The human brain in numbers: a linearly scaled-up primate brain

Using Organoids to Model Sex Differences in the Human Brain

Sex differences are widespread during neurodevelopment and play a role in neuropsychiatric conditions such as autism, which is more prevalent in males than females. In humans, males have been shown to have larger brain volumes than females with development of the hippocampus and amygdala showing prominent sex differences. Mechanistically, sex steroids and sex chromosomes drive these differences in brain development, which seem to peak during prenatal and pubertal stages. Animal models have played a crucial role in understanding sex differences, but the study of human sex differences requires an experimental model that can recapitulate complex genetic traits. To fill this gap, human induced pluripotent stem cell-derived brain organoids are now being used to study how complex genetic traits influence prenatal brain development. For example, brain organoids from individuals with autism and individuals with X chromosome-linked Rett syndrome and fragile X syndrome have revealed prenatal differences in cell proliferation, a measure of brain volume differences, and excitatory-inhibitory imbalances. Brain organoids have also revealed increased neurogenesis of excitatory neurons due to androgens. However, despite growing interest in using brain organoids, several key challenges remain that affect its validity as a model system. In this review, we discuss how sex steroids and the sex chromosomes each contribute to sex differences in brain development. Then, we examine the role of X chromosome inactivation as a factor that drives sex differences. Finally, we discuss the combined challenges of modeling X chromosome inactivation and limitations of brain organoids that need to be taken into consideration when studying sex differences.

Multivariate pattern analysis of medical imaging-based Alzheimer's disease

Alzheimer's disease (AD) is a devastating brain disorder that steadily worsens over time. It is marked by a relentless decline in memory and cognitive abilities. As the disease progresses, it leads to a significant loss of mental function. Early detection of AD is essential to starting treatments that can mitigate the progression of this disease and enhance patients' quality of life. This study aims to observe AD's brain functional connectivity pattern to extract essential patterns through multivariate pattern analysis (MVPA) and analyze activity patterns across multiple brain voxels. The optimized feature extraction techniques are used to obtain the important features for performing the training on the models using several hybrid machine learning classifiers for performing binary classification and multi-class classification. The proposed approach using hybrid machine learning classification has been applied to two public datasets named the Open Access Series of Imaging Studies (OASIS) and the AD Neuroimaging Initiative (ADNI). The results are evaluated using performance metrics, and comparisons have been made to differentiate between different stages of AD using visualization tools.

Advances in the Differentiation of hiPSCs into Cerebellar Neuronal Cells

The cerebellum has historically been primarily associated with the regulation of precise motor functions. However, recent findings suggest that it also plays a pivotal role in the development of advanced cognitive functions, including learning, memory, and emotion regulation. Pathological changes in the cerebellum, whether congenital hereditary or acquired degenerative, can result in a diverse spectrum of disorders, ranging from genetic spinocerebellar ataxias to psychiatric conditions such as autism, and schizophrenia. While studies in animal models have significantly contributed to our understanding of the genetic networks governing cerebellar development, it is important to note that the human cerebellum follows a protracted developmental timeline compared to the neocortex. Consequently, employing animal models to uncover human-specific molecular events in cerebellar development presents significant challenges. The emergence of human induced pluripotent stem cells (hiPSCs) has provided an invaluable tool for creating human-based culture systems, enabling the modeling and analysis of cerebellar physiology and pathology. hiPSCs and their differentiated progenies can be derived from patients with specific disorders or carrying distinct genetic variants. Importantly, they preserve the unique genetic signatures of the individuals from whom they originate, allowing for the elucidation of human-specific molecular and cellular processes involved in cerebellar development and related disorders. This review focuses on the technical advancements in the utilization of hiPSCs for the generation of both 2D cerebellar neuronal cells and 3D cerebellar organoids.

Unraveling the complexity of human brain: Structure, function in healthy and disease states

The human brain stands as an intricate organ, embodying a nexus of structure, function, development, and diversity. This review delves into the multifaceted landscape of the brain, spanning its anatomical intricacies, diverse functional capacities, dynamic developmental trajectories, and inherent variability across individuals. The dynamic process of brain development, from early embryonic stages to adulthood, highlights the nuanced changes that occur throughout the lifespan. The brain, a remarkably complex organ, is composed of various anatomical regions, each contributing uniquely to its overall functionality. Through an exploration of neuroanatomy, neurophysiology, and electrophysiology, this review elucidates how different brain structures interact to support a wide array of cognitive processes, sensory perception, motor control, and emotional regulation. Moreover, it addresses the impact of age, sex, and ethnic background on brain structure and function, and gender differences profoundly influence the onset, progression, and manifestation of brain disorders shaped by genetic, hormonal, environmental, and social factors. Delving into the complexities of the human brain, it investigates how variations in anatomical configuration correspond to diverse functional capacities across individuals. Furthermore, it examines the impact of neurodegenerative diseases on the structural and functional integrity of the brain. Specifically, our article explores the pathological processes underlying neurodegenerative diseases, such as Alzheimer's, Parkinson's, and Huntington's diseases, shedding light on the structural alterations and functional impairments that accompany these conditions. We will also explore the current research trends in neurodegenerative diseases and identify the existing gaps in the literature. Overall, this article deepens our understanding of the fundamental principles governing brain structure and function and paves the way for a deeper understanding of individual differences and tailored approaches in neuroscience and clinical practice-additionally, a comprehensive understanding of structural and functional changes that manifest in neurodegenerative diseases.

A Comparison of Rapid Rule-Learning Strategies in Humans and Monkeys

Interspecies comparisons are key to deriving an understanding of the behavioral and neural correlates of human cognition from animal models. We perform a detailed comparison of the strategies of female macaque monkeys to male and female humans on a variant of the Wisconsin Card Sorting Test (WCST), a widely studied and applied task that provides a multiattribute measure of cognitive function and depends on the frontal lobe. WCST performance requires the inference of a rule change given ambiguous feedback. We found that well-trained monkeys infer new rules three times more slowly than minimally instructed humans. Input-dependent hidden Markov model-generalized linear models were fit to their choices, revealing hidden states akin to feature-based attention in both species. Decision processes resembled a win-stay, lose-shift strategy with interspecies similarities as well as key differences. Monkeys and humans both test multiple rule hypotheses over a series of rule-search trials and perform inference-like computations to exclude candidate choice options. We quantitatively show that perseveration, random exploration, and poor sensitivity to negative feedback account for the slower task-switching performance in monkeys.

Cerebellar Heterogeneity and Selective vulnerability in Spinocerebellar Ataxia Type 1 (SCA1)

Heterogeneity is one of the key features of the healthy brain and selective vulnerability characterizes many, if not all, neurodegenerative diseases. While cerebellum contains majority of brain cells, neither its heterogeneity nor selective vulnerability in disease are well understood. Here we describe molecular, cellular and functional heterogeneity in the context of healthy cerebellum as well as in cerebellar disease Spinocerebellar Ataxia Type 1 (SCA1). We first compared disease pathology in cerebellar vermis and hemispheres across anterior to posterior axis in a knock-in SCA1 mouse model. Using immunohistochemistry, we demonstrated earlier and more severe pathology of PCs and glia in the posterior cerebellar vermis of SCA1 mice. We also demonstrate heterogeneity of Bergmann glia in the unaffected, wild-type mice. Then, using RNA sequencing, we found both shared, as well as, posterior cerebellum-specific molecular mechanisms of pathogenesis that include exacerbated gene dysregulation, increased number of altered signaling pathways, and decreased pathway activity scores in the posterior cerebellum of SCA1 mice. We demonstrated unexpectedly large differences in the gene expression between posterior and anterior cerebellar vermis of wild-type mice, indicative of robust intraregional heterogeneity of gene expression in the healthy cerebellum. Additionally, we found that SCA1 disease profoundly reduces intracerebellar heterogeneity of gene expression. Further, using fiber photometry, we found that population level PC calcium activity was altered in the posterior lobules in SCA1 mice during walking. We also identified regional differences in the population level activity of Purkinje cells (PCs) in unrestrained wild-type mice that were diminished in SCA1 mice.

A boundary element method of bidomain modeling for predicting cellular responses to electromagnetic fields

Objective.Commonly used cable equation approaches for simulating the effects of electromagnetic fields on excitable cells make several simplifying assumptions that could limit their predictive power. Bidomain or 'whole' finite element methods have been developed to fully couple cells and electric fields for more realistic neuron modeling. Here, we introduce a novel bidomain integral equation designed for determining the full electromagnetic coupling between stimulation devices and the intracellular, membrane, and extracellular regions of neurons.Approach.Our proposed boundary element formulation offers a solution to an integral equation that connects the device, tissue inhomogeneity, and cell membrane-induced E-fields. We solve this integral equation using first-order nodal elements and an unconditionally stable Crank-Nicholson time-stepping scheme. To validate and demonstrate our approach, we simulated cylindrical Hodgkin-Huxley axons and spherical cells in multiple brain stimulation scenarios.Main Results.Comparison studies show that a boundary element approach produces accurate results for both electric and magnetic stimulation. Unlike bidomain finite element methods, the bidomain boundary element method does not require volume meshes containing features at multiple scales. As a result, modeling cells, or tightly packed populations of cells, with microscale features embedded in a macroscale head model, is simplified, and the relative placement of devices and cells can be varied without the need to generate a new mesh.Significance.Device-induced electromagnetic fields are commonly used to modulate brain activity for research and therapeutic applications. Bidomain solvers allow for the full incorporation of realistic cell geometries, device E-fields, and neuron populations. Thus, multi-cell studies of advanced neuronal mechanisms would greatly benefit from the development of fast-bidomain solvers to ensure scalability and the practical execution of neural network simulations with realistic neuron morphologies.

The Networking Brain: How Extracellular Matrix, Cellular Networks, and Vasculature Shape the In Vivo Mechanical Properties of the Brain

Mechanically, the brain is characterized by both solid and fluid properties. The resulting unique material behavior fosters proliferation, differentiation, and repair of cellular and vascular networks, and optimally protects them from damaging shear forces. Magnetic resonance elastography (MRE) is a noninvasive imaging technique that maps the mechanical properties of the brain in vivo. MRE studies have shown that abnormal processes such as neuronal degeneration, demyelination, inflammation, and vascular leakage lead to tissue softening. In contrast, neuronal proliferation, cellular network formation, and higher vascular pressure result in brain stiffening. In addition, brain viscosity has been reported to change with normal blood perfusion variability and brain maturation as well as disease conditions such as tumor invasion. In this article, the contributions of the neuronal, glial, extracellular, and vascular networks are discussed to the coarse-grained parameters determined by MRE. This reductionist multi-network model of brain mechanics helps to explain many MRE observations in terms of microanatomical changes and suggests that cerebral viscoelasticity is a suitable imaging marker for brain disease.

Temporal patterning of the vertebrate developing neural tube

The chronologically ordered generation of distinct cell types is essential for the establishment of neuronal diversity and the formation of neuronal circuits. Recently, single-cell transcriptomic analyses of various areas of the developing vertebrate nervous system have provided evidence for the existence of a shared temporal patterning program that partitions neurons based on the timing of neurogenesis. In this review, I summarize the findings that lead to the proposal of this shared temporal program before focusing on the developing spinal cord to discuss how temporal patterning in general and this program specifically contributes to the ordered formation of neuronal circuits.

A molecular and cellular perspective on human brain evolution and tempo

The evolution of the modern human brain was accompanied by distinct molecular and cellular specializations, which underpin our diverse cognitive abilities but also increase our susceptibility to neurological diseases. These features, some specific to humans and others shared with related species, manifest during different stages of brain development. In this multi-stage process, neural stem cells proliferate to produce a large and diverse progenitor pool, giving rise to excitatory or inhibitory neurons that integrate into circuits during further maturation. This process unfolds over varying time scales across species and has progressively become slower in the human lineage, with differences in tempo correlating with differences in brain size, cell number and diversity, and connectivity. Here we introduce the terms 'bradychrony' and 'tachycrony' to describe slowed and accelerated developmental tempos, respectively. We review how recent technical advances across disciplines, including advanced engineering of in vitro models, functional comparative genetics and high-throughput single-cell profiling, are leading to a deeper understanding of how specializations of the human brain arise during bradychronic neurodevelopment. Emerging insights point to a central role for genetics, gene-regulatory networks, cellular innovations and developmental tempo, which together contribute to the establishment of human specializations during various stages of neurodevelopment and at different points in evolution.

Multiscale Modes of Functional Brain Connectivity

Information processing in the brain spans from localised sensorimotor processes to higher-level cognition that integrates across multiple regions. Interactions between and within these subsystems enable multiscale information processing. Despite this multiscale characteristic, functional brain connectivity is often either estimated based on 10-30 distributed modes or parcellations with 100-1000 localised parcels, both missing across-scale functional interactions. We present Multiscale Probabilistic Functional Modes (mPFMs), a new mapping which comprises modes over various scales of granularity, thus enabling direct estimation of functional connectivity within- and across-scales. Crucially, mPFMs emerged from data-driven multilevel Bayesian modelling of large functional MRI (fMRI) populations. We demonstrate that mPFMs capture both distributed brain modes and their co-existing subcomponents. In addition to validating mPFMs using simulations and real data, we show that mPFMs can predict ~900 personalised traits from UK Biobank more accurately than current standard techniques. Therefore, mPFMs can offer a paradigm shift in functional connectivity modelling and yield enhanced fMRI biomarkers for traits and diseases.

Bimanual coordinated motor skill learning in patients with a chronic cerebellar stroke

Cerebellar strokes induce coordination disorders that can affect activities of daily living. Evidence-based neurorehabilitation programs are founded on motor learning principles. The cerebellum is a key neural structure in motor learning. It is unknown whether and how well chronic cerebellar stroke individuals (CCSIs) can learn to coordinate their upper limbs through bimanual motor skill learning. The aim was to determine whether CCSIs could achieve bimanual skill learning through a serious game with the REAplan® robot and to compare CCSIs with healthy individuals (HIs). Over three consecutive days, sixteen CCSIs and eighteen HIs were trained on an asymmetric bimanual coordination task ("CIRCUIT" game) with the REAplan® robot, allowing quantification of speed, accuracy and coordination. The primary outcomes were the bimanual speed/accuracy trade-off (BiSAT) and bimanual coordination factor (BiCo). They were also evaluated on a bimanual REACHING task on Days 1 and 3. Correlation analyses between the robotic outcomes and clinical scale scores were computed. Throughout the sessions, BiSAT and BiCo improved during the CIRCUIT task in both HIs and CCSIs. On Day 3, HIs and CCSIs showed generalization of BiSAT, BiCo and transferred to the REACHING task. There was no significant between-group difference in progression. Four CCSIs and two HIs were categorized as "poor learners" according to BiSAT and/or BiCo. Increasing age correlated with reduced BiSAT but not BiCo progression. Over three days of training, HIs and CCSIs improved, retained, generalized and transferred a coordinated bimanual skill. There was no between-group difference, suggesting plastic compensation in CCSIs. Clinical trial NCT04642599 approved the 24th of November 2020.

A common tumour in a rare location: a single centre case series of cerebellar glioblastoma

Although glioblastoma is the commonest primary brain tumour in adults, its location in the cerebellum is extremely rare. We present thirteen cases (3 female, 10 male; median age at presentation 56 [age range 21-77]) of surgically managed, histologically confirmed, primary cerebellar glioblastoma (cGB) over a 17 year period (2005-2022). Pre-operative radiological diagnosis was challenging given cGB rarity, although MRI demonstrated ring enhancement in all cases. Surgical management included posterior fossa craniectomy and debulking in 11 cases and burr hole biopsy in two. CSF diversion was necessary in four cases. No evidence of IDH or ATRX gene mutations was found when tested. Survival ranged from 1 to 22 months after diagnosis (mean 10.9 months). We also seek to understand why glioblastoma is rare in this location and discuss potential reasons for this. We hypothesise that increasing anatomical distance from germinal regions and decreased local endogenous neural stem cell activity (which has been associated with glioblastoma) may explain why glioblastoma is rare in the cerebellum. We hereby seek to add to the limited literature on cGB as this is the largest UK cGB series to date.

CBGTPy: An extensible cortico-basal ganglia-thalamic framework for modeling biological decision making

Here we introduce CBGTPy, a virtual environment for designing and testing goal-directed agents with internal dynamics that are modeled on the cortico-basal-ganglia-thalamic (CBGT) pathways in the mammalian brain. CBGTPy enables researchers to investigate the internal dynamics of the CBGT system during a variety of tasks, allowing for the formation of testable predictions about animal behavior and neural activity. The framework has been designed around the principle of flexibility, such that many experimental parameters in a decision making paradigm can be easily defined and modified. Here we demonstrate the capabilities of CBGTPy across a range of single and multi-choice tasks, highlighting the ease of set up and the biologically realistic behavior that it produces. We show that CBGTPy is extensible enough to apply to a range of experimental protocols and to allow for the implementation of model extensions with minimal developmental effort.

Author summary

We introduce a toolbox for producing biologically realistic simulations of the cortico-basal ganglia-thalamic dynamics during a variety of experimental tasks. The purpose is to foster the theory-experiment cycle, offering a tool for generating testable predictions of behavioral and neural responses that can be validated experimentally, in a framework that allows for simple updating as new experimental evidence emerges. We outline how our toolbox works and demonstrate its performance on a set of normative cognitive tasks.

Imitating and exploring the human brain's resting and task-performing states via brain computing: scaling and architecture

A computational human brain model with the voxel-wise assimilation method was established based on individual structural and functional imaging data. We found that the more similar the brain model is to the biological counterpart in both scale and architecture, the more similarity was found between the assimilated model and the biological brain both in resting states and during tasks by quantitative metrics. The hypothesis that resting state activity reflects internal body states was validated by the interoceptive circuit's capability to enhance the similarity between the simulation model and the biological brain. We identified that the removal of connections from the primary visual cortex (V1) to downstream visual pathways significantly decreased the similarity at the hippocampus between the model and its biological counterpart, despite a slight influence on the whole brain. In conclusion, the model and methodology present a solid quantitative framework for a digital twin brain for discovering the relationship between brain architecture and functions, and for digitally trying and testing diverse cognitive, medical and lesioning approaches that would otherwise be unfeasible in real subjects.

Cortical brain organoid slices (cBOS) for the study of human neural cells in minimal networks

Brain organoids derived from human pluripotent stem cells are a promising tool for studying human neurodevelopment and related disorders. Here, we generated long-term cultures of cortical brain organoid slices (cBOS) grown at the air-liquid interphase from regionalized cortical organoids. We show that cBOS host mature neurons and astrocytes organized in complex architecture. Whole-cell patch-clamp demonstrated subthreshold synaptic inputs and action potential firing of neurons. Spontaneous intracellular calcium signals turned into synchronous large-scale oscillations upon combined disinhibition of NMDA receptors and blocking of GABAA receptors. Brief metabolic inhibition to mimic transient energy restriction in the ischemic brain induced reversible intracellular calcium loading of cBOS. Moreover, metabolic inhibition induced a reversible decline in neuronal ATP as revealed by ATeam1.03YEMK. Overall, cBOS provide a powerful platform to assess morphological and functional aspects of human neural cells in intact minimal networks and to address the pathways that drive cellular damage during brain ischemia.

The ins and outs of microglial cells in brain health and disease

Microglia are the brain's resident macrophages that play pivotal roles in immune surveillance and maintaining homeostasis of the Central Nervous System (CNS). Microglia are functionally implicated in various cerebrovascular diseases, including stroke, aneurysm, and tumorigenesis as they regulate neuroinflammatory responses and tissue repair processes. Here, we review the manifold functions of microglia in the brain under physiological and pathological conditions, primarily focusing on the implication of microglia in glioma propagation and progression. We further review the current status of therapies targeting microglial cells, including their re-education, depletion, and re-population approaches as therapeutic options to improve patient outcomes for various neurological and neuroinflammatory disorders, including cancer.

Oxygen and the Spark of Human Brain Evolution: Complex Interactions of Metabolism and Cortical Expansion across Development and Evolution

Scientific theories on the functioning and dysfunction of the human brain require an understanding of its development-before and after birth and through maturation to adulthood-and its evolution. Here we bring together several accounts of human brain evolution by focusing on the central role of oxygen and brain metabolism. We argue that evolutionary expansion of human transmodal association cortices exceeded the capacity of oxygen delivery by the vascular system, which led these brain tissues to rely on nonoxidative glycolysis for additional energy supply. We draw a link between the resulting lower oxygen tension and its effect on cytoarchitecture, which we posit as a key driver of genetic developmental programs for the human brain-favoring lower intracortical myelination and the presence of biosynthetic materials for synapse turnover. Across biological and temporal scales, this protracted capacity for neural plasticity sets the conditions for cognitive flexibility and ongoing learning, supporting complex group dynamics and intergenerational learning that in turn enabled improved nutrition to fuel the metabolic costs of further cortical expansion. Our proposed model delineates explicit mechanistic links among metabolism, molecular and cellular brain heterogeneity, and behavior, which may lead toward a clearer understanding of brain development and its disorders.

Input and Output Connections of the Crow Nidopallium Caudolaterale

The avian telencephalic structure nidopallium caudolaterale (NCL) functions as an analog to the mammalian prefrontal cortex. In crows, corvid songbirds, it plays a crucial role in higher cognitive and executive functions. These functions rely on the NCL's extensive telencephalic connections. However, systematic investigations into the brain-wide connectivity of the NCL in crows or other songbirds are lacking. Here, we studied its input and output connections by injecting retrograde and anterograde tracers into the carrion crow NCL. Our results, mapped onto a published carrion crow brain atlas, confirm NCL multisensory connections and extend prior pigeon findings by identifying a novel input from the hippocampal formation. Furthermore, we analyze crow NCL efferent projections to the arcopallium and report newly identified arcopallial neurons projecting bilaterally to the NCL. These findings help to clarify the role of the NCL as central executive hub in the corvid songbird brain.

Opportunities and obstacles in non-invasive brain stimulation

Non-invasive brain stimulation (NIBS) is a complex and multifaceted approach to modulating brain activity and holds the potential for broad accessibility. This work discusses the mechanisms of the four distinct approaches to modulating brain activity non-invasively: electrical currents, magnetic fields, light, and ultrasound. We examine the dual stochastic and deterministic nature of brain activity and its implications for NIBS, highlighting the challenges posed by inter-individual variability, nebulous dose-response relationships, potential biases and neuroanatomical heterogeneity. Looking forward, we propose five areas of opportunity for future research: closed-loop stimulation, consistent stimulation of the intended target region, reducing bias, multimodal approaches, and strategies to address low sample sizes.

Transgenerational inheritance of methylmercury and vitamin A-induced toxicological effects in a Wistar rats environmental-based model

Mercury (Hg) and vitamin A (VitA) are two environmental factors with potential health impacts, especially during pregnancy and early childhood. Fish and seafood may present elevated levels of methylmercury (MeHg), the major Hg derivative, and VitA. This study aimed to evaluate the transgenerational effects of exposure to MeHg and/or VitA on epigenetic and toxicological parameters in a Wistar rat model. Our findings revealed persistent toxicological effects in generations F1 and F2 following low/mild doses of MeHg and/or VitA exposure during dams' (F0) gestation and breastfeeding. Toxicological effects observed in F2 included chronic DNA damage, bone marrow toxicity, altered microglial content, reduced neuronal signal, and diminished male longevity. Sex-specific patterns were also observed. Co-exposure to MeHg and VitA showed both synergistic and antagonistic effects. Additionally, the study demonstrated that MeHg and VitA affected histone methylation and caused consistent effects in F2. While MeHg exposure has been associated with transgenerational inheritance effects in other organisms, this study provides the first evidence of transgenerational inheritance of MeHg and VitA-induced toxicological effects in rodents. Although the exact mechanism is not yet fully understood, these findings suggest that MeHg and VitA may perpetuate their impacts across generations. The study highlights the need for remedial policies and interventions to mitigate the potential health problems faced by future generations exposed to MeHg or VitA. Further research is warranted to investigate the transgenerational effects beyond F2 and determine the matrilineal or patrilineal inheritance patterns.

Why birds are smart

Many cognitive neuroscientists believe that both a large brain and an isocortex are crucial for complex cognition. Yet corvids and parrots possess non-cortical brains of just 1-25 g, and these birds exhibit cognitive abilities comparable with those of great apes such as chimpanzees, which have brains of about 400 g. This opinion explores how this cognitive equivalence is possible. We propose four features that may be required for complex cognition: a large number of associative pallial neurons, a prefrontal cortex (PFC)-like area, a dense dopaminergic innervation of association areas, and dynamic neurophysiological fundaments for working memory. These four neural features have convergently evolved and may therefore represent 'hard to replace' mechanisms enabling complex cognition.

Sources of richness and ineffability for phenomenally conscious states

Conscious states-state that there is something it is like to be in-seem both rich or full of detail and ineffable or hard to fully describe or recall. The problem of ineffability, in particular, is a longstanding issue in philosophy that partly motivates the explanatory gap: the belief that consciousness cannot be reduced to underlying physical processes. Here, we provide an information theoretic dynamical systems perspective on the richness and ineffability of consciousness. In our framework, the richness of conscious experience corresponds to the amount of information in a conscious state and ineffability corresponds to the amount of information lost at different stages of processing. We describe how attractor dynamics in working memory would induce impoverished recollections of our original experiences, how the discrete symbolic nature of language is insufficient for describing the rich and high-dimensional structure of experiences, and how similarity in the cognitive function of two individuals relates to improved communicability of their experiences to each other. While our model may not settle all questions relating to the explanatory gap, it makes progress toward a fully physicalist explanation of the richness and ineffability of conscious experience-two important aspects that seem to be part of what makes qualitative character so puzzling.

Bioelectronic Medicine: a multidisciplinary roadmap from biophysics to precision therapies

Bioelectronic Medicine stands as an emerging field that rapidly evolves and offers distinctive clinical benefits, alongside unique challenges. It consists of the modulation of the nervous system by precise delivery of electrical current for the treatment of clinical conditions, such as post-stroke movement recovery or drug-resistant disorders. The unquestionable clinical impact of Bioelectronic Medicine is underscored by the successful translation to humans in the last decades, and the long list of preclinical studies. Given the emergency of accelerating the progress in new neuromodulation treatments (i.e., drug-resistant hypertension, autoimmune and degenerative diseases), collaboration between multiple fields is imperative. This work intends to foster multidisciplinary work and bring together different fields to provide the fundamental basis underlying Bioelectronic Medicine. In this review we will go from the biophysics of the cell membrane, which we consider the inner core of neuromodulation, to patient care. We will discuss the recently discovered mechanism of neurotransmission switching and how it will impact neuromodulation design, and we will provide an update on neuronal and glial basis in health and disease. The advances in biomedical technology have facilitated the collection of large amounts of data, thereby introducing new challenges in data analysis. We will discuss the current approaches and challenges in high throughput data analysis, encompassing big data, networks, artificial intelligence, and internet of things. Emphasis will be placed on understanding the electrochemical properties of neural interfaces, along with the integration of biocompatible and reliable materials and compliance with biomedical regulations for translational applications. Preclinical validation is foundational to the translational process, and we will discuss the critical aspects of such animal studies. Finally, we will focus on the patient point-of-care and challenges in neuromodulation as the ultimate goal of bioelectronic medicine. This review is a call to scientists from different fields to work together with a common endeavor: accelerate the decoding and modulation of the nervous system in a new era of therapeutic possibilities.

Development and evolution of the primate neocortex from a progenitor cell perspective

The generation of neurons in the developing neocortex is a major determinant of neocortex size. Crucially, the increase in cortical neuron numbers in the primate lineage, notably in the upper-layer neurons, contributes to increased cognitive abilities. Here, we review major evolutionary changes affecting the apical progenitors in the ventricular zone and focus on the key germinal zone constituting the foundation of neocortical neurogenesis in primates, the outer subventricular zone (OSVZ). We summarize characteristic features of the OSVZ and its key stem cell type, the basal (or outer) radial glia. Next, we concentrate on primate-specific and human-specific genes, expressed in OSVZ-progenitors, the ability of which to amplify these progenitors by targeting the regulation of the cell cycle ultimately underlies the evolutionary increase in upper-layer neurons. Finally, we address likely differences in neocortical development between present-day humans and Neanderthals that are based on human-specific amino acid substitutions in proteins operating in cortical progenitors.

Organoids and organoids-on-a-chip as the new testing strategies for environmental toxicology-applications & advantages

An increasing number of harmful environmental factors are causing serious impacts on human health, and there is an urgent need to accurately identify the toxic effects and mechanisms of these harmful environmental factors. However, traditional toxicity test methods (e.g., animal models and cell lines) often fail to provide accurate results. Fortunately, organoids differentiated from stem cells can more accurately, sensitively and specifically reflect the effects of harmful environmental factors on the human body. They are also suitable for specific studies and are frequently used in environmental toxicology nowadays. As a combination of organoids and organ-on-a-chip technology, organoids-on-a-chip has great potential in environmental toxicology. It is more controllable to the physicochemical microenvironment and is not easy to be contaminated. It has higher homogeneity in the size and shape of organoids. In addition, it can achieve vascularization and exchange the nutrients and metabolic wastes in time. Multi-organoids-chip can also simulate the interactions of different organs. These advantages can facilitate better function and maturity of organoids, which can also make up for the shortcomings of common organoids to a certain extent. This review firstly discussed the limitations of traditional toxicology testing platforms, leading to the introduction of new platforms: organoids and organoids-on-a-chip. Next, the applications of different organoids and organoids-on-a-chip in environmental toxicology were summarized and prospected. Since the advantages of the new platforms have not been sufficiently considered in previous literature, we particularly emphasized them. Finally, this review also summarized the opportunities and challenges faced by organoids and organoids-on-a-chip, with the expectation that readers will gain a deeper understanding of their value in the field of environmental toxicology.

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.

Backpack-mediated anti-inflammatory macrophage cell therapy for the treatment of traumatic brain injury

Traumatic brain injury (TBI) is a debilitating disease with no current therapies outside of acute clinical management. While acute, controlled inflammation is important for debris clearance and regeneration after injury, chronic, rampant inflammation plays a significant adverse role in the pathophysiology of secondary brain injury. Immune cell therapies hold unique therapeutic potential for inflammation modulation, due to their active sensing and migration abilities. Macrophages are particularly suited for this task, given the role of macrophages and microglia in the dysregulated inflammatory response after TBI. However, maintaining adoptively transferred macrophages in an anti-inflammatory, wound-healing phenotype against the proinflammatory TBI milieu is essential. To achieve this, we developed discoidal microparticles, termed backpacks, encapsulating anti-inflammatory interleukin-4, and dexamethasone for ex vivo macrophage attachment. Backpacks durably adhered to the surface of macrophages without internalization and maintained an anti-inflammatory phenotype of the carrier macrophage through 7 days in vitro. Backpack-macrophage therapy was scaled up and safely infused into piglets in a cortical impact TBI model. Backpack-macrophages migrated to the brain lesion site and reduced proinflammatory activation of microglia in the lesion penumbra of the rostral gyrus of the cortex and decreased serum concentrations of proinflammatory biomarkers. These immunomodulatory effects elicited a 56% decrease in lesion volume. The results reported here demonstrate, to the best of our knowledge, a potential use of a cell therapy intervention for a large animal model of TBI and highlight the potential of macrophage-based therapy. Further investigation is required to elucidate the neuroprotection mechanisms associated with anti-inflammatory macrophage therapy.

Genomic variation in neurons

Neurons born during the fetal period have extreme longevity and survive until the death of the individual because the human brain has highly limited tissue regeneration. The brain is comprised of an enormous variety of neurons each exhibiting different morphological and physiological characteristics and recent studies have further reported variations in their genome including chromosomal abnormalities, copy number variations, and single nucleotide mutations. During the early stages of brain development, the increasing number of neurons generated at high speeds has been proposed to lead to chromosomal instability. Additionally, mutations in the neuronal genome can occur in the mature brain. This observed genomic mosaicism in the brain can be produced by multiple endogenous and environmental factors and careful analyses of these observed variations in the neuronal genome remain central for our understanding of the genetic basis of neurological disorders.

Possible roles of deep cortical neurons and oligodendrocytes in the neural basis of human sociality

Sociality is an instinctive property of organisms that live in relation to others and is a complex characteristic of higher order brain functions. However, the evolution of the human brain to acquire higher order brain functions, such as sociality, and the neural basis for executing these functions and their control mechanisms are largely unknown. Several studies have attempted to evaluate how human sociality was acquired during the course of evolution and the mechanisms controlling sociality from a neurodevelopment viewpoint. This review discusses these findings in the context of human brain evolution and the pathophysiology of autism spectrum disorder (ASD). Comparative genomic studies of postmortem primate brains have demonstrated human-specific regulatory mechanisms underlying higher order brain functions, providing evidence for the contribution of oligodendrocytes to human brain function. Functional analyses of the causative genes of ASD in animal models have demonstrated that the neural basis of social behavior is associated with layer 6 (L6) of the neocortex and oligodendrocytes. These findings demonstrate that both neurons and oligodendrocytes contribute to the neural basis and molecular mechanisms underlying human brain evolution and social functioning. This review provides novel insights into sociability and the corresponding neural bases of brain disorders and evolution.

The Fractal Geometry of the Human Brain: An Evolutionary Perspective

The evolution of the brain in mammals is characterized by changes in size, architecture, and internal organization. Consequently, the geometry of the brain, and especially the size and shape of the cerebral cortex, has changed notably during evolution. Comparative studies of the cerebral cortex suggest that there are general architectural principles governing its growth and evolutionary development. In this chapter, some of the design principles and operational modes that underlie the fractal geometry and information processing capacity of the cerebral cortex in primates, including humans, will be explored. It is shown that the development of the cortex coordinates folding with connectivity in a way that produces smaller and faster brains.

Cell behaviors that pattern developing tissues: the case of the vertebrate nervous system

Morphogenesis from cells to tissue gives rise to the complex architectures that make our organs. How cells and their dynamic behavior are translated into functional spatial patterns is only starting to be understood. Recent advances in quantitative imaging revealed that, although highly heterogeneous, cellular behaviors make reproducible tissue patterns. Emerging evidence suggests that mechanisms of cellular coordination, intrinsic variability and plasticity are critical for robust pattern formation. While pattern development shows a high level of fidelity, tissue organization has undergone drastic changes throughout the course of evolution. In addition, alterations in cell behavior, if unregulated, can cause developmental malformations that disrupt function. Therefore, comparative studies of different species and of disease models offer a powerful approach for understanding how novel spatial configurations arise from variations in cell behavior and the fundamentals of successful pattern formation. In this chapter, I dive into the development of the vertebrate nervous system to explore efforts to dissect pattern formation beyond molecules, the emerging core principles and open questions.

LRRC37B is a human modifier of voltage-gated sodium channels and axon excitability in cortical neurons

The enhanced cognitive abilities characterizing the human species result from specialized features of neurons and circuits. Here, we report that the hominid-specific gene LRRC37B encodes a receptor expressed in human cortical pyramidal neurons (CPNs) and selectively localized to the axon initial segment (AIS), the subcellular compartment triggering action potentials. Ectopic expression of LRRC37B in mouse CPNs in vivo leads to reduced intrinsic excitability, a distinctive feature of some classes of human CPNs. Molecularly, LRRC37B binds to the secreted ligand FGF13A and to the voltage-gated sodium channel (Nav) β-subunit SCN1B. LRRC37B concentrates inhibitory effects of FGF13A on Nav channel function, thereby reducing excitability, specifically at the AIS level. Electrophysiological recordings in adult human cortical slices reveal lower neuronal excitability in human CPNs expressing LRRC37B. LRRC37B thus acts as a species-specific modifier of human neuron excitability, linking human genome and cell evolution, with important implications for human brain function and diseases.

Shaping the brain: The emergence of cortical structure and folding

The cerebral cortex-the brain's covering and largest region-has increased in size and complexity in humans and supports higher cognitive functions such as language and abstract thinking. There is a growing understanding of the human cerebral cortex, including the diversity and number of cell types that it contains, as well as of the developmental mechanisms that shape cortical structure and organization. In this review, we discuss recent progress in our understanding of molecular and cellular processes, as well as mechanical forces, that regulate the folding of the cerebral cortex. Advances in human genetics, coupled with experimental modeling in gyrencephalic species, have provided insights into the central role of cortical progenitors in the gyrification and evolutionary expansion of the cerebral cortex. These studies are essential for understanding the emergence of structural and functional organization during cortical development and the pathogenesis of neurodevelopmental disorders associated with cortical malformations.

A Boundary Element Method of Bidomain Modeling for Predicting Cellular Responses to Electromagnetic Fields

Objective

Commonly used cable equation-based approaches for determining the effects of electromagnetic fields on excitable cells make several simplifying assumptions that could limit their predictive power. Bidomain or "whole" finite element methods have been developed to fully couple cells and electric fields for more realistic neuron modeling. Here, we introduce a novel bidomain integral equation designed for determining the full electromagnetic coupling between stimulation devices and the intracellular, membrane, and extracellular regions of neurons.

Methods

Our proposed boundary element formulation offers a solution to an integral equation that connects the device, tissue inhomogeneity, and cell membrane-induced E-fields. We solve this integral equation using first-order nodal elements and an unconditionally stable Crank-Nicholson time-stepping scheme. To validate and demonstrate our approach, we simulated cylindrical Hodgkin-Huxley axons and spherical cells in multiple brain stimulation scenarios.

Main Results

Comparison studies show that a boundary element approach produces accurate results for both electric and magnetic stimulation. Unlike bidomain finite element methods, the bidomain boundary element method does not require volume meshes containing features at multiple scales. As a result, modeling cells, or tightly packed populations of cells, with microscale features embedded in a macroscale head model, is made computationally tractable, and the relative placement of devices and cells can be varied without the need to generate a new mesh.

Significance

Device-induced electromagnetic fields are commonly used to modulate brain activity for research and therapeutic applications. Bidomain solvers allow for the full incorporation of realistic cell geometries, device E-fields, and neuron populations. Thus, multi-cell studies of advanced neuronal mechanisms would greatly benefit from the development of fast-bidomain solvers to ensure scalability and the practical execution of neural network simulations with realistic neuron morphologies.

Permanent deconstruction of intracellular primary cilia in differentiating granule cell neurons

Primary cilia on granule cell neuron progenitors in the developing cerebellum detect sonic hedgehog to facilitate proliferation. Following differentiation, cerebellar granule cells become the most abundant neuronal cell type in the brain. While essential during early developmental stages, the fate of granule cell cilia is unknown. Here, we provide nanoscopic resolution of ciliary dynamics in situ by studying developmental changes in granule cell cilia using large-scale electron microscopy volumes and immunostaining of mouse cerebella. We found that many granule cell primary cilia were intracellular and concealed from the external environment. Cilia were disassembed in differentiating granule cell neurons in a process we call cilia deconstruction that was distinct from pre-mitotic cilia resorption in proliferating progenitors. In differentiating granule cells, ciliary loss involved unique disassembly intermediates, and, as maturation progressed, mother centriolar docking at the plasma membrane. Cilia did not reform from the docked centrioles, rather, in adult mice granule cell neurons remained unciliated. Many neurons in other brain regions require cilia to regulate function and connectivity. In contrast, our results show that granule cell progenitors had concealed cilia that underwent deconstruction potentially to prevent mitogenic hedgehog responsiveness. The ciliary deconstruction mechanism we describe could be paradigmatic of cilia removal during differentiation in other tissues.

Whole-brain Optical Imaging: A Powerful Tool for Precise Brain Mapping at the Mesoscopic Level

The mammalian brain is a highly complex network that consists of millions to billions of densely-interconnected neurons. Precise dissection of neural circuits at the mesoscopic level can provide important structural information for understanding the brain. Optical approaches can achieve submicron lateral resolution and achieve "optical sectioning" by a variety of means, which has the natural advantage of allowing the observation of neural circuits at the mesoscopic level. Automated whole-brain optical imaging methods based on tissue clearing or histological sectioning surpass the limitation of optical imaging depth in biological tissues and can provide delicate structural information in a large volume of tissues. Combined with various fluorescent labeling techniques, whole-brain optical imaging methods have shown great potential in the brain-wide quantitative profiling of cells, circuits, and blood vessels. In this review, we summarize the principles and implementations of various whole-brain optical imaging methods and provide some concepts regarding their future development.

Exposure to Δ9-tetrahydrocannabinol leads to a rise in caspase-3, morphological changes in microglial, and astrocyte reactivity in the cerebellum of rats

The present study aimed to elucidate the effect of 10 mg/kg Δ9-tetrahydrocannabinol (THC) on cerebellar neuronal and glial morphology, apoptosis and inflammatory gene expression using a series of histological assays including stereology, Sholl analysis, immunofluorescence and real-time qPCR in male Wistar rats. A decrease in the number of Purkinje neurons and the thickness of the granular layer in the cerebellum was reported in THC-treated rats. Increased expression of Iba-1 and arborization of microglial processes were evidence of microgliosis and morphological changes in microglia. In addition, astrogliosis and changes in astrocyte morphology were other findings associated with THC administration. THC also led to an increase in caspase-3 positive cells and a decrease in autophagy and inflammatory gene expression such as mTOR, BECN1 and LAMP2. However, there were no significant changes in the volume of molecular layers and white matter, the spatial arrangement of granular layers and white matter, or the spatial arrangement of granular layers and white matter in the cerebellum. Taken together, our data showed both neuroprotective and neurodegenerative properties of THC in the cerebellum, which require further study in the future.

Real-time selective detection of dopamine and serotonin at nanomolar concentration from complex in vitro systems

Electrochemical sensors provide means for real-time monitoring of neurotransmitter release events, which is a relatively easy process in simple electrolytes. However, this does not apply to in vitro environments. In cell culture media, competitively adsorbing molecules are present at concentrations up to 350 000-fold excess compared to the neurotransmitter-of-interest. Because detection of dopamine and serotonin requires direct adsorption of the analyte to electrode surface, a significant loss of sensitivity occurs when recording is performed in the in vitro environment. Despite these challenges, our single-walled carbon nanotube (SWCNT) sensor was capable of selectively measuring dopamine and serotonin from cell culture medium at nanomolar concentration in real-time. A primary midbrain culture was used to prove excellent biocompatibility of our SWCNT electrodes, which is a necessity for brain-on-a-chip models. Most importantly, our sensor was able to electrochemically record spontaneous transient activity from dopaminergic cell culture without altering the culture conditions, which has not been possible earlier. Drug discovery and development requires high-throughput screening of in vitro models, being hindered by the challenges in non-invasive characterization of complex neuronal models such as organoids. Our neurotransmitter sensors could be used for real-time monitoring of complex neuronal models, providing an alternative tool for their characterization non-invasively.

Fetal head-down posture may explain the rapid brain evolution in humans and other primates: An interpretative review

Evolutionary cerebrovascular consequences of upside-down postural verticality of the anthropoid fetus have been largely overlooked in the literature. This working hypothesis-based report provides a literature interpretation from an aspect that the rapid evolution of the human brain has been promoted by fetal head-down position due to maternal upright and semi-upright posture. Habitual vertical torso posture is a feature not only of humans, but also of monkeys and non-human apes that spend considerable time in a sitting position. Consequently, the head-down position of the fetus may have caused physiological craniovascular hypertension that stimulated expansion of the intracranial vessels and acted as an epigenetic physiological stress, which enhanced neurogenesis and eventually, along with other selective pressures, led to the progressive growth of the anthropoid brain and its organization. This article collaterally opens a new insight into the conundrum of high cephalopelvic proportions (i.e., the tight fit between the pelvic birth canal and fetal head) in phylogenetically distant lineages of monkeys, lesser apes, and humans. Low cephalopelvic proportions in non-human great apes could be accounted for by their energetically efficient horizontal nest-sleeping and consequently by their larger body mass compared to monkeys and lesser apes that sleep upright. One can further hypothesize that brain size varies in anthropoids according to the degree of exposure of the fetus to postural verticality. The supporting evidence for this postulation includes a finding that in fossil hominins cerebral blood flow rate increased faster than brain volume. This testable hypothesis opens a perspective for research on fetal postural cerebral hemodynamics.

A Comparative Perspective on the Cerebello-Cerebral System and Its Link to Cognition

The longstanding idea that the cerebral cortex is the main neural correlate of human cognition can be elaborated by comparative analyses along the vertebrate phylogenetic tree that support the view that the cerebello-cerebral system is suited to support non-motor functions more generally. In humans, diverse accounts have illustrated cerebellar involvement in cognitive functions. Although the neocortex, and its transmodal association cortices such as the prefrontal cortex, have become disproportionately large over primate evolution specifically, human neocortical volume does not appear to be exceptional relative to the variability within primates. Rather, several lines of evidence indicate that the exceptional volumetric increase of the lateral cerebellum in conjunction with its connectivity with the cerebral cortical system may be linked to non-motor functions and mental operation in primates. This idea is supported by diverging cerebello-cerebral adaptations that potentially coevolve with cognitive abilities across other vertebrates such as dolphins, parrots, and elephants. Modular adaptations upon the vertebrate cerebello-cerebral system may thus help better understand the neuroevolutionary trajectory of the primate brain and its relation to cognition in humans. Lateral cerebellar lobules crura I-II and their reciprocal connections to the cerebral cortical association areas appear to have substantially expanded in great apes, and humans. This, along with the notable increase in the ventral portions of the dentate nucleus and a shift to increased relative prefrontal-cerebellar connectivity, suggests that modular cerebellar adaptations support cognitive functions in humans. In sum, we show how comparative neuroscience provides new avenues to broaden our understanding of cerebellar and cerebello-cerebral functions in the context of cognition.

Developmental synapse pathology triggered by maternal exposure to the herbicide glufosinate ammonium

Environmental and genetic factors influence synapse formation. Numerous animal experiments have revealed that pesticides, including herbicides, can disturb normal intracellular signals, gene expression, and individual animal behaviors. However, the mechanism underlying the adverse outcomes of pesticide exposure remains elusive. Herein, we investigated the effect of maternal exposure to the herbicide glufosinate ammonium (GLA) on offspring neuronal synapse formation in vitro. Cultured cerebral cortical neurons prepared from mouse embryos with maternal GLA exposure demonstrated impaired synapse formation induced by synaptic organizer neuroligin 1 (NLGN1)-coated beads. Conversely, the direct administration of GLA to the neuronal cultures exhibited negligible effect on the NLGN1-induced synapse formation. The comparison of the transcriptomes of cultured neurons from embryos treated with maternal GLA or vehicle and a subsequent bioinformatics analysis of differentially expressed genes (DEGs) identified "nervous system development," including "synapse," as the top-ranking process for downregulated DEGs in the GLA group. In addition, we detected lower densities of parvalbumin (Pvalb)-positive neurons at the postnatal developmental stage in the medial prefrontal cortex (mPFC) of offspring born to GLA-exposed dams. These results suggest that maternal GLA exposure induces synapse pathology, with alterations in the expression of genes that regulate synaptic development via an indirect pathway distinct from the effect of direct GLA action on neurons.

Data-driven multiscale model of macaque auditory thalamocortical circuits reproduces in vivo dynamics

We developed a detailed model of macaque auditory thalamocortical circuits, including primary auditory cortex (A1), medial geniculate body (MGB), and thalamic reticular nucleus, utilizing the NEURON simulator and NetPyNE tool. The A1 model simulates a cortical column with over 12,000 neurons and 25 million synapses, incorporating data on cell-type-specific neuron densities, morphology, and connectivity across six cortical layers. It is reciprocally connected to the MGB thalamus, which includes interneurons and core and matrix-layer-specific projections to A1. The model simulates multiscale measures, including physiological firing rates, local field potentials (LFPs), current source densities (CSDs), and electroencephalography (EEG) signals. Laminar CSD patterns, during spontaneous activity and in response to broadband noise stimulus trains, mirror experimental findings. Physiological oscillations emerge spontaneously across frequency bands comparable to those recorded in vivo. We elucidate population-specific contributions to observed oscillation events and relate them to firing and presynaptic input patterns. The model offers a quantitative theoretical framework to integrate and interpret experimental data and predict its underlying cellular and circuit mechanisms.

Single-cell epigenomics and spatiotemporal transcriptomics reveal human cerebellar development

Human cerebellar development is orchestrated by molecular regulatory networks to achieve cytoarchitecture and coordinate motor and cognitive functions. Here, we combined single-cell transcriptomics, spatial transcriptomics and single cell chromatin accessibility states to systematically depict an integrative spatiotemporal landscape of human fetal cerebellar development. We revealed that combinations of transcription factors and cis-regulatory elements (CREs) play roles in governing progenitor differentiation and cell fate determination along trajectories in a hierarchical manner, providing a gene expression regulatory map of cell fate and spatial information for these cells. We also illustrated that granule cells located in different regions of the cerebellar cortex showed distinct molecular signatures regulated by different signals during development. Finally, we mapped single-nucleotide polymorphisms (SNPs) of disorders related to cerebellar dysfunction and discovered that several disorder-associated genes showed spatiotemporal and cell type-specific expression patterns only in humans, indicating the cellular basis and possible mechanisms of the pathogenesis of neuropsychiatric disorders.

Circular RNAs in renal cell carcinoma: from mechanistic to clinical perspective

CircRNAs, a special type of noncoding RNAs characterized by their stable structure and unique abilities to form backsplicing loops, have recently attracted the interest of scientists. These RNAs are abundant throughout the body and play important roles such as microRNA sponges, templates for transcription, and regulation of protein translation and RNA-binding proteins. Renal cancer development is highly correlated with abnormal circRNA expression in vivo. CircRNAs are currently considered promising targets for novel therapeutic approaches as well as possible biomarkers for prognosis and diagnosis of various malignancies. Despite our growing understanding of circRNA, numerous questions remain unanswered. Here, we address the characteristics of circRNAs and their function, focusing in particular on their impact on drug resistance, metabolic processes, metastasis, cell growth, and programmed cell death in renal cancer. In addition, the application of circRNAs as prognostic and diagnostic biomarkers will be discussed.

Frontal mechanisms underlying primate calls recognition by humans

Introduction

The ability to process verbal language seems unique to humans and relies not only on semantics but on other forms of communication such as affective vocalizations, that we share with other primate species-particularly great apes (Hominidae).

Methods

To better understand these processes at the behavioral and brain level, we asked human participants to categorize vocalizations of four primate species including human, great apes (chimpanzee and bonobo), and monkey (rhesus macaque) during MRI acquisition.

Results

Classification was above chance level for all species but bonobo vocalizations. Imaging analyses were computed using a participant-specific, trial-by-trial fitted probability categorization value in a model-based style of data analysis. Model-based analyses revealed the implication of the bilateral orbitofrontal cortex and inferior frontal gyrus pars triangularis (IFGtri) respectively correlating and anti-correlating with the fitted probability of accurate species classification. Further conjunction analyses revealed enhanced activity in a sub-area of the left IFGtri specifically for the accurate classification of chimpanzee calls compared to human voices.

Discussion

Our data-that are controlled for acoustic variability between species-therefore reveal distinct frontal mechanisms that shed light on how the human brain evolved to process vocal signals.

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.

A high-efficiency model indicating the role of inhibition in the resilience of neuronal networks to damage resulting from traumatic injury

Recent investigations of traumatic brain injuries have shown that these injuries can result in conformational changes at the level of individual neurons in the cerebral cortex. Focal axonal swelling is one consequence of such injuries and leads to a variable width along the cell axon. Simulations of the electrical properties of axons impacted in such a way show that this damage may have a nonlinear deleterious effect on spike-encoded signal transmission. The computational cost of these simulations complicates the investigation of the effects of such damage at a network level. We have developed an efficient algorithm that faithfully reproduces the spike train filtering properties seen in physical simulations. We use this algorithm to explore the impact of focal axonal swelling on small networks of integrate and fire neurons. We explore also the effects of architecture modifications to networks impacted in this manner. In all tested networks, our results indicate that the addition of presynaptic inhibitory neurons either increases or leaves unchanged the fidelity, in terms of bandwidth, of the network's processing properties with respect to this damage.

Chemical cognition: chemoconnectomics and convergent evolution of integrative systems in animals

Neurons underpin cognition in animals. However, the roots of animal cognition are elusive from both mechanistic and evolutionary standpoints. Two conceptual frameworks both highlight and promise to address these challenges. First, we discuss evidence that animal neural and other integrative systems evolved more than once (convergent evolution) within basal metazoan lineages, giving us unique experiments by Nature for future studies. The most remarkable examples are neural systems in ctenophores and neuroid-like systems in placozoans and sponges. Second, in addition to classical synaptic wiring, a chemical connectome mediated by hundreds of signal molecules operates in tandem with neurons and is the most information-rich source of emerging properties and adaptability. The major gap-dynamic, multifunctional chemical micro-environments in nervous systems-is not understood well. Thus, novel tools and information are needed to establish mechanistic links between orchestrated, yet cell-specific, volume transmission and behaviors. Uniting what we call chemoconnectomics and analyses of the cellular bases of behavior in basal metazoan lineages arguably would form the foundation for deciphering the origins and early evolution of elementary cognition and intelligence.