Computational models of neocortical neuronogenesis and programmed cell death in the developing mouse, monkey, and human

Length of the Neurogenic Period-A Key Determinant for the Generation of Upper-Layer Neurons During Neocortex Development and Evolution

The neocortex, a six-layer neuronal brain structure that arose during the evolution of, and is unique to, mammals, is the seat of higher order brain functions responsible for human cognitive abilities. Despite its recent evolutionary origin, it shows a striking variability in size and folding complexity even among closely related mammalian species. In most mammals, cortical neurogenesis occurs prenatally, and its length correlates with the length of gestation. The evolutionary expansion of the neocortex, notably in human, is associated with an increase in the number of neurons, particularly within its upper layers. Various mechanisms have been proposed and investigated to explain the evolutionary enlargement of the human neocortex, focussing in particular on changes pertaining to neural progenitor types and their division modes, driven in part by the emergence of human-specific genes with novel functions. These led to an amplification of the progenitor pool size, which affects the rate and timing of neuron production. In addition, in early theoretical studies, another mechanism of neocortex expansion was proposed—the lengthening of the neurogenic period. A critical role of neurogenic period length in determining neocortical neuron number was subsequently supported by mathematical modeling studies. Recently, we have provided experimental evidence in rodents directly supporting the mechanism of extending neurogenesis to specifically increase the number of upper-layer cortical neurons. Moreover, our study examined the relationship between cortical neurogenesis and gestation, linking the extension of the neurogenic period to the maternal environment. As the exact nature of factors promoting neurogenic period prolongation, as well as the generalization of this mechanism for evolutionary distinct lineages, remain elusive, the directions for future studies are outlined and discussed.

BCNNM: A Framework for in silico Neural Tissue Development Modeling

Cerebral (“brain”) organoids are high-fidelity in vitro cellular models of the developing brain, which makes them one of the go-to methods to study isolated processes of tissue organization and its electrophysiological properties, allowing to collect invaluable data for in silico modeling neurodevelopmental processes. Complex computer models of biological systems supplement in vivo and in vitro experimentation and allow researchers to look at things that no laboratory study has access to, due to either technological or ethical limitations. In this paper, we present the Biological Cellular Neural Network Modeling (BCNNM) framework designed for building dynamic spatial models of neural tissue organization and basic stimulus dynamics. The BCNNM uses a convenient predicate description of sequences of biochemical reactions and can be used to run complex models of multi-layer neural network formation from a single initial stem cell. It involves processes such as proliferation of precursor cells and their differentiation into mature cell types, cell migration, axon and dendritic tree formation, axon pathfinding and synaptogenesis. The experiment described in this article demonstrates a creation of an in silico cerebral organoid-like structure, constituted of up to 1 million cells, which differentiate and self-organize into an interconnected system with four layers, where the spatial arrangement of layers and cells are consistent with the values of analogous parameters obtained from research on living tissues. Our in silico organoid contains axons and millions of synapses within and between the layers, and it comprises neurons with high density of connections (more than 10). In sum, the BCNNM is an easy-to-use and powerful framework for simulations of neural tissue development that provides a convenient way to design a variety of tractable in silico experiments.

Prenatal Origins of ASD: The When, What, and How of ASD Development

Autism spectrum disorder (ASD) is a largely heritable, multistage prenatal disorder that impacts a child's ability to perceive and react to social information. Most ASD risk genes are expressed prenatally in many ASD-relevant brain regions and fall into two categories: broadly expressed regulatory genes that are expressed in the brain and other organs, and brain-specific genes. In trimesters one to three (Epoch-1), one set of broadly expressed (the majority) and brain-specific risk genes disrupts cell proliferation, neurogenesis, migration, and cell fate, while in trimester three and early postnatally (Epoch-2) another set (the majority being brain specific) disrupts neurite outgrowth, synaptogenesis, and the 'wiring' of the cortex. A proposed model is that upstream, highly interconnected regulatory ASD gene mutations disrupt transcriptional programs or signaling pathways resulting in dysregulation of downstream processes such as proliferation, neurogenesis, synaptogenesis, and neural activity. Dysregulation of signaling pathways is correlated with ASD social symptom severity. Since the majority of ASD risk genes are broadly expressed, many ASD individuals may benefit by being treated as having a broader medical disorder. An important future direction is the noninvasive study of ASD cell biology.

Mathematical Modeling of Cortical Neurogenesis Reveals that the Founder Population does not Necessarily Scale with Neurogenic Output

The mammalian cerebral neocortex has a unique structure, composed of layers of different neuron types, interconnected in a stereotyped fashion. While the overall developmental program seems to be conserved, there are divergent developmental factors generating cortical diversity amongst species. In terms of cortical neuronal numbers, some of the determining factors are the size of the founder population, the duration of cortical neurogenesis, the proportion of different progenitor types, and the fine-tuned balance between self-renewing and differentiative divisions. We develop a mathematical model of neurogenesis that, accounting for these factors, aims at explaining the high diversity in neuronal numbers found across species. By framing our hypotheses in rigorous mathematical terms, we are able to identify paths of neurogenesis that match experimentally observed patterns in mouse, macaque and human. Additionally, we use our model to identify key parameters that would particularly benefit from accurate experimental investigation. We find that the timing of a switch in favor of symmetric neurogenic divisions produces the highest variation in cortical neuronal numbers. Surprisingly, assuming similar cell cycle lengths in primate progenitors, the increase in cortical neuronal numbers does not reflect a larger size of founder population, a prediction that has identified a specific need for experimental quantifications.

A multiscale mathematical model of cell dynamics during neurogenesis in the mouse cerebral cortex

Background

Neurogenesis in the murine cerebral cortex involves the coordinated divisions of two main types of progenitor cells, whose numbers, division modes and cell cycle durations set up the final neuronal output. To understand the respective roles of these factors in the neurogenesis process, we combine experimental in vivo studies with mathematical modeling and numerical simulations of the dynamics of neural progenitor cells. A special focus is put on the population of intermediate progenitors (IPs), a transit amplifying progenitor type critically involved in the size of the final neuron pool.

Results

A multiscale formalism describing IP dynamics allows one to track the progression of cells along the subsequent phases of the cell cycle, as well as the temporal evolution of the different cell numbers. Our model takes into account the dividing apical progenitors (AP) engaged into neurogenesis, both neurogenic and proliferative IPs, and the newborn neurons. The transfer rates from one population to another are subject to the mode of division (proliferative, or neurogenic) and may be time-varying. The model outputs are successfully fitted to experimental cell numbers from mouse embryos at different stages of cortical development, taking into account IPs and neurons, in order to adjust the numerical parameters. We provide additional information on cell kinetics, such as the mitotic and S phase indexes, and neurogenic fraction.

Conclusions

Applying the model to a mouse mutant for Ftm/Rpgrip1l, a gene involved in human ciliopathies with severe brain abnormalities, reveals a shortening of the neurogenic period associated with an increased influx of newborn IPs from apical progenitors at mid-neurogenesis. Our model can be used to study other mouse mutants with cortical neurogenesis defects and can be adapted to study the importance of progenitor dynamics in cortical evolution and human diseases.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-3018-8) contains supplementary material, which is available to authorized users.

A stochastic model of adult neurogenesis coupling cell cycle progression and differentiation

Long-term tissue homeostasis requires a precise balance between stem cell self-renewal and the generation of differentiated progeny. Recently, it has been shown that in the adult murine brain, neural stem cells (NSCs) divide mostly symmetrically. This finding suggests that the required balance for tissue homeostasis is accomplished at the population level. However, it remains unclear how this balance is enabled. Furthermore, there is experimental evidence that proneural differentiation factors not only promote differentiation, but also cell cycle progression, suggesting a link between the two processes in NSCs. To study the effect of such a link on NSC dynamics, we developed a stochastic model in which stem cells have an intrinsic probability to progress through cell cycle and to differentiate. Our results show that increasing heterogeneity in differentiation probabilities leads to a decreased probability of long-term tissue homeostasis, and that this effect can be compensated when cell cycle progression and differentiation are positively coupled. Using single-cell RNA-Seq profiling of adult NSCs, we found a positive correlation in the expression levels of cell cycle and differentiation markers. Our findings suggest that a coupling between cell cycle progression and differentiation on the cellular level is part of the process that maintains tissue homeostasis in the adult brain.

The ASD Living Biology: from cell proliferation to clinical phenotype

Autism spectrum disorder (ASD) has captured the attention of scientists, clinicians and the lay public because of its uncertain origins and striking and unexplained clinical heterogeneity. Here we review genetic, genomic, cellular, postmortem, animal model, and cell model evidence that shows ASD begins in the womb. This evidence leads to a new theory that ASD is a multistage, progressive disorder of brain development, spanning nearly all of prenatal life. ASD can begin as early as the 1st and 2nd trimester with disruption of cell proliferation and differentiation. It continues with disruption of neural migration, laminar disorganization, altered neuron maturation and neurite outgrowth, disruption of synaptogenesis and reduced neural network functioning. Among the most commonly reported high-confidence ASD (hcASD) genes, 94% express during prenatal life and affect these fetal processes in neocortex, amygdala, hippocampus, striatum and cerebellum. A majority of hcASD genes are pleiotropic, and affect proliferation/differentiation and/or synapse development. Proliferation and subsequent fetal stages can also be disrupted by maternal immune activation in the 1st trimester. Commonly implicated pathways, PI3K/AKT and RAS/ERK, are also pleiotropic and affect multiple fetal processes from proliferation through synapse and neural functional development. In different ASD individuals, variation in how and when these pleiotropic pathways are dysregulated, will lead to different, even opposing effects, producing prenatal as well as later neural and clinical heterogeneity. Thus, the pathogenesis of ASD is not set at one point in time and does not reside in one process, but rather is a cascade of prenatal pathogenic processes in the vast majority of ASD toddlers. Despite this new knowledge and theory that ASD biology begins in the womb, current research methods have not provided individualized information: What are the fetal processes and early-age molecular and cellular differences that underlie ASD in each individual child? Without such individualized knowledge, rapid advances in biological-based diagnostic, prognostic, and precision medicine treatments cannot occur. Missing, therefore, is what we call ASD Living Biology. This is a conceptual and paradigm shift towards a focus on the abnormal prenatal processes underlying ASD within each living individual. The concept emphasizes the specific need for foundational knowledge of a living child's development from abnormal prenatal beginnings to early clinical stages. The ASD Living Biology paradigm seeks this knowledge by linking genetic and in vitro prenatal molecular, cellular and neural measurements with in vivo post-natal molecular, neural and clinical presentation and progression in each ASD child. We review the first such study, which confirms the multistage fetal nature of ASD and provides the first in vitro fetal-stage explanation for in vivo early brain overgrowth. Within-child ASD Living Biology is a novel research concept we coin here that advocates the integration of in vitro prenatal and in vivo early post-natal information to generate individualized and group-level explanations, clinically useful prognoses, and precision medicine approaches that are truly beneficial for the individual infant and toddler with ASD.

Theoretical Models of Neural Development

Constructing a functioning nervous system requires the precise orchestration of a vast array of mechanical, molecular, and neural-activity-dependent cues. Theoretical models can play a vital role in helping to frame quantitative issues, reveal mathematical commonalities between apparently diverse systems, identify what is and what is not possible in principle, and test the abilities of specific mechanisms to explain the data. This review focuses on the progress that has been made over the last decade in our theoretical understanding of neural development.

Psychiatry in a Dish: Stem Cells and Brain Organoids Modeling Autism Spectrum Disorders

Autism spectrum disorders are a group of pervasive neurodevelopmental conditions with heterogeneous etiology, characterized by deficits in social cognition, communication, and behavioral flexibility. Despite an increasing scientific effort to find the pathophysiological explanations for the disease, the neurobiological links remain unclear. A large amount of evidence suggests that pathological processes taking place in early embryonic neurodevelopment might be responsible for later manifestation of autistic symptoms. This dysfunctional development includes altered maturation/differentiation processes, disturbances in cell-cell communication, and an unbalanced ratio between certain neuronal populations. All those processes are highly dependent on the interconnectivity and three-dimensional organizations of the brain. Moreover, in order to gain a deeper understanding of the complex neurobiology of autism spectrum disorders, valid disease models are pivotal. Induced pluripotent stem cells could potentially help to elucidate the complex mechanisms of the disease and lead to the development of more effective individualized treatment. The induced pluripotent stem cells approach allows comparison between the development of various cellular phenotypes generated from cell lines of patients and healthy individuals. A newly advanced organoid technology makes it possible to create three-dimensional in vitro models of brain development and structural interconnectivity, based on induced pluripotent stem cells derived from the respective individuals. The biggest challenge for modeling psychiatric diseases in vitro is finding and establishing the link between cellular and molecular findings with the clinical symptoms, and this review aims to give an overview over the feasibility and applicability of this new tissue engineering tool in psychiatry.

The Thymus/Neocortex Hypothesis of the Brain: A Cell Basis for Recognition and Instruction of Self

The recognition of internal and external sources of stimuli, the self from non-self, seems to be an intrinsic property to the adequate functioning of the immune system and the nervous system, both complex network systems that have evolved to safeguard the self biological identity of the organism. The mammalian brain development relies on dynamic and adaptive processes that are now well described. However, the rules dictating this highly constrained developmental process remain elusive. Here we hypothesize that there is a cellular basis for brain selfhood, based on the analogy of the global mechanisms that drive the self/non-self recognition and instruction by the immune system. In utero education within the thymus by multi-step selection processes discard overly low and high affinity T-lymphocytes to self stimuli, thus avoiding expendable or autoreactive responses that might lead to harmful autoimmunity. We argue that the self principle is one of the chief determinants of neocortical brain neurogenesis. According to our hypothesis, early-life education on self at the subcortical plate of the neocortex by selection processes might participate in the striking specificity of neuronal repertoire and assure efficiency and self tolerance. Potential implications of this hypothesis in self-reactive neurological pathologies are discussed, particularly involving consciousness-associated pathophysiological conditions, i.e., epilepsy and schizophrenia, for which we coined the term autophrenity.

Applying evolutionary genetics to developmental toxicology and risk assessment

Evolutionary thinking continues to challenge our views on health and disease. Yet, there is a communication gap between evolutionary biologists and toxicologists in recognizing the connections among developmental pathways, high-throughput screening, and birth defects in humans. To increase our capability in identifying potential developmental toxicants in humans, we propose to apply evolutionary genetics to improve the experimental design and data interpretation with various in vitro and whole-organism models. We review five molecular systems of stress response and update 18 consensual cell-cell signaling pathways that are the hallmark for early development, organogenesis, and differentiation; and revisit the principles of teratology in light of recent advances in high-throughput screening, big data techniques, and systems toxicology. Multiscale systems modeling plays an integral role in the evolutionary approach to cross-species extrapolation. Phylogenetic analysis and comparative bioinformatics are both valuable tools in identifying and validating the molecular initiating events that account for adverse developmental outcomes in humans. The discordance of susceptibility between test species and humans (ontogeny) reflects their differences in evolutionary history (phylogeny). This synthesis not only can lead to novel applications in developmental toxicity and risk assessment, but also can pave the way for applying an evo-devo perspective to the study of developmental origins of health and disease.

Alterations in the mantle epithelium during transition from hatching gland to adhesive organ of Idiosepius pygmaeus (Mollusca, Cephalopoda)

Epithelial gland systems play an important role in marine molluscs in fabricating lubricants, repellents, fragrances, adhesives or enzymes. In cephalopods the typically single layered epithelium provides a highly dynamic variability and affords a rapid rebuilding of gland cells. While the digestive hatching gland (also named Hoyle organ) is obligatory for most cephalopods, only four genera (Nautilus, Sepia, Euprymna and Idiosepius) produce adhesive secretions by means of glandular cells in an adhesive area on the mantle or tentacles. In Idiosepius this adhesive organ is restricted to the posterior part of the fin region on the dorsal mantle side and well developed in the adult stage. Two gland cell types could be distinguished, which produce different contents of the adhesive. During the embryonic development the same body area is occupied by the temporary hatching gland. The question arises, in which way the hatching gland degrades and is replaced by the adhesive gland. Ultrastructural analyses as well as computer tomography scans were performed to monitor the successive post hatching transformation in the mantle epithelium from hatching gland degradation to the formation of the adhesive organ. According to our investigations the hatching gland cells degrade within about 1 day after hatching by a type of programmed cell death and leave behind a temporary cellular gap in this area. First glandular cells of the adhesive gland arise 7 days after hatching and proceed evenly over the posterior mantle epithelium. In contrast, the accompanying reduction of a part of the dorsal mantle musculature is already established before hatching. The results demonstrate a distinct independence between the two gland systems and illustrate the early development of the adhesive organ as well as the corresponding modifications within the mantle.

Modeling local and cross-species neuron number variations in the cerebral cortex as arising from a common mechanism

A massive increase in the number of neurons in the cerebral cortex, driving its size to increase by five orders of magnitude, is a key feature of mammalian evolution. Not only are there systematic variations in cerebral cortical architecture across species, but also across spatial axes within a given cortex. In this article we present a computational model that accounts for both types of variation as arising from the same developmental mechanism. The model employs empirically measured parameters from over a dozen species to demonstrate that changes to the kinetics of neurogenesis (the cell-cycle rate, the progenitor death rate, and the "quit rate," i.e., the ratio of terminal cell divisions) are sufficient to explain the great diversity in the number of cortical neurons across mammals. Moreover, spatiotemporal gradients in those same parameters in the embryonic cortex can account for cortex-wide, graded variations in the mature neural architecture. Consistent with emerging anatomical data in several species, the model predicts (i) a greater complement of neurons per cortical column in the later-developing, posterior regions of intermediate and large cortices, (ii) that the extent of variation across a cortex increases with cortex size, reaching fivefold or greater in primates, and (iii) that when the number of neurons per cortical column increases, whether across species or within a given cortex, it is the later-developing superficial layers of the cortex which accommodate those additional neurons. We posit that these graded features of the cortex have computational and functional significance, and so must be subject to evolutionary selection.

SIRT1 knockdown promotes neural differentiation and attenuates the heat shock response

Neurons have a limited capacity for heat shock protein (HSP) induction and are vulnerable to the pathogenic consequence of protein misfolding and aggregation as seen in age-related neurodegenerative diseases. Sirtuin 1 (SIRT1), an NAD(+) -dependent lysine deacetylase with important biological functions, has been shown to sustain the DNA-binding state of HSF1 for HSP induction. Here we show that differentiation and maturation of embryonic cortical neurons and N2a neuroprogenitor cells is associated with decreases in SIRT1 expression and heat shock-dependent induction of HSP70 protein. Tests of a pharmacological activator and an inhibitor of SIRT1 affirm the regulatory role of SIRT1 in HSP70 induction. Protein cross-linking studies show that nuclear SIRT1 and HSF1 form a co-migrating high molecular weight complex upon stress. The use of retroviral vectors to manipulate SIRT1 expression in N2a cells show that shRNA-mediated knock down of SIRT1 causes spontaneous neurite outgrowth coincident with reduced growth rate and decreased induction of hsp70-reporter gene, whereas SIRT1 over-expression blocks the induced neural differentiation of N2a cells. Our results suggest that decreased SIRT1 expression is conducive to neuronal differentiation and this decrease contributes to the attenuated induction of HSPs in neurons.

Distinct developmental growth patterns account for the disproportionate expansion of the rostral and caudal isocortex in evolution

In adulthood, the isocortex of several species is characterized by a gradient in neurons per unit of cortical surface area with fewer neurons per unit of cortical surface area in the rostral pole relative to the caudal pole. A gradient in neurogenesis timing predicts differences in neurons across the isocortex: neurons per unit of cortical surface area are fewer rostrally, where neurogenesis duration is short, and higher caudally where neurogenesis duration is longer. How species differences in neurogenesis duration impact cortical progenitor cells across its axis is not known. I estimated progenitor cells per unit of ventricular area across the rostro-caudal axis of the isocortex in cats (Felis catus) and in dogs (Canis familiaris) mostly before layers VI-II neurons are generated. I also estimated the ventricular length across the rostro-caudal axis at various stages of development in both species. These two species were chosen because neurogenesis duration in dogs is extended compared with cats. Caudally, cortical progenitors expand more tangentially and in numbers in dogs compared with cats. Rostrally, the cortical proliferative zone expands more tangentially in dogs compared with cats. However, the tangential expansion in the rostral cortical proliferative zone occurs without a concomitant increase in progenitor cell numbers. The tangential expansion of the ventricular surface in the rostral cortex is mediated by a reduction in cell density. These different developmental growth patterns account for the disproportionate expansion of the rostral (i.e., frontal cortex) and caudal cortex (e.g., primary visual cortex) when neurogenesis duration lengthens in evolution.

Patches of disorganization in the neocortex of children with autism

BACKGROUND

Autism involves early brain overgrowth and dysfunction, which is most strongly evident in the prefrontal cortex. As assessed on pathological analysis, an excess of neurons in the prefrontal cortex among children with autism signals a disturbance in prenatal development and may be concomitant with abnormal cell type and laminar development.

METHODS

To systematically examine neocortical architecture during the early years after the onset of autism, we used RNA in situ hybridization with a panel of layer- and cell-type-specific molecular markers to phenotype cortical microstructure. We assayed markers for neurons and glia, along with genes that have been implicated in the risk of autism, in prefrontal, temporal, and occipital neocortical tissue from postmortem samples obtained from children with autism and unaffected children between the ages of 2 and 15 years.

RESULTS

We observed focal patches of abnormal laminar cytoarchitecture and cortical disorganization of neurons, but not glia, in prefrontal and temporal cortical tissue from 10 of 11 children with autism and from 1 of 11 unaffected children. We observed heterogeneity between cases with respect to cell types that were most abnormal in the patches and the layers that were most affected by the pathological features. No cortical layer was uniformly spared, with the clearest signs of abnormal expression in layers 4 and 5. Three-dimensional reconstruction of layer markers confirmed the focal geometry and size of patches.

CONCLUSIONS

In this small, explorative study, we found focal disruption of cortical laminar architecture in the cortexes of a majority of young children with autism. Our data support a probable dysregulation of layer formation and layer-specific neuronal differentiation at prenatal developmental stages. (Funded by the Simons Foundation and others.).

Development and evolution of the human neocortex

The size and surface area of the mammalian brain are thought to be critical determinants of intellectual ability. Recent studies show that development of the gyrated human neocortex involves a lineage of neural stem and transit-amplifying cells that forms the outer subventricular zone (OSVZ), a proliferative region outside the ventricular epithelium. We discuss how proliferation of cells within the OSVZ expands the neocortex by increasing neuron number and modifying the trajectory of migrating neurons. Relating these features to other mammalian species and known molecular regulators of the mouse neocortex suggests how this developmental process could have emerged in evolution.

Synchronized changes to relative neuron populations in postnatal human neocortical development

Mammalian prenatal neocortical development is dominated by the synchronized formation of the laminae and migration of neurons. Postnatal development likewise contains "sensitive periods" during which functions such as ocular dominance emerge. Here we introduce a novel neuroinformatics approach to identify and study these periods of active development. Although many aspects of the approach can be used in other studies, some specific techniques were chosen because of a legacy dataset of human histological data (Conel in The postnatal development of the human cerebral cortex, vol 1-8. Harvard University Press, Cambridge, 1939-1967). Our method calculates normalized change vectors from the raw histological data, and then employs k-means cluster analysis of the change vectors to explore the population dynamics of neurons from 37 neocortical areas across eight postnatal developmental stages from birth to 72 months in 54 subjects. We show that the cortical "address" (Brodmann area/sub-area and layer) provides the necessary resolution to segregate neuron population changes into seven correlated "k-clusters" in k-means cluster analysis. The members in each k-cluster share a single change interval where the relative share of the cortex by the members undergoes its maximum change. The maximum change occurs in a different change interval for each k-cluster. Each k-cluster has at least one totally connected maximal "clique" which appears to correspond to cortical function.

ELECTRONIC SUPPLEMENTARY MATERIAL

The online version of this article (doi:10.1007/s11571-010-9103-3) contains supplementary material, which is available to authorized users.

Normal development of brain circuits

Spanning functions from the simplest reflex arc to complex cognitive processes, neural circuits have diverse functional roles. In the cerebral cortex, functional domains such as visual processing, attention, memory, and cognitive control rely on the development of distinct yet interconnected sets of anatomically distributed cortical and subcortical regions. The developmental organization of these circuits is a remarkably complex process that is influenced by genetic predispositions, environmental events, and neuroplastic responses to experiential demand that modulates connectivity and communication among neurons, within individual brain regions and circuits, and across neural pathways. Recent advances in neuroimaging and computational neurobiology, together with traditional investigational approaches such as histological studies and cellular and molecular biology, have been invaluable in improving our understanding of these developmental processes in humans in both health and illness. To contextualize the developmental origins of a wide array of neuropsychiatric illnesses, this review describes the development and maturation of neural circuits from the first synapse through critical periods of vulnerability and opportunity to the emergent capacity for cognitive and behavioral regulation, and finally the dynamic interplay across levels of circuit organization and developmental epochs.

Why "late equals large" does not work

The concept of conservative scaling of mammalian brain subdivision size with respect to brain size is one of the more contentious issues in neuromorphological studies. What is generally less critically discussed is the widely-cited suggestion that a highly conserved neurogenetic sequence during brain development is the reason for this conservative scaling and other processes of mammalian brain evolution. Here I re-visit the data with which the influential notion of conserved neurogenesis and mechanistic relationship between neurogenesis and mammalian brain subdivision scaling was developed. I suggest that neurogenetic sequences in the species available are not particularly conserved, and that brain subdivision sizes do not correspond well with neurogenetic sequence timing. As an alternative, I propose favouring less generalized and more heterochrony-focused approaches of relating timing differences between species to adult morphology.

Mathematical modeling supports substantial mouse neural progenitor cell death

Background

Existing quantitative models of mouse cerebral cortical development are not fully constrained by experimental data.

Results

Here, we use simple difference equations to model neural progenitor cell fate decisions, incorporating intermediate progenitor cells and initially low rates of neural progenitor cell death. Also, we conduct a sensitivity analysis to investigate possible uncertainty in the fraction of cells that divide, differentiate, and die at each cell cycle.

Conclusion

We demonstrate that uniformly low-level neural progenitor cell death, as concluded in previous models, is incompatible with normal mouse cortical development. Levels of neural progenitor cell death up to and exceeding 50% are compatible with normal cortical development and may operate to prevent forebrain overgrowth as observed following cell death attenuation, as occurs in caspase 3-null mutant mice.

A lifestage-specific approach to hazard and dose-response characterization for children's health risk assessment

In 2006, the U.S. EPA published a report entitled A Framework for Assessing Health Risks of Environmental Exposures to Children (hereafter referred to as the "Framework") describing a lifestage approach to risk assessment that includes the evaluation of existing data from a temporal perspective (i.e., the timing of both the exposure and the outcome). This article summarizes the lifestage-specific issues discussed in the Framework related to the qualitative and the quantitative hazard and dose-response characterization. Lifestage-specific hazard characterization includes an evaluation of relevant human and experimental animal studies, focusing on the identification of critical windows of development (i.e., exposure intervals of maximum susceptibility) for observed outcomes, evaluation of differential exposure at individual lifestages, the relevance and impact of lifestage-specific toxicokinetic and toxicodynamic data, mode of action information, variability and latency of effects from early lifestage exposure, and describing uncertainties. The interpretation of the hazard data to determine the strength of association between early life exposures and the timing and type of outcomes depends upon the overall weight of evidence. Lifestage-specific dose-response characterization relies on the identification of susceptible lifestages in order to quantify health risk, information on the point of departure, key default assumptions, and descriptions of uncertainty, sensitivity, and variability. Discussion of the strength and limitations of the hazard and dose-response data provides a basis for confidence in risk determinations. Applying a lifestage approach to hazard and dose-response characterization is likely to improve children's health risk assessment by identifying data gaps and providing a better understanding of sources of uncertainty.

Computational models of ethanol-induced neurodevelopmental toxicity across species: Implications for risk assessment

Computational, systems-based approaches can provide a quantitative construct for evaluating risk in the context of mechanistic data. Previously, we developed computational models for the rat, mouse, rhesus monkey, and human, describing the acquisition of adult neuron number in the neocortex during the key neurodevelopmental processes of neurogenesis and synaptogenesis. Here we apply mechanistic data from the rat describing ethanol-induced toxicity in the developing neocortex to evaluate the utility of these models for analyzing neurodevelopmental toxicity across species. Our model can explain long-term neocortical neuronal loss in the rodent model after in utero exposure to ethanol based on inhibition of proliferation during neurogenesis. Our human model predicts a significant neuronal deficit after daily peak BECs reaching 10-20 mg/dl, which is the approximate BEC reached after drinking one standard drink within one hour. In contrast, peak daily BECs of 100 mg/dl are necessary to predict similar deficits in the rat. Our model prediction of increased sensitivity of primate species to ethanol-induced inhibition of proliferation is based on application of in vivo experimental data from primates showing a prolonged rapid growth period in the primate versus rodent neuronal progenitor population. To place our predictions into a broader context, we evaluate the evidence for functional low-dose effects across rats, monkeys, and humans. Results from this critical evaluation suggest subtle effects are evident at doses causing peak BECs of approximately 20 mg/dl daily, corroborating our model predictions. Our example highlights the utility of a systems-based modeling approach in risk assessment.