Development and Arealization of the Cerebral Cortex

Development of the basic architecture of neocortical circuitry in the human fetus as revealed by the coupling spatiotemporal pattern of synaptogenesis along with microstructure and macroscale in vivo MR imaging

In humans, a quantifiable number of cortical synapses appears early in fetal life. In this paper, we present a bridge across different scales of resolution and the distribution of synapses across the transient cytoarchitectonic compartments: marginal zone (MZ), cortical plate (CP), subplate (SP), and in vivo MR images. The tissue of somatosensory cortex (7-26 postconceptional weeks (PCW)) was prepared for electron microscopy, and classified synapses with a determined subpial depth were used for creating histograms matched to the histological sections immunoreacted for synaptic markers and aligned to in vivo MR images (1.5 T) of corresponding fetal ages (maternal indication). Two time periods and laminar patterns of synaptogenesis were identified: an early and midfetal two-compartmental distribution (MZ and SP) and a late fetal three-compartmental distribution (CP synaptogenesis). During both periods, a voluminous, synapse-rich SP was visualized on the in vivo MR. Another novel finding concerns the phase of secondary expansion of the SP (13 PCW), where a quantifiable number of synapses appears in the upper SP. This lamina shows a T2 intermediate signal intensity below the low signal CP. In conclusion, the early fetal appearance of synapses shows early differentiation of putative genetic mechanisms underlying the synthesis, transport and assembly of synaptic proteins. "Pioneering" synapses are likely to play a morphogenetic role in constructing of fundamental circuitry architecture due to interaction between neurons. They underlie spontaneous, evoked, and resting state activity prior to ex utero experience. Synapses can also mediate genetic and environmental triggers, adversely altering the development of cortical circuitry and leading to neurodevelopmental disorders.

Molecular and cellular dynamics of the developing human neocortex at single-cell resolution

The development of the human neocortex is a highly dynamic process and involves complex cellular trajectories controlled by cell-type-specific gene regulation1. Here, we collected paired single-nucleus chromatin accessibility and transcriptome data from 38 human neocortical samples encompassing both the prefrontal cortex and primary visual cortex. These samples span five main developmental stages, ranging from the first trimester to adolescence. In parallel, we performed spatial transcriptomic analysis on a subset of the samples to illustrate spatial organization and intercellular communication. This atlas enables us to catalog cell type-, age-, and area-specific gene regulatory networks underlying neural differentiation. Moreover, combining single-cell profiling, progenitor purification, and lineage-tracing experiments, we have untangled the complex lineage relationships among progenitor subtypes during the transition from neurogenesis to gliogenesis in the human neocortex. We identified a tripotential intermediate progenitor subtype, termed Tri-IPC, responsible for the local production of GABAergic neurons, oligodendrocyte precursor cells, and astrocytes. Remarkably, most glioblastoma cells resemble Tri-IPCs at the transcriptomic level, suggesting that cancer cells hijack developmental processes to enhance growth and heterogeneity. Furthermore, by integrating our atlas data with large-scale GWAS data, we created a disease-risk map highlighting enriched ASD risk in second-trimester intratelencephalic projection neurons. Our study sheds light on the gene regulatory landscape and cellular dynamics of the developing human neocortex.

Indirect neurogenesis in space and time

During central nervous system (CNS) development, neural progenitor cells (NPCs) generate neurons and glia in two different ways. In direct neurogenesis, daughter cells differentiate directly into neurons or glia, whereas in indirect neurogenesis, neurons or glia are generated after one or more daughter cell divisions. Intriguingly, indirect neurogenesis is not stochastically deployed and plays instructive roles during CNS development: increased generation of cells from specific lineages; increased generation of early or late-born cell types within a lineage; and increased cell diversification. Increased indirect neurogenesis might contribute to the anterior CNS expansion evident throughout the Bilateria and help to modify brain-region size without requiring increased NPC numbers or extended neurogenesis. Increased indirect neurogenesis could be an evolutionary driver of the gyrencephalic (that is, folded) cortex that emerged during mammalian evolution and might even have increased during hominid evolution. Thus, selection of indirect versus direct neurogenesis provides a powerful developmental and evolutionary instrument that drives not only the evolution of CNS complexity but also brain expansion and modulation of brain-region size, and thereby the evolution of increasingly advanced cognitive abilities. This Review describes indirect neurogenesis in several model species and humans, and highlights some of the molecular genetic mechanisms that control this important process.

Entosis implicates a new role for P53 in microcephaly pathogenesis, beyond apoptosis

Entosis, a form of cell cannibalism, is a newly discovered pathogenic mechanism leading to the development of small brains, termed microcephaly, in which P53 activation was found to play a major role. Microcephaly with entosis, found in Pals1 mutant mice, displays P53 activation that promotes entosis and apoptotic cell death. This previously unappreciated pathogenic mechanism represents a novel cellular dynamic in dividing cortical progenitors which is responsible for cell loss. To date, various recent models of microcephaly have bolstered the importance of P53 activation in cell death leading to microcephaly. P53 activation caused by mitotic delay or DNA damage manifests apoptotic cell death which can be suppressed by P53 removal in these animal models. Such genetic studies attest P53 activation as quality control meant to eliminate genomically unfit cells with minimal involvement in the actual function of microcephaly associated genes. In this review, we summarize the known role of P53 activation in a variety of microcephaly models and introduce a novel mechanism wherein entotic cell cannibalism in neural progenitors is triggered by P53 activation.

A shifting role of thalamocortical connectivity in the emergence of cortical functional organization

The cortical patterning principle has been a long-standing question in neuroscience, yet how this translates to macroscale functional specialization in the human brain remains largely unknown. Here we examine age-dependent differences in resting-state thalamocortical connectivity to investigate its role in the emergence of large-scale functional networks during early life, using a primarily cross-sectional but also longitudinal approach. We show that thalamocortical connectivity during infancy reflects an early differentiation of sensorimotor networks and genetically influenced axonal projection. This pattern changes in childhood, when connectivity is established with the salience network, while decoupling externally and internally oriented functional systems. A developmental simulation using generative network models corroborated these findings, demonstrating that thalamic connectivity contributes to developing key features of the mature brain, such as functional segregation and the sensory-association axis, especially across 12-18 years of age. Our study suggests that the thalamus plays an important role in functional specialization during development, with potential implications for studying conditions with compromised internal and external processing.

SynBot: An open-source image analysis software for automated quantification of synapses

The formation of precise numbers of neuronal connections, known as synapses, is crucial for brain function. Therefore, synaptogenesis mechanisms have been one of the main focuses of neuroscience. Immunohistochemistry is a common tool for visualizing synapses. Thus, quantifying the numbers of synapses from light microscopy images enables screening the impacts of experimental manipulations on synapse development. Despite its utility, this approach is paired with low throughput analysis methods that are challenging to learn and results are variable between experimenters, especially when analyzing noisy images of brain tissue. We developed an open-source ImageJ-based software, SynBot, to address these technical bottlenecks by automating the analysis. SynBot incorporates the advanced algorithms ilastik and SynQuant for accurate thresholding for synaptic puncta identification, and the code can easily be modified by users. The use of this software will allow for rapid and reproducible screening of synaptic phenotypes in healthy and diseased nervous systems.

Making Ramón y Cajal proud: Development of cell identity and diversity in the cerebral cortex

Since the beautiful images of Santiago Ramón y Cajal provided a first glimpse into the immense diversity and complexity of cell types found in the cerebral cortex, neuroscience has been challenged and inspired to understand how these diverse cells are generated and how they interact with each other to orchestrate the development of this remarkable tissue. Some fundamental questions drive the field's quest to understand cortical development: what are the mechanistic principles that govern the emergence of neuronal diversity? How do extrinsic and intrinsic signals integrate with physical forces and activity to shape cell identity? How do the diverse populations of neurons and glia influence each other during development to guarantee proper integration and function? The advent of powerful new technologies to profile and perturb cortical development at unprecedented resolution and across a variety of modalities has offered a new opportunity to integrate past knowledge with brand new data. Here, we review some of this progress using cortical excitatory projection neurons as a system to draw out general principles of cell diversification and the role of cell-cell interactions during cortical development.

Infant vocal productions coincide with body movements

Producing recognizable words is a difficult motor task; a one-syllable word can require the coordination of over 80 muscles. Thus, it is not surprising that the development of word productions in infancy lags considerably behind receptive language and is a known limiting factor in language development. A large literature has focused on the vocal apparatus, its articulators, and language development. There has been limited study of the relations between non-speech motor skills and the quality of early speech productions. Here we present evidence that the spontaneous vocalizations of 9- to 24-month-old infants recruit extraneous, synergistic co-activations of hand and head movements and that the temporal precision of the co-activation of vocal and extraneous muscle groups tightens with age and improved recognizability of speech. These results implicate an interaction between the muscle groups that produce speech and other body movements and provide new empirical pathways for understanding the role of motor development in language acquisition. RESEARCH HIGHLIGHTS: The spontaneous vocalizations of 9- to 24-month-old infants recruit extraneous, synergistic co-activations of hand and head movements. The temporal precision of these hand and head movements during vocal production tighten with age and improved speech recognition. These results implicate an interaction between the muscle groups producing speech with other body movements. These results provide new empirical pathways for understanding the role of motor development in language acquisition.

Genomic, molecular, and cellular divergence of the human brain

While many core biological processes are conserved across species, the human brain has evolved with unique capacities. Current understanding of the neurobiological mechanisms that endow human traits as well as associated vulnerabilities remains limited. However, emerging data have illuminated species divergence in DNA elements and genome organization, in molecular, morphological, and functional features of conserved neural cell types, as well as temporal differences in brain development. Here, we summarize recent data on unique features of the human brain and their complex implications for the study and treatment of brain diseases. We also consider key outstanding questions in the field and discuss the technologies and foundational knowledge that will be required to accelerate understanding of human neurobiology.

Deciphering the functional specialization of whole-brain spatiomolecular gradients in the adult brain

Cortical arealization arises during neurodevelopment from the confluence of molecular gradients representing patterned expression of morphogens and transcription factors. However, whether similar gradients are maintained in the adult brain remains unknown. Here, we uncover three axes of topographic variation in gene expression in the adult human brain that specifically capture previously identified rostral-caudal, dorsal-ventral, and medial-lateral axes of early developmental patterning. The interaction of these spatiomolecular gradients i) accurately reconstructs the position of brain tissue samples, ii) delineates known functional territories, and iii) can model the topographical variation of diverse cortical features. The spatiomolecular gradients are distinct from canonical cortical axes differentiating the primary sensory cortex from the association cortex, but radiate in parallel with the axes traversed by local field potentials along the cortex. We replicate all three molecular gradients in three independent human datasets as well as two nonhuman primate datasets and find that each gradient shows a distinct developmental trajectory across the lifespan. The gradients are composed of several well-known transcription factors (e.g., PAX6 and SIX3), and a small set of genes shared across gradients are strongly enriched for multiple diseases. Together, these results provide insight into the developmental sculpting of functionally distinct brain regions, governed by three robust transcriptomic axes embedded within brain parenchyma.

Early Developmental Origins of Cortical Disorders Modeled in Human Neural Stem Cells

The implications of the early phases of human telencephalic development, involving neural stem cells (NSCs), in the etiology of cortical disorders remain elusive. Here, we explored the expression dynamics of cortical and neuropsychiatric disorder-associated genes in datasets generated from human NSCs across telencephalic fate transitions in vitro and in vivo. We identified risk genes expressed in brain organizers and sequential gene regulatory networks across corticogenesis revealing disease-specific critical phases, when NSCs are more vulnerable to gene dysfunctions, and converging signaling across multiple diseases. Moreover, we simulated the impact of risk transcription factor (TF) depletions on different neural cell types spanning the developing human neocortex and observed a spatiotemporal-dependent effect for each perturbation. Finally, single-cell transcriptomics of newly generated autism-affected patient-derived NSCs in vitro revealed recurrent alterations of TFs orchestrating brain patterning and NSC lineage commitment. This work opens new perspectives to explore human brain dysfunctions at the early phases of development.

SIMS: A deep-learning label transfer tool for single-cell RNA sequencing analysis

Cell atlases serve as vital references for automating cell labeling in new samples, yet existing classification algorithms struggle with accuracy. Here we introduce SIMS (scalable, interpretable machine learning for single cell), a low-code data-efficient pipeline for single-cell RNA classification. We benchmark SIMS against datasets from different tissues and species. We demonstrate SIMS's efficacy in classifying cells in the brain, achieving high accuracy even with small training sets (<3,500 cells) and across different samples. SIMS accurately predicts neuronal subtypes in the developing brain, shedding light on genetic changes during neuronal differentiation and postmitotic fate refinement. Finally, we apply SIMS to single-cell RNA datasets of cortical organoids to predict cell identities and uncover genetic variations between cell lines. SIMS identifies cell-line differences and misannotated cell lineages in human cortical organoids derived from different pluripotent stem cell lines. Altogether, we show that SIMS is a versatile and robust tool for cell-type classification from single-cell datasets.

Spatial Single-cell Analysis Decodes Cortical Layer and Area Specification

The human cerebral cortex, pivotal for advanced cognitive functions, is composed of six distinct layers and dozens of functionally specialized areas1,2. The layers and areas are distinguished both molecularly, by diverse neuronal and glial cell subtypes, and structurally, through intricate spatial organization3,4. While single-cell transcriptomics studies have advanced molecular characterization of human cortical development, a critical gap exists due to the loss of spatial context during cell dissociation5,6,7,8. Here, we utilized multiplexed error-robust fluorescence in situ hybridization (MERFISH)9, augmented with deep-learning-based cell segmentation, to examine the molecular, cellular, and cytoarchitectural development of human fetal cortex with spatially resolved single-cell resolution. Our extensive spatial atlas, encompassing 16 million single cells, spans eight cortical areas across four time points in the second and third trimesters. We uncovered an early establishment of the six-layer structure, identifiable in the laminar distribution of excitatory neuronal subtypes by mid-gestation, long before the emergence of cytoarchitectural layers. Notably, while anterior-posterior gradients of neuronal subtypes were generally observed in most cortical areas, a striking exception was the sharp molecular border between primary (V1) and secondary visual cortices (V2) at gestational week 20. Here we discovered an abrupt binary shift in neuronal subtype specification at the earliest stages, challenging the notion that continuous morphogen gradients dictate mid-gestation cortical arealization6,10. Moreover, integrating single-nuclei RNA-sequencing and in situ whole transcriptomics revealed an early upregulation of synaptogenesis in V1-specific Layer 4 neurons, suggesting a role of synaptogenesis in this discrete border formation. Collectively, our findings underscore the crucial role of spatial relationships in determining the molecular specification of cortical layers and areas. This work not only provides a valuable resource for the field, but also establishes a spatially resolved single-cell analysis paradigm that paves the way for a comprehensive developmental atlas of the human brain.

Characterizing Large-Scale Human Circuit Development with In Vivo Neuroimaging

Large-scale coordinated patterns of neural activity are crucial for the integration of information in the human brain and to enable complex and flexible human behavior across the life span. Through recent advances in noninvasive functional magnetic resonance imaging (fMRI) methods, it is now possible to study this activity and how it emerges in the living fetal brain across the second half of human gestation. This work has demonstrated that functional activity in the fetal brain has several features in keeping with highly organized networks of activity, which are undergoing a highly programmed and rapid sequence of development before birth, in which long-range connections emerge and core features of the mature functional connectome (such as hub regions and a gradient organization) are established. In this review, the findings of these studies are summarized, their relationship to the known changes in developmental neurobiology is considered, and considerations for future work in the context of limitations to the fMRI approach are presented.

Organization of the human cerebral cortex estimated within individuals: networks, global topography, and function

The cerebral cortex is populated by specialized regions that are organized into networks. Here we estimated networks from functional MRI (fMRI) data in intensively sampled participants. The procedure was developed in two participants (scanned 31 times) and then prospectively applied to 15 participants (scanned 8-11 times). Analysis of the networks revealed a global organization. Locally organized first-order sensory and motor networks were surrounded by spatially adjacent second-order networks that linked to distant regions. Third-order networks possessed regions distributed widely throughout association cortex. Regions of distinct third-order networks displayed side-by-side juxtapositions with a pattern that repeated across multiple cortical zones. We refer to these as supra-areal association megaclusters (SAAMs). Within each SAAM, two candidate control regions were adjacent to three separate domain-specialized regions. Response properties were explored with task data. The somatomotor and visual networks responded to body movements and visual stimulation, respectively. Second-order networks responded to transients in an oddball detection task, consistent with a role in orienting to salient events. The third-order networks, including distinct regions within each SAAM, showed two levels of functional specialization. Regions linked to candidate control networks responded to working memory load across multiple stimulus domains. The remaining regions dissociated across language, social, and spatial/episodic processing domains. These results suggest that progressively higher-order networks nest outward from primary sensory and motor cortices. Within the apex zones of association cortex, there is specialization that repeatedly divides domain-flexible from domain-specialized regions. We discuss implications of these findings, including how repeating organizational motifs may emerge during development.NEW & NOTEWORTHY The organization of cerebral networks was estimated within individuals with intensive, repeat sampling of fMRI data. A hierarchical organization emerged in each individual that delineated first-, second-, and third-order cortical networks. Regions of distinct third-order association networks consistently exhibited side-by-side juxtapositions that repeated across multiple cortical zones, with clear and robust functional specialization among the embedded regions.

Two common and distinct forms of variation in human functional brain networks

The cortex has a characteristic layout with specialized functional areas forming distributed large-scale networks. However, substantial work shows striking variation in this organization across people, which relates to differences in behavior. While most previous work treats individual differences as linked to boundary shifts between the borders of regions, here we show that cortical 'variants' also occur at a distance from their typical position, forming ectopic intrusions. Both 'border' and 'ectopic' variants are common across individuals, but differ in their location, network associations, properties of subgroups of individuals, activations during tasks, and prediction of behavioral phenotypes. Border variants also track significantly more with shared genetics than ectopic variants, suggesting a closer link between ectopic variants and environmental influences. This work argues that these two dissociable forms of variation-border shifts and ectopic intrusions-must be separately accounted for in the analysis of individual differences in cortical systems across people.

Developmental maturation of millimeter-scale functional networks across brain areas

Interacting with the environment to process sensory information, generate perceptions, and shape behavior engages neural networks in brain areas with highly varied representations, ranging from unimodal sensory cortices to higher-order association areas. Recent work suggests a much greater degree of commonality across areas, with distributed and modular networks present in both sensory and non-sensory areas during early development. However, it is currently unknown whether this initially common modular structure undergoes an equally common developmental trajectory, or whether such a modular functional organization persists in some areas-such as primary visual cortex-but not others. Here we examine the development of network organization across diverse cortical regions in ferrets of both sexes using in vivo widefield calcium imaging of spontaneous activity. We find that all regions examined, including both primary sensory cortices (visual, auditory, and somatosensory-V1, A1, and S1, respectively) and higher order association areas (prefrontal and posterior parietal cortices) exhibit a largely similar pattern of changes over an approximately 3 week developmental period spanning eye opening and the transition to predominantly externally-driven sensory activity. We find that both a modular functional organization and millimeter-scale correlated networks remain present across all cortical areas examined. These networks weakened over development in most cortical areas, but strengthened in V1. Overall, the conserved maintenance of modular organization across different cortical areas suggests a common pathway of network refinement, and suggests that a modular organization-known to encode functional representations in visual areas-may be similarly engaged in highly diverse brain areas.

Metformin alters dendrite development and synaptic plasticity in rat cortical neurons

Synaptic plasticity is crucial as it dynamically molds the strength and connectivity of neural circuits, influencing learning, memory, and the development of neurological disorders. Metformin, a widely prescribed anti-diabetic medication, has been shown to readily cross the blood-brain barrier (BBB) and the placenta. However, its prolonged impact on neuronal morphology and functions remains underexplored. In this study, we investigated the influence of metformin on dendrite development and synaptic plasticity in embryonic brains and primary rat cortical neurons. Our findings reveal a negative modulation of dendrite development by metformin, as evidenced by altered dendritic arborization, impaired dendritic spine morphology and disruptions in synaptic plasticity, suggesting a potential link between metformin exposure and aberrations in neuronal connectivity. In addition, we extend our insights to the impact of maternal metformin exposure on embryonic brains, revealing a significant inhibition of dendrite development in E18.5 rat brains. In conclusion, this study adds to the expanding knowledge base on the non-metabolic effects of metformin, emphasizing the significance of assessing its potential influence on both neuronal structure and function. There is an urgent need for further investigations into the enduring impact of prolonged metformin administration on the structural and functional aspects of neurons.

Principles of cortical areas and their implications for neuroimaging

Cortical organization should constrain the study of how the brain performs behavior and cognition. A fundamental concept in cortical organization is that of arealization: that the cortex is parceled into discrete areas. In part one of this report, we review how non-human animal studies have illuminated principles of cortical arealization by revealing: (1) what defines a cortical area, (2) how cortical areas are formed, (3) how cortical areas interact with one another, and (4) what "computations" or "functions" areas perform. In part two, we discuss how these principles apply to neuroimaging research. In doing so, we highlight several examples where the commonly accepted interpretation of neuroimaging observations requires assumptions that violate the principles of arealization, including nonstationary areas that move on short time scales, large-scale gradients as organizing features, and cortical areas with singular functionality that perfectly map psychological constructs. Our belief is that principles of neurobiology should strongly guide the nature of computational explanations.

Spatial Multi-Omics in Alzheimer's Disease: A Multi-Dimensional Approach to Understanding Pathology and Progression

Alzheimer's Disease (AD) presents a complex neuropathological landscape characterized by hallmark amyloid plaques and neurofibrillary tangles, leading to progressive cognitive decline. Despite extensive research, the molecular intricacies contributing to AD pathogenesis are inadequately understood. While single-cell omics technology holds great promise for application in AD, particularly in deciphering the understanding of different cell types and analyzing rare cell types and transcriptomic expression changes, it is unable to provide spatial distribution information, which is crucial for understanding the pathological processes of AD. In contrast, spatial multi-omics research emerges as a promising and comprehensive approach to analyzing tissue cells, potentially better suited for addressing these issues in AD. This article focuses on the latest advancements in spatial multi-omics technology and compares various techniques. Additionally, we provide an overview of current spatial omics-based research results in AD. These technologies play a crucial role in facilitating new discoveries and advancing translational AD research in the future. Despite challenges such as balancing resolution, increasing throughput, and data analysis, the application of spatial multi-omics holds immense potential in revolutionizing our understanding of human disease processes and identifying new biomarkers and therapeutic targets, thereby potentially contributing to the advancement of AD research.

Early cortical GABAergic interneurons determine the projection patterns of L4 excitatory neurons

During cerebral cortex development, excitatory pyramidal neurons (PNs) establish specific projection patterns while receiving inputs from GABAergic inhibitory interneurons (INs). Whether these inhibitory inputs can shape PNs' projection patterns is, however, unknown. While layer 4 (L4) PNs of the primary somatosensory (S1) cortex are all born as long-range callosal projection neurons (CPNs), most of them acquire local connectivity upon activity-dependent elimination of their interhemispheric axons during postnatal development. Here, we demonstrate that precise developmental regulation of inhibition is key for the retraction of S1L4 PNs' callosal projections. Ablation of somatostatin INs leads to premature inhibition from parvalbumin INs onto S1L4 PNs and prevents them from acquiring their barrel-restricted local connectivity pattern. As a result, adult S1L4 PNs retain interhemispheric projections responding to tactile stimuli, and the mice lose whisker-based texture discrimination. Overall, we show that temporally ordered IN activity during development is key to shaping local ipsilateral S1L4 PNs' projection pattern, which is required for fine somatosensory processing.

A cell fate decision map reveals abundant direct neurogenesis bypassing intermediate progenitors in the human developing neocortex

The human neocortex has undergone strong evolutionary expansion, largely due to an increased progenitor population, the basal radial glial cells. These cells are responsible for the production of a diversity of cell types, but the successive cell fate decisions taken by individual progenitors remain unknown. Here we developed a semi-automated live/fixed correlative imaging method to map basal radial glial cell division modes in early fetal tissue and cerebral organoids. Through the live analysis of hundreds of dividing progenitors, we show that basal radial glial cells undergo abundant symmetric amplifying divisions, and frequent self-consuming direct neurogenic divisions, bypassing intermediate progenitors. These direct neurogenic divisions are more abundant in the upper part of the subventricular zone. We furthermore demonstrate asymmetric Notch activation in the self-renewing daughter cells, independently of basal fibre inheritance. Our results reveal a remarkable conservation of fate decisions in cerebral organoids, supporting their value as models of early human neurogenesis.

Whole-cortex in situ sequencing reveals input-dependent area identity

The cerebral cortex is composed of neuronal types with diverse gene expression that are organized into specialized cortical areas. These areas, each with characteristic cytoarchitecture1,2, connectivity3,4 and neuronal activity5,6, are wired into modular networks3,4,7. However, it remains unclear whether these spatial organizations are reflected in neuronal transcriptomic signatures and how such signatures are established in development. Here we used BARseq, a high-throughput in situ sequencing technique, to interrogate the expression of 104 cell-type marker genes in 10.3 million cells, including 4,194,658 cortical neurons over nine mouse forebrain hemispheres, at cellular resolution. De novo clustering of gene expression in single neurons revealed transcriptomic types consistent with previous single-cell RNA sequencing studies8,9. The composition of transcriptomic types is highly predictive of cortical area identity. Moreover, areas with similar compositions of transcriptomic types, which we defined as cortical modules, overlap with areas that are highly connected, suggesting that the same modular organization is reflected in both transcriptomic signatures and connectivity. To explore how the transcriptomic profiles of cortical neurons depend on development, we assessed cell-type distributions after neonatal binocular enucleation. Notably, binocular enucleation caused the shifting of the cell-type compositional profiles of visual areas towards neighbouring cortical areas within the same module, suggesting that peripheral inputs sharpen the distinct transcriptomic identities of areas within cortical modules. Enabled by the high throughput, low cost and reproducibility of BARseq, our study provides a proof of principle for the use of large-scale in situ sequencing to both reveal brain-wide molecular architecture and understand its development.

Spatiotemporal expression of thyroid hormone transporter MCT8 and THRA mRNA in human cerebral organoids recapitulating first trimester cortex development

Thyroid hormones (TH) play critical roles during nervous system development and patients carrying coding variants of MCT8 (monocarboxylate transporter 8) or THRA (thyroid hormone receptor alpha) present a spectrum of neurological phenotypes resulting from perturbed local TH action during early brain development. Recently, human cerebral organoids (hCOs) emerged as powerful in vitro tools for disease modelling recapitulating key aspects of early human cortex development. To begin exploring prospects of this model for thyroid research, we performed a detailed characterization of the spatiotemporal expression of MCT8 and THRA in developing hCOs. Immunostaining showed MCT8 membrane expression in neuronal progenitor cell types including early neuroepithelial cells, radial glia cells (RGCs), intermediate progenitors and outer RGCs. In addition, we detected robust MCT8 protein expression in deep layer and upper layer neurons. Spatiotemporal SLC16A2 mRNA expression, detected by fluorescent in situ hybridization (FISH), was highly concordant with MCT8 protein expression across cortical cell layers. FISH detected THRA mRNA expression already in neuroepithelium before the onset of neurogenesis. THRA mRNA expression remained low in the ventricular zone, increased in the subventricular zone whereas strong THRA expression was observed in excitatory neurons. In combination with a robust up-regulation of known T3 response genes following T3 treatment, these observations show that hCOs provide a promising and experimentally tractable model to probe local TH action during human cortical neurogenesis and eventually to model the consequences of impaired TH function for early cortex development.

Detailed phenotyping of Tbr1-2A-CreER knock-in mice demonstrates significant impacts on TBR1 protein levels and axon development

Spatiotemporal control of Cre-mediated recombination has been an invaluable tool for understanding key developmental processes. For example, knock-in of Cre into cell type marker gene loci drives Cre expression under endogenous promoter and enhancer sequences, greatly facilitating the study of diverse neuronal subtypes in the cerebral cortex. However, insertion of exogenous DNA into the genome can have unintended effects on local gene regulation or protein function that must be carefully considered. Here, we analyze a recently generated Tbr1-2A-CreER knock-in mouse line, where a 2A-CreER cassette was inserted in-frame just before the stop codon of the transcription factor gene Tbr1 . Heterozygous TBR1 mutations in humans and mice are known to cause autism or autism-like behavioral phenotypes accompanied by structural brain malformations, most frequently a reduction of the anterior commissure. Thus, it is critical for modified versions of Tbr1 to exhibit true wild-type-like activity. We evaluated the Tbr1-2A-CreER allele for its potential impact on Tbr1 function and complementation to Tbr1 loss-of-function alleles. In mice with one copy of the Tbr1-2A-CreER allele, we identified reduction of TBR1 protein in early postnatal cortex along with thinning of the anterior commissure, suggesting hypersensitivity of this structure to TBR1 dosage. Comparing Tbr1-2A-CreER and Tbr1 -null heterozygous and homozygous mice to Tbr1 -null complementation crosses showed reductions of TBR1 dosage ranging from 28.4% to 95.9%. Using these combinatorial genotypes, we found that low levels of TBR1 protein (∼16%) are sufficient to establish cortical layer positioning, while greater levels (>50%) are required for normal suppression of layer 5 identity. In total, these results strongly support the conclusion that Tbr1-2A-CreER is a hypomorphic allele. We advise caution when interpreting experiments using this allele, such as transcriptomic studies, considering the sensitivity of various corticogenic processes to TBR1 dosage and the association of heterozygous TBR1 mutations with complex neurodevelopmental disorders.

Alterations in subcortical magnetic susceptibility and disease-specific relationship with brain volume in major depressive disorder and schizophrenia

Quantitative susceptibility mapping is a magnetic resonance imaging technique that measures brain tissues' magnetic susceptibility, including iron deposition and myelination. This study examines the relationship between subcortical volume and magnetic susceptibility and determines specific differences in these measures among patients with major depressive disorder (MDD), patients with schizophrenia, and healthy controls (HCs). This was a cross-sectional study. Sex- and age- matched patients with MDD (n = 49), patients with schizophrenia (n = 24), and HCs (n = 50) were included. Magnetic resonance imaging was conducted using quantitative susceptibility mapping and T1-weighted imaging to measure subcortical susceptibility and volume. The acquired brain measurements were compared among groups using analyses of variance and post hoc comparisons. Finally, a general linear model examined the susceptibility-volume relationship. Significant group-level differences were found in the magnetic susceptibility of the nucleus accumbens and amygdala (p = 0.045). Post-hoc analyses indicated that the magnetic susceptibility of the nucleus accumbens and amygdala for the MDD group was significantly higher than that for the HC group (p = 0.0054, p = 0.0065, respectively). However, no significant differences in subcortical volume were found between the groups. The general linear model indicated a significant interaction between group and volume for the nucleus accumbens in MDD group but not schizophrenia or HC groups. This study showed susceptibility alterations in the nucleus accumbens and amygdala in MDD patients. A significant relationship was observed between subcortical susceptibility and volume in the MDD group's nucleus accumbens, which indicated abnormalities in myelination and the dopaminergic system related to iron deposition.

Common modular architecture across diverse cortical areas in early development

In order to deal with a complex environment, animals form a diverse range of neural representations that vary across cortical areas, ranging from largely unimodal sensory input to higher-order representations of goals, outcomes, and motivation. The developmental origin of this diversity is currently unclear, as representations could arise through processes that are already area-specific from the earliest developmental stages or alternatively, they could emerge from an initially common functional organization shared across areas. Here, we use spontaneous activity recorded with two-photon and widefield calcium imaging to reveal the functional organization across the early developing cortex in ferrets, a species with a well-characterized columnar organization and modular structure of spontaneous activity in the visual cortex. We find that in animals 7 to 14 d prior to eye-opening and ear canal opening, spontaneous activity in both sensory areas (auditory and somatosensory cortex, A1 and S1, respectively), and association areas (posterior parietal and prefrontal cortex, PPC and PFC, respectively) showed an organized and modular structure that is highly similar to the organization in V1. In all cortical areas, this modular activity was distributed across the cortical surface, forming functional networks that exhibit millimeter-scale correlations. Moreover, this modular structure was evident in highly coherent spontaneous activity at the cellular level, with strong correlations among local populations of neurons apparent in all cortical areas examined. Together, our results demonstrate a common distributed and modular organization across the cortex during early development, suggesting that diverse cortical representations develop initially according to similar design principles.

Molecular signatures of cortical expansion in the human fetal brain

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

A unified model for cross-modal plasticity and skill acquisition

Historically, cross-modal plasticity following early blindness has been largely studied in the context of visual deprivation. However, more recently, there has been a shift in focus towards understanding cross-modal plasticity from the perspective of skill acquisition: the striking plasticity observed in early blind individuals reflects the extraordinary perceptual and cognitive challenges they solve. Here, inspired by two seminal papers on skill learning (the "cortical recycling" theory) and cross-modal plasticity (the "metamodal" hypothesis) respectively, we present a unified hypothesis of cortical specialization that describes how shared functional, algorithmic, and structural constraints might mediate both types of plasticity.

Transcriptional regulation in the development and dysfunction of neocortical projection neurons

Glutamatergic projection neurons generate sophisticated excitatory circuits to integrate and transmit information among different cortical areas, and between the neocortex and other regions of the brain and spinal cord. Appropriate development of cortical projection neurons is regulated by certain essential events such as neural fate determination, proliferation, specification, differentiation, migration, survival, axonogenesis, and synaptogenesis. These processes are precisely regulated in a tempo-spatial manner by intrinsic factors, extrinsic signals, and neural activities. The generation of correct subtypes and precise connections of projection neurons is imperative not only to support the basic cortical functions (such as sensory information integration, motor coordination, and cognition) but also to prevent the onset and progression of neurodevelopmental disorders (such as intellectual disability, autism spectrum disorders, anxiety, and depression). This review mainly focuses on the recent progress of transcriptional regulations on the development and diversity of neocortical projection neurons and the clinical relevance of the failure of transcriptional modulations.

Diverse axonal morphologies of individual callosal projection neurons reveal new insights into brain connectivity

In the mature brain, functionally distinct areas connect to specific targets, mediating network activity required for function. New insights are still occurring regarding how specific connectivity occurs in the developing brain. Decades of work have revealed important insights into the molecular and genetic mechanisms regulating cell type specification in the brain. This work classified long-range projection neurons of the cerebral cortex into three major classes based on their primary target (e.g. subcortical, intracortical, and interhemispheric projections). However, painstaking single-cell mapping reveals that long-range projection neurons of the corpus callosum connect to multiple and overlapping ipsilateral and contralateral targets with often highly branched axons. In addition, their scRNA transcriptomes are highly variable, making it difficult to identify meaningful subclasses. This work has prompted us to reexamine how cortical projection neurons that comprise the corpus callosum are currently classified and how this stunning array of variability might be achieved during development.

Molecular mechanisms of corpus callosum development: a four-step journey

The Corpus Callosum (CC) is a bundle of axons connecting the cerebral hemispheres. It is the most recent structure to have appeared during evolution of placental mammals. Its development is controlled by a very complex interplay of many molecules. In humans it contains almost 80% of all commissural axons in the brain. The formation of the CC can be divided into four main stages, each controlled by numerous intracellular and extracellular molecular factors. First, a newborn neuron has to specify an axon, leave proliferative compartments, the Ventricular Zone (VZ) and Subventricular Zone (SVZ), migrate through the Intermediate Zone (IZ), and then settle at the Cortical Plate (CP). During the second stage, callosal axons navigate toward the midline within a compact bundle. Next stage is the midline crossing into contralateral hemisphere. The last step is targeting a defined area and synapse formation. This review provides an insight into these four phases of callosal axons development, as well as a description of the main molecular players involved.

Role of microglia in brain development after viral infection

Microglia are immune cells in the brain that originate from the yolk sac and enter the developing brain before birth. They play critical roles in brain development by supporting neural precursor proliferation, synaptic pruning, and circuit formation. However, microglia are also vulnerable to environmental factors, such as infection and stress that may alter their phenotype and function. Viral infection activates microglia to produce inflammatory cytokines and anti-viral responses that protect the brain from damage. However, excessive or prolonged microglial activation impairs brain development and leads to long-term consequences such as autism spectrum disorder and schizophrenia spectrum disorder. Moreover, certain viruses may attack microglia and deploy them as "Trojan horses" to infiltrate the brain. In this brief review, we describe the function of microglia during brain development and examine their roles after infection through microglia-neural crosstalk. We also identify limitations for current studies and highlight future investigated questions.

Genetics of human brain development

Brain development in humans is achieved through precise spatiotemporal genetic control, the mechanisms of which remain largely elusive. Recently, integration of technological advances in human stem cell-based modelling with genome editing has emerged as a powerful platform to establish causative links between genotypes and phenotypes directly in the human system. Here, we review our current knowledge of complex genetic regulation of each key step of human brain development through the lens of evolutionary specialization and neurodevelopmental disorders and highlight the use of human stem cell-derived 2D cultures and 3D brain organoids to investigate human-enriched features and disease mechanisms. We also discuss opportunities and challenges of integrating new technologies to reveal the genetic architecture of human brain development and disorders.

Spatiotemporal transcriptome atlas reveals the regional specification of the developing human brain

Different functional regions of brain are fundamental for basic neurophysiological activities. However, the regional specification remains largely unexplored during human brain development. Here, by combining spatial transcriptomics (scStereo-seq) and scRNA-seq, we built a spatiotemporal developmental atlas of multiple human brain regions from 6-23 gestational weeks (GWs). We discovered that, around GW8, radial glia (RG) cells have displayed regional heterogeneity and specific spatial distribution. Interestingly, we found that the regional heterogeneity of RG subtypes contributed to the subsequent neuronal specification. Specifically, two diencephalon-specific subtypes gave rise to glutamatergic and GABAergic neurons, whereas subtypes in ventral midbrain were associated with the dopaminergic neurons. Similar GABAergic neuronal subtypes were shared between neocortex and diencephalon. Additionally, we revealed that cell-cell interactions between oligodendrocyte precursor cells and GABAergic neurons influenced and promoted neuronal development coupled with regional specification. Altogether, this study provides comprehensive insights into the regional specification in the developing human brain.

Brain-charting autism and attention deficit hyperactivity disorder reveals distinct and overlapping neurobiology

Background

Autism and attention deficit hyperactivity disorder (ADHD) are heterogeneous neurodevelopmental conditions with complex underlying neurobiology. Despite overlapping presentation and sex-biased prevalence, autism and ADHD are rarely studied together, and sex differences are often overlooked. Normative modelling provides a unified framework for studying age-specific and sex-specific divergences in neurodivergent brain development.

Methods

Here we use normative modelling and a large, multi-site neuroimaging dataset to characterise cortical anatomy associated with autism and ADHD, benchmarked against models of typical brain development based on a sample of over 75,000 individuals. We also examined sex and age differences, relationship with autistic traits, and explored the co-occurrence of autism and ADHD (autism+ADHD).

Results

We observed robust neuroanatomical signatures of both autism and ADHD. Overall, autistic individuals showed greater cortical thickness and volume localised to the superior temporal cortex, whereas individuals with ADHD showed more global effects of cortical thickness increases but lower cortical volume and surface area across much of the cortex. The autism+ADHD group displayed a unique pattern of widespread increases in cortical thickness, and certain decreases in surface area. We also found evidence that sex modulates the neuroanatomy of autism but not ADHD, and an age-by-diagnosis interaction for ADHD only.

Conclusions

These results indicate distinct cortical differences in autism and ADHD that are differentially impacted by age, sex, and potentially unique patterns related to their co-occurrence.

Towards a biologically annotated brain connectome

The brain is a network of interleaved neural circuits. In modern connectomics, brain connectivity is typically encoded as a network of nodes and edges, abstracting away the rich biological detail of local neuronal populations. Yet biological annotations for network nodes - such as gene expression, cytoarchitecture, neurotransmitter receptors or intrinsic dynamics - can be readily measured and overlaid on network models. Here we review how connectomes can be represented and analysed as annotated networks. Annotated connectomes allow us to reconceptualize architectural features of networks and to relate the connection patterns of brain regions to their underlying biology. Emerging work demonstrates that annotated connectomes help to make more veridical models of brain network formation, neural dynamics and disease propagation. Finally, annotations can be used to infer entirely new inter-regional relationships and to construct new types of network that complement existing connectome representations. In summary, biologically annotated connectomes offer a compelling way to study neural wiring in concert with local biological features.

Cortical Organoid-on-a-Chip with Physiological Hypoxia for Investigating Tanshinone IIA-Induced Neural Differentiation

Cortical organoids represent cutting-edge models for mimic human brain development during the early and even middle stage of pregnancy, while they often fail to recreate the complex microenvironmental factors, such as physiological hypoxia. Herein, to recapitulate fetal brain development, we propose a novel cortical organoid-on-a-chip with physiological hypoxia and further explore the effects of tanshinone IIA (Tan IIA) in neural differentiation. The microfluidic chip was designed with a micropillar array for the controlled and efficient generation of cortical organoids. With low oxygen, the generated cortical organoids could recapitulate key aspects of early-gestational human brain development. Compared to organoids in normoxic culturing condition, the promoted neurogenesis, synaptogenesis and neuronal maturation were observed in the present microsystem, suggesting the significance of physiological hypoxia in cortical development. Based on this model, we have found that Chinese herbal drug Tan IIA could promote neural differentiation and maturation, indicating its potential therapeutic effects on neurodevelopmental disorders as well as congenital neuropsychiatric diseases. These results indicate that the proposed biomimetic cortical organoid-on-a-chip model with physiological hypoxia can offer a promising platform to simulate prenatal environment, explore brain development, and screen natural neuroactive components.

Unraveling Neuronal Identities Using SIMS: A Deep Learning Label Transfer Tool for Single-Cell RNA Sequencing Analysis

Large single-cell RNA datasets have contributed to unprecedented biological insight. Often, these take the form of cell atlases and serve as a reference for automating cell labeling of newly sequenced samples. Yet, classification algorithms have lacked the capacity to accurately annotate cells, particularly in complex datasets. Here we present SIMS (Scalable, Interpretable Machine Learning for Single-Cell), an end-to-end data-efficient machine learning pipeline for discrete classification of single-cell data that can be applied to new datasets with minimal coding. We benchmarked SIMS against common single-cell label transfer tools and demonstrated that it performs as well or better than state of the art algorithms. We then use SIMS to classify cells in one of the most complex tissues: the brain. We show that SIMS classifies cells of the adult cerebral cortex and hippocampus at a remarkably high accuracy. This accuracy is maintained in trans-sample label transfers of the adult human cerebral cortex. We then apply SIMS to classify cells in the developing brain and demonstrate a high level of accuracy at predicting neuronal subtypes, even in periods of fate refinement, shedding light on genetic changes affecting specific cell types across development. Finally, we apply SIMS to single cell datasets of cortical organoids to predict cell identities and unveil genetic variations between cell lines. SIMS identifies cell-line differences and misannotated cell lineages in human cortical organoids derived from different pluripotent stem cell lines. When cell types are obscured by stress signals, label transfer from primary tissue improves the accuracy of cortical organoid annotations, serving as a reliable ground truth. Altogether, we show that SIMS is a versatile and robust tool for cell-type classification from single-cell datasets.

Loss of CNTNAP2 Alters Human Cortical Excitatory Neuron Differentiation and Neural Network Development

BACKGROUND

Loss-of-function mutations in the contactin-associated protein-like 2 (CNTNAP2) gene are causal for neurodevelopmental disorders, including autism, schizophrenia, epilepsy, and intellectual disability. CNTNAP2 encodes CASPR2, a single-pass transmembrane protein that belongs to the neurexin family of cell adhesion molecules. These proteins have a variety of functions in developing neurons, including connecting presynaptic and postsynaptic neurons, and mediating signaling across the synapse.

METHODS

To study the effect of loss of CNTNAP2 function on human cerebral cortex development, and how this contributes to the pathogenesis of neurodevelopmental disorders, we generated human induced pluripotent stem cells from one neurotypical control donor null for full-length CNTNAP2, modeling cortical development from neurogenesis through to neural network formation in vitro.

RESULTS

CNTNAP2 is particularly highly expressed in the first two populations of early-born excitatory cortical neurons, and loss of CNTNAP2 shifted the relative proportions of these two neuronal types. Live imaging of excitatory neuronal growth showed that loss of CNTNAP2 reduced neurite branching and overall neuronal complexity. At the network level, developing cortical excitatory networks null for CNTNAP2 had complex changes in activity compared with isogenic controls: an initial period of relatively reduced activity compared with isogenic controls, followed by a lengthy period of hyperexcitability, and then a further switch to reduced activity.

CONCLUSIONS

Complete loss of CNTNAP2 contributes to the pathogenesis of neurodevelopmental disorders through complex changes in several aspects of human cerebral cortex excitatory neuron development that culminate in aberrant neural network formation and function.

Cell lineage analysis with somatic mutations reveals late divergence of neuronal cell types and cortical areas in human cerebral cortex

The mammalian cerebral cortex shows functional specialization into regions with distinct neuronal compositions, most strikingly in the human brain, but little is known in about how cellular lineages shape cortical regional variation and neuronal cell types during development. Here, we use somatic single nucleotide variants (sSNVs) to map lineages of neuronal sub-types and cortical regions. Early-occurring sSNVs rarely respect Brodmann area (BA) borders, while late-occurring sSNVs mark neuron-generating clones with modest regional restriction, though descendants often dispersed into neighboring BAs. Nevertheless, in visual cortex, BA17 contains 30-70% more sSNVs compared to the neighboring BA18, with clones across the BA17/18 border distributed asymmetrically and thus displaying different cortex-wide dispersion patterns. Moreover, we find that excitatory neuron-generating clones with modest regional restriction consistently share low-mosaic sSNVs with some inhibitory neurons, suggesting significant co-generation of excitatory and some inhibitory neurons in the dorsal cortex. Our analysis reveals human-specific cortical cell lineage patterns, with both regional inhomogeneities in progenitor proliferation and late divergence of excitatory/inhibitory lineages.

Neurogenesis in primates versus rodents and the value of non-human primate models

Neurogenesis, the process of generating neurons from neural stem cells, occurs during both embryonic and adult stages, with each stage possessing distinct characteristics. Dysfunction in either stage can disrupt normal neural development, impair cognitive functions, and lead to various neurological disorders. Recent technological advancements in single-cell multiomics and gene-editing have facilitated investigations into primate neurogenesis. Here, we provide a comprehensive overview of neurogenesis across rodents, non-human primates, and humans, covering embryonic development to adulthood and focusing on the conservation and diversity among species. While non-human primates, especially monkeys, serve as valuable models with closer neural resemblance to humans, we highlight the potential impacts and limitations of non-human primate models on both physiological and pathological neurogenesis research.

Secretagogin as a marker to distinguish between different neuron types in human frontal and temporal cortex

The principal aim of the present work was to chemically characterize the population of neurons labeled for the calcium binding protein secretagogin (SCGN) in the human frontal and temporal cortices (Brodmann's area 10 and 21, respectively). Both cortical regions are involved in many high cognitive functions that are especially well developed (or unique) in humans, but with different functional roles. The pattern of SCGN immunostaining was rather similar in BA10 and BA21, with all the labeled neurons displaying a non-pyramidal morphology (interneurons). Although SCGN cells were present throughout all layers, they were more frequently observed in layers II, III and IV, whereas in layer I they were found only occasionally. We examined the degree of colocalization of SCGN with parvalbumin (PV) and calretinin (CR), as well as with nitric oxide synthase (nNOS; the enzyme responsible for the synthesis of nitric oxide by neurons) by triple immunostaining. We looked for possible similarities or differences in the coexpression patterns of SCGN with PV, CR and nNOS between BA10 and BA21 throughout the different cortical layers (I-VI). The percentage of colocalization was estimated by counting the number of all labeled cells through columns (1,100-1,400 μm wide) across the entire thickness of the cortex (from the pial surface to the white matter) in 50 μm-thick sections. Several hundred neurons were examined in both cortical regions. We found that SCGN cells include multiple neurochemical subtypes, whose abundance varies according to the cortical area and layer. The present results further highlight the regional specialization of cortical neurons and underline the importance of performing additional experiments to characterize the subpopulation of SCGN cells in the human cerebral cortex in greater detail.

The regional variation of laminar thickness in the human isocortex is related to cortical hierarchy and interregional connectivity

The human isocortex consists of tangentially organized layers with unique cytoarchitectural properties. These layers show spatial variations in thickness and cytoarchitecture across the neocortex, which is thought to support function through enabling targeted corticocortical connections. Here, leveraging maps of the 6 cortical layers based on 3D human brain histology, we aimed to quantitatively characterize the systematic covariation of laminar structure in the cortex and its functional consequences. After correcting for the effect of cortical curvature, we identified a spatial pattern of changes in laminar thickness covariance from lateral frontal to posterior occipital regions, which differentiated the dominance of infra- versus supragranular layer thickness. Corresponding to the laminar regularities of cortical connections along cortical hierarchy, the infragranular-dominant pattern of laminar thickness was associated with higher hierarchical positions of regions, mapped based on resting-state effective connectivity in humans and tract-tracing of structural connections in macaques. Moreover, we show that regions with similar laminar thickness patterns have a higher likelihood of structural connections and strength of functional connections. In sum, here we characterize the organization of laminar thickness in the human isocortex and its association with cortico-cortical connectivity, illustrating how laminar organization may provide a foundational principle of cortical function.

Asymmetric inheritance of centrosomes maintains stem cell properties in human neural progenitor cells

During human forebrain development, neural progenitor cells (NPCs) in the ventricular zone (VZ) undergo asymmetric cell divisions to produce a self-renewed progenitor cell, maintaining the potential to go through additional rounds of cell divisions, and differentiating daughter cells, populating the developing cortex. Previous work in the embryonic rodent brain suggested that the preferential inheritance of the pre-existing (older) centrosome to the self-renewed progenitor cell is required to maintain stem cell properties, ensuring proper neurogenesis. If asymmetric segregation of centrosomes occurs in NPCs of the developing human brain, which depends on unique molecular regulators and species-specific cellular composition, remains unknown. Using a novel, recombination-induced tag exchange-based genetic tool to birthdate and track the segregation of centrosomes over multiple cell divisions in human embryonic stem cell-derived regionalised forebrain organoids, we show the preferential inheritance of the older mother centrosome towards self-renewed NPCs. Aberration of asymmetric segregation of centrosomes by genetic manipulation of the centrosomal, microtubule-associated protein Ninein alters fate decisions of NPCs and their maintenance in the VZ of human cortical organoids. Thus, the data described here use a novel genetic approach to birthdate centrosomes in human cells and identify asymmetric inheritance of centrosomes as a mechanism to maintain self-renewal properties and to ensure proper neurogenesis in human NPCs.

Molecular programs of regional specification and neural stem cell fate progression in macaque telencephalon

During early telencephalic development, intricate processes of regional patterning and neural stem cell (NSC) fate specification take place. However, our understanding of these processes in primates, including both conserved and species-specific features, remains limited. Here, we profiled 761,529 single-cell transcriptomes from multiple regions of the prenatal macaque telencephalon. We deciphered the molecular programs of the early organizing centers and their cross-talk with NSCs, revealing primate-biased galanin-like peptide (GALP) signaling in the anteroventral telencephalon. Regional transcriptomic variations were observed along the frontotemporal axis during early stages of neocortical NSC progression and in neurons and astrocytes. Additionally, we found that genes associated with neuropsychiatric disorders and brain cancer risk might play critical roles in the early telencephalic organizers and during NSC progression.

Targeted approaches to delineate neuronal morphology during early development

Understanding the developmental changes that affect neurons is a key step in exploring the assembly and maturation of neural circuits in the brain. For decades, researchers have used a number of labeling techniques to visualize neuronal morphology at different stages of development. However, the efficiency and accuracy of neuronal labeling technologies are limited by the complexity and fragility of neonatal brains. In this review, we illustrate the various labeling techniques utilized for examining the neurogenesis and morphological changes occurring during the early stages of development. We compare the advantages and limitations of each technique from different aspects. Then, we highlight the gaps remaining in our understanding of the structure of neurons in the neonatal mouse brain.

Gestational exposure to FireMaster® 550 (FM 550) disrupts the placenta-brain axis in a socially monogamous rodent species, the prairie vole (Microtus ochrogaster)

Gestational flame retardant (FR) exposure has been linked to heightened risk of neurodevelopmental disorders, but the mechanisms remain largely unknown. Historically, toxicologists have relied on traditional, inbred rodent models, yet those do not always best model human vulnerability or biological systems, especially social systems. Here we used prairie voles (Microtus ochrogaster), a monogamous and bi-parental rodent, leveraged for decades to decipher the underpinnings of social behaviors, to examine the impact of fetal FR exposure on gene targets in the mid-gestational placenta and fetal brain. We previously established gestational exposure to the commercial mixture Firemaster 550 (FM 550) impairs sociality, particularly in males. FM 550 exposure disrupted placental monoamine production, particularly serotonin, and genes required for axon guidance and cellular respiration in the fetal brains. Effects were dose and sex specific. These data provide insights on the mechanisms by which FRs impair neurodevelopment and later in life social behaviors.

Unravelling the liver-brain connection: A two-sample Mendelian randomization study investigating the causal relationship between NAFLD and cortical structure

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) has been linked to cognitive decline and neuropsychiatric conditions, implying a potential connection between NAFLD and brain health. However, the causal association between NAFLD and cortical changes remains uncertain. This study aimed to examine the causal impact of NAFLD on cortical structures using a two-sample Mendelian randomization (MR) approach.

METHODS

Summary data from genome-wide association studies (GWAS) for NAFLD were gathered from large-scale cohorts. Surface area (SA) and cortical thickness (TH) measurements were derived from Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium magnetic resonance imaging (MRI) data of 33,992 participants. Inverse-variance weighted (IVW) served as the primary method. Additional sensitivity analyses, including MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO), MR-Egger, and weighted median procedures, were conducted to detect heterogeneity and pleiotropy.

RESULTS

Our MR analysis revealed that NAFLD led to notable alterations in cortical structures, particularly in the pars orbitalis gyrus. Specifically, genetically predicted NAFLD was linked to a decrease in TH (β = -0.008 mm, 95 % CI: -0.013 mm to -0.004 mm, P = 3.00 × 10-4) within this region. No significant heterogeneity and pleiotropy were identified.

CONCLUSION

The two-sample MR study supports the existence of a liver-brain axis by demonstrating a causal association between NAFLD and changes in cortical structures. These findings emphasize the potential association between NAFLD and brain health, which could have implications for preventing and treating cognitive deficits and neuropsychiatric conditions in patients with NAFLD.