral sulcus (PoCS). First, we confirm the longitudinal sulcal pattern stability of the IPS and the PoCS. Second, we found a lower proportion of left sectioned IPS and a higher proportion of a double-horizontal IPS shape bilaterally in DD compared to TD. Third, our analyses revealed that arithmetic is the only aspect of numerical processing that is significantly related to the IPS sulcal pattern (sectioned vs not sectioned), and that this relationship is specific to the left hemisphere. And last, correlation analyses of age and arithmetic in children without a sectioned left IPS indicate that although they may have an inherent disadvantage in numerical abilities, these may improve with age. Thus, our results indicate that only the left IPS sulcal pattern is related to numerical abilities and that other factors co-determine numerical abilities.

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.

Toward a better understanding of how a gyrified brain develops

The size and shape of the cerebral cortex have changed dramatically across evolution. For some species, the cortex remains smooth (lissencephalic) throughout their lifetime, while for other species, including humans and other primates, the cortex increases substantially in size and becomes folded (gyrencephalic). A folded cortex boasts substantially increased surface area, cortical thickness, and neuronal density, and it is therefore associated with higher-order cognitive abilities. The mechanisms that drive gyrification in some species, while others remain lissencephalic despite many shared neurodevelopmental features, have been a topic of investigation for many decades, giving rise to multiple perspectives of how the gyrified cerebral cortex acquires its unique shape. Recently, a structurally unique germinal layer, known as the outer subventricular zone, and the specialized cell type that populates it, called basal radial glial cells, were identified, and these have been shown to be indispensable for cortical expansion and folding. Transcriptional analyses and gene manipulation models have provided an invaluable insight into many of the key cellular and genetic drivers of gyrification. However, the degree to which certain biomechanical, genetic, and cellular processes drive gyrification remains under investigation. This review considers the key aspects of cerebral expansion and folding that have been identified to date and how theories of gyrification have evolved to incorporate this new knowledge.

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.

Systematic cortical thickness and curvature patterns in primates

Humans are known to have significant and consistent differences in thickness throughout the cortex, with thick outer gyral folds and thin inner sulcal folds. Our previous work has suggested a mechanical basis for this thickness pattern, with the forces generated during cortical folding leading to thick gyri and thin sulci, and shown that cortical thickness varies along a gyral-sulcal spectrum in humans. While other primate species are expected to exhibit similar patterns of cortical thickness, it is currently unknown how these patterns scale across different sizes, forms, and foldedness. Among primates, brains vary enormously from roughly the size of a grape to the size of a grapefruit, and from nearly smooth to dramatically folded; of these, human brains are the largest and most folded. These variations in size and form make comparative neuroanatomy a rich resource for investigating common trends that transcend differences between species. In this study, we examine 12 primate species in order to cover a wide range of sizes and forms, and investigate the scaling of their cortical thickness relative to the surface geometry. The 12 species were selected due to the public availability of either reconstructed surfaces and/or population templates. After obtaining or reconstructing 3D surfaces from publicly available neuroimaging data, we used our surface-based computational pipeline (https://github.com/mholla/curveball) to analyze patterns of cortical thickness and folding with respect to size (total surface area), geometry (i.e. curvature, shape, and sulcal depth), and foldedness (gyrification). In all 12 species, we found consistent cortical thickness variations along a gyral-sulcal spectrum, with convex shapes thicker than concave shapes and saddle shapes in between. Furthermore, we saw an increasing thickness difference between gyri and sulci as brain size increases. Our results suggest a systematic folding mechanism relating local cortical thickness to geometry. Finally, all of our reconstructed surfaces and morphometry data are available for future research in comparative neuroanatomy.

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.

Fast and Adaptive Construction of Gyral Morphological Networks Based on Morphometric Features of Cortical Surface

The organization of cortical folding patterns are related to brain function, cognition and behaviors. Due to the enormous complexity and high inter-subject variability in cortical morphology, it has been a challenging task to effectively and efficiently quantify the gyrification patterns of cerebral cortex. To tackle these issues, the gyral net approach used a graph-based representation of cortical architecture by segmenting the gyral crests from the cortical meshes based on its morphological metrics. However, current morphology-based approaches are very time-consuming and not applicable for large-scale dataset. In this study, we develop a fast and adaptive method to automatically construct the gyral morphological graph within 10 seconds. Our method is robust to low contrast conditions and more computationally efficient, approximately 5 times faster than classical approaches. We evaluated the proposed method on 1081 young adults acquired from the HCP dataset and uncovered significant differences among functional brain networks from the perspective of morphological networks.

Long-term morphological and functional dynamics of human stem cell-derived neuronal networks on high-density micro-electrode arrays

Comprehensive electrophysiological characterizations of human induced pluripotent stem cell (hiPSC)-derived neuronal networks are essential to determine to what extent these in vitro models recapitulate the functional features of in vivo neuronal circuits. High-density micro-electrode arrays (HD-MEAs) offer non-invasive recording with the best spatial and temporal resolution possible to date. For 3 months, we tracked the morphology and activity features of developing networks derived from a transgenic hiPSC line in which neurogenesis is inducible by neurogenic transcription factor overexpression. Our morphological data revealed large-scale structural changes from homogeneously distributed neurons in the first month to the formation of neuronal clusters over time. This led to a constant shift in position of neuronal cells and clusters on HD-MEAs and corresponding changes in spatial distribution of the network activity maps. Network activity appeared as scarce action potentials (APs), evolved as local bursts with longer duration and changed to network-wide synchronized bursts with higher frequencies but shorter duration over time, resembling the emerging burst features found in the developing human brain. Instantaneous firing rate data indicated that the fraction of fast spiking neurons (150–600 Hz) increases sharply after 63 days post induction (dpi). Inhibition of glutamatergic synapses erased burst features from network activity profiles and confirmed the presence of mature excitatory neurotransmission. The application of GABAergic receptor antagonists profoundly changed the bursting profile of the network at 120 dpi. This indicated a GABAergic switch from excitatory to inhibitory neurotransmission during circuit development and maturation. Our results suggested that an emerging GABAergic system at older culture ages is involved in regulating spontaneous network bursts. In conclusion, our data showed that long-term and continuous microscopy and electrophysiology readouts are crucial for a meaningful characterization of morphological and functional maturation in stem cell-derived human networks. Most importantly, assessing the level and duration of functional maturation is key to subject these human neuronal circuits on HD-MEAs for basic and biomedical applications.

Gyral and sulcal connectivity in the human cerebral cortex

The rapid evolution of image acquisition and data analytic methods has established in vivo whole-brain tractography as a routine technology over the last 20 years. Imaging-based methods provide an additional approach to classic neuroanatomical studies focusing on biomechanical principles of anatomical organization and can in turn overcome the complexity of inter-individual variability associated with histological and tractography studies. In this work we propose a novel, reliable framework for determining brain tracts resolving the anatomical variance of brain regions. We distinguished 4 region types based on anatomical considerations: (i) gyral regions at borders between cortical communities; (ii) gyral regions within communities; (iii) sulcal regions at invariant locations across subjects; and (iv) other sulcal regions. Region types showed strikingly different anatomical and connection properties. Results allowed complementing the current understanding of the brain’s communication structure with a model of its anatomical underpinnings.

Gyral peaks: Novel gyral landmarks in developing macaque brains

Cerebral cortex development undergoes a variety of processes, which provide valuable information for the study of the developmental mechanism of cortical folding as well as its relationship to brain structural architectures and brain functions. Despite the variability in the anatomy–function relationship on the higher‐order cortex, recent studies have succeeded in identifying typical cortical landmarks, such as sulcal pits, that bestow specific functional and cognitive patterns and remain invariant across subjects and ages with their invariance being related to a gene‐mediated proto‐map. Inspired by the success of these studies, we aim in this study at defining and identifying novel cortical landmarks, termed gyral peaks, which are the local highest foci on gyri. By analyzing data from 156 MRI scans of 32 macaque monkeys with the age spanned from 0 to 36 months, we identified 39 and 37 gyral peaks on the left and right hemispheres, respectively. Our investigation suggests that these gyral peaks are spatially consistent across individuals and relatively stable within the age range of this dataset. Moreover, compared with other gyri, gyral peaks have a thicker cortex, higher mean curvature, more pronounced hub‐like features in structural connective networks, and are closer to the borders of structural connectivity‐based cortical parcellations. The spatial distribution of gyral peaks was shown to correlate with that of other cortical landmarks, including sulcal pits. These results provide insights into the spatial arrangement and temporal development of gyral peaks as well as their relation to brain structure and function.

Beyond language: The unspoken sensory-motor representation of the tongue in non-primates, non-human and human primates

The English idiom "on the tip of my tongue" commonly acknowledges that something is known, but it cannot be immediately brought to mind. This phrase accurately describes sensorimotor functions of the tongue, which are fundamental for many tongue-related behaviors (e.g., speech), but often neglected by scientific research. Here, we review a wide range of studies conducted on non-primates, non-human and human primates with the aim of providing a comprehensive description of the cortical representation of the tongue's somatosensory inputs and motor outputs across different phylogenetic domains. First, we summarize how the properties of passive non-noxious mechanical stimuli are encoded in the putative somatosensory tongue area, which has a conserved location in the ventral portion of the somatosensory cortex across mammals. Second, we review how complex self-generated actions involving the tongue are represented in more anterior regions of the putative somato-motor tongue area. Finally, we describe multisensory response properties of the primate and non-primate tongue area by also defining how the cytoarchitecture of this area is affected by experience and deafferentation.

Orchestrated neuronal migration and cortical folding: A computational and experimental study

Brain development involves precisely orchestrated genetic, biochemical, and mechanical events. At the cellular level, neuronal proliferation in the innermost zone of the brain followed by migration towards the outermost layer results in a rapid increase in brain surface area, outpacing the volumetric growth of the brain, and forming the highly folded cortex. This work aims to provide mechanistic insights into the process of brain development and cortical folding using a biomechanical model that couples cell division and migration with volumetric growth. Unlike phenomenological growth models, our model tracks the spatio-temporal development of cohorts of neurons born at different times, with each cohort modeled separately as an advection-diffusion process and the total cell density determining the extent of volume growth. We numerically implement our model in Abaqus/Standard (2020) by writing user-defined element (UEL) subroutines. For model calibration, we apply in utero electroporation (IUE) to ferret brains to visualize and track cohorts of neurons born at different stages of embryonic development. Our calibrated simulations of cortical folding align qualitatively with the ferret experiments. We have made our experimental data and finite-element implementation available online to offer other researchers a modeling platform for future study of neurological disorders associated with atypical neurodevelopment and cortical malformations.

Brain development and cortical folding is a highly dynamic process that results from the interaction between gene expression, cellular mechanisms, and mechanical forces. Here, we expand on existing mathematical models of brain development and cortical folding to capture the behavior of multiple different subpopulations of neurons. By calibrating our biomechanical model to our novel experiments on ferrets, we can track the distribution of neurons over time and observe how the brain grows and develops its characteristic folds. Our calibrated model captures interactions between cell behavior and tissue deformation and offers more detailed information about the orchestrated migration of neuronal subpopulations. This work offers new mechanistic insights into brain development and opens the door to future investigations of atypical brain development caused by disrupted neuronal activities, particularly those alterations associated with injury, exposure, or treatment at a specific location or time during development. Finally, our experimental data and numerical implementations are provided as a resource online for the use of other researchers.

MatriGrid® Based Biological Morphologies: Tools for 3D Cell Culturing

Recent trends in 3D cell culturing has placed organotypic tissue models at another level. Now, not only is the microenvironment at the cynosure of this research, but rather, microscopic geometrical parameters are also decisive for mimicking a tissue model. Over the years, technologies such as micromachining, 3D printing, and hydrogels are making the foundation of this field. However, mimicking the topography of a particular tissue-relevant substrate can be achieved relatively simply with so-called template or morphology transfer techniques. Over the last 15 years, in one such research venture, we have been investigating a micro thermoforming technique as a facile tool for generating bioinspired topographies. We call them MatriGrid^®s. In this research account, we summarize our learning outcome from this technique in terms of the influence of 3D micro morphologies on different cell cultures that we have tested in our laboratory. An integral part of this research is the evolution of unavoidable aspects such as possible label-free sensing and fluidic automatization. The development in the research field is also documented in this account.

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.