A general model of neural development is derived to fit 18 mammalian species, including humans, macaques, several rodent species, and six metatherian (marsupial) mammals. The goal of this work is to ...describe heterochronic changes in brain evolution within its basic developmental allometry, and provide an empirical basis to recognize equivalent maturational states across animals. The empirical data generating the model comprises 271 developmental events, including measures of initial neurogenesis, axon extension, establishment, and refinement of connectivity, as well as later events such as myelin formation, growth of brain volume, and early behavioral milestones, to the third year of human postnatal life. The progress of neural events across species is sufficiently predictable that a single model can be used to predict the timing of all events in all species, with a correlation of modeled values to empirical data of 0.9929. Each species' rate of progress through the event scale, described by a regression equation predicting duration of development in days, is highly correlated with adult brain size. Neural heterochrony can be seen in selective delay of retinogenesis in the cat, associated with greater numbers of rods in its retina, and delay of corticogenesis in all species but rodents and the rabbit, associated with relatively larger cortices in species with delay. Unexpectedly, precocial mammals (those unusually mature at birth) delay the onset of first neurogenesis but then progress rapidly through remaining developmental events.
How the unique capacities of human cognition arose in evolution is a question of enduring interest. It is still unclear which developmental programmes are responsible for the emergence of the human ...brain. The inability to determine corresponding ages between humans and apes has hampered progress in detecting developmental programmes leading to the emergence of the human brain. I harness temporal variation in anatomical, behavioural and transcriptional variation to determine corresponding ages from fetal to postnatal development and ageing, between humans and chimpanzees. This multi-dimensional approach results in 137 corresponding time points across the lifespan, from embryonic day 44 to approximately 55 years of age, in humans and their equivalent ages in chimpanzees. I used these data to test whether developmental programmes, such as the timeline of prefrontal cortex (PFC) maturation, previously claimed to differ between humans and chimpanzees, do so once variation in developmental schedules is controlled for. I compared the maturation of frontal cortex projections from structural magnetic resonance (MR) scans and from temporal variation in the expression of genes used to track long-range projecting neurons (i.e. supragranular-enriched genes) in chimpanzees and humans. Contrary to what has been suggested, the timetable of PFC maturation is not unusually extended in humans. This dataset, which is the largest with which to determine corresponding ages across humans and chimpanzees, provides a rigorous approach to control for variation in developmental schedules and to identify developmental programmes responsible for unique features of the human brain.
Plasticity, and in particular, neurogenesis, is a promising target to treat and prevent a wide variety of diseases (e.g., epilepsy, stroke, dementia). There are different types of plasticity, which ...vary with age, brain region, and species. These observations stress the importance of defining plasticity along temporal and spatial dimensions. We review recent studies focused on brain plasticity across the lifespan and in different species. One main theme to emerge from this work is that plasticity declines with age but that we have yet to map these different forms of plasticity across species. As part of this effort, we discuss our recent progress aimed to identify corresponding ages across species, and how this information can be used to map temporal variation in plasticity from model systems to humans.
The brain is composed of a complex web of networks but we have yet to map the structural connections of the human brain in detail. Diffusion MR imaging is a high‐throughput method that relies on the ...principle of diffusion to reconstruct tracts (ie, pathways) across the brain. Although diffusion MR tractography is an exciting method to explore the structural connectivity of the brain in development and across species, the tractography has at times led to questionable interpretations. There are at present few if any alternative methods to trace structural pathways in the human brain. Given these limitations and the potential of diffusion MR imaging to map the human connectome, it is imperative that we develop new approaches to validate neuroimaging techniques. I discuss our recent studies integrating neuroimaging with transcriptional and anatomical variation across humans and other species over the course of development and in adulthood. Developing a novel framework to harness the potential of diffusion MR tractography provides new and exciting opportunities to study the evolution of developmental mechanisms generating variation in connections and bridge the gap between model systems to humans.
Key Findings
Diffusion MR tractography identifies pathways across the entire brain and is one of the sole tools available to study structural connections in the human brain. However, the limitations of diffusion MR tractography have precluded its ability to trace pathways in sufficient detail to map connections in the human brain. These limitations necessitate developing new tools to study connections. I discuss how integrating diffusion MR imaging with transcriptional variation provides new venues to map connections in the human brain and enhances our understanding of the evolution of development mechanisms generating connections in the human brain.
Uniformity, local variability, and systematic variation in neuron numbers per unit of cortical surface area across species and cortical areas have been claimed to characterize the isocortex. ...Resolving these claims has been difficult, because species, techniques, and cortical areas vary across studies. We present a stereological assessment of neuron numbers in layers II-IV and V-VI per unit of cortical surface area across the isocortex in rodents (hamster, Mesocricetus auratus; agouti, Dasyprocta azarae; paca, Cuniculus paca) and primates (owl monkey, Aotus trivigratus; tamarin, Saguinus midas; capuchin, Cebus apella); these chosen to vary systematically in cortical size. The contributions of species, cortical areas, and techniques (stereology, "isotropic fractionator") to neuron estimates were assessed. Neurons per unit of cortical surface area increase across the rostro-caudal (RC) axis in primates (varying by a factor of 1.64-2.13 across the rostral and caudal poles) but less in rodents (varying by a factor of 1.15-1.54). Layer II-IV neurons account for most of this variation. When integrated into the context of species variation, and this RC gradient in neuron numbers, conflicts between studies can be accounted for. The RC variation in isocortical neurons in adulthood mirrors the gradients in neurogenesis duration in development.
Comparison of neurodevelopmental sequences between species whose initial period of brain organization may vary from 100 days to 1,000 days, and whose progress is intrinsically non-linear presents ...large challenges in normalization. Comparing adult timelines when lifespans stretch from 1 year to 75 years, when underlying cellular mechanisms under scrutiny do not scale similarly, presents challenges to simple detection and comparison. The question of adult hippocampal neurogenesis has generated numerous controversies regarding its simple presence or absence in humans versus rodents, whether it is best described as the tail of a distribution centered on early neural development, or is several distinct processes. In addition, adult neurogenesis may have substantially changed in evolutionary time in different taxonomic groups. Here, we extend and adapt a model of the cross-species transformation of early neurodevelopmental events which presently reaches up to the equivalent of the third human postnatal year for 18 mammalian species (www.translatingtime.net) to address questions relevant to hippocampal neurogenesis, which permit extending the database to adolescence or perhaps to the whole lifespan. We acquired quantitative data delimiting the envelope of hippocampal neurogenesis from cell cycle markers (i.e., Ki67 and DCX) and RNA sequencing data for two primates (macaque and humans) and two rodents (rat and mouse). To improve species coverage in primates, we gathered the same data from marmosets (
), but additionally gathered data on a number of developmental milestones to find equivalent developmental time points between marmosets and other species. When all species are so modeled, and represented in a common time frame, the envelopes of hippocampal neurogenesis are essentially superimposable. Early developmental events involving the olfactory and limbic system start and conclude possibly slightly early in primates than rodents, and we find a comparable early conclusion of primate hippocampal neurogenesis (as assessed by the relative number of Ki67 cells) suggesting a plateau to low levels at approximately 2 years of age in humans. Marmosets show equivalent patterns within neurodevelopment, but unlike macaque and humans may have wholesale delay in the initiation of neurodevelopment processes previously observed in some precocial mammals such as the guinea pig and multiple large ungulates.
Human infants are helpless for a protracted period after birth. This has been attributed to maternal constraints causing an early birth while the brain is still immature.However, anatomical studies ...have shown that relative to other species, human newborn brains are not particularly immature.Consistent with this, neuroimaging studies have shown that the structure and function of many cognitive systems is surprisingly mature in humans at birth.Why else might humans have a protracted helpless period? In machine learning, learning good representations of the environment through self-supervised learning in large deep neural networks yields enormously powerful ‘foundation models’, which allow better generalisation to new problems and have a higher final performance.We propose that in the helpless period, human infants are learning a foundation model that underpins their later cognition.
Humans have a protracted postnatal helplessness period, typically attributed to human-specific maternal constraints causing an early birth when the brain is highly immature. By aligning neurodevelopmental events across species, however, it has been found that humans are not born with especially immature brains compared with animal species with a shorter helpless period. Consistent with this, the rapidly growing field of infant neuroimaging has found that brain connectivity and functional activation at birth share many similarities with the mature brain. Inspired by machine learning, where deep neural networks also benefit from a ‘helpless period’ of pre-training, we propose that human infants are learning a foundation model: a set of fundamental representations that underpin later cognition with high performance and rapid generalisation.
Humans have a protracted postnatal helplessness period, typically attributed to human-specific maternal constraints causing an early birth when the brain is highly immature. By aligning neurodevelopmental events across species, however, it has been found that humans are not born with especially immature brains compared with animal species with a shorter helpless period. Consistent with this, the rapidly growing field of infant neuroimaging has found that brain connectivity and functional activation at birth share many similarities with the mature brain. Inspired by machine learning, where deep neural networks also benefit from a ‘helpless period’ of pre-training, we propose that human infants are learning a foundation model: a set of fundamental representations that underpin later cognition with high performance and rapid generalisation.
•Ex vivo fetal brain MRI has great potential to resolve detailed tissue structures.•Careful histopathology assessments and large-scale scans/analyses are important.•Comparative ex vivo MRI finds ...species-specific differences in early development.•Ex vivo MRI results will be a great reference to in vivo fetal brain MRI.
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.
Significance Despite great diversity across mammals in the number of cortical neurons and the cognitive functions they support, the fundamental process which populates the cerebral cortex with neurons changes only subtly from the smallest rodents to the largest primates. Understanding how the dynamics of neurogenesis can vary will help unravel how the genome molds normal and disrupted cortical development. We gathered data on the growing and mature cortex to build a computational model of neurogenesis. The model recapitulates how dynamics, known to vary across species and across the cortex, sculpt the basic landscape of the embryonic cortex. Features of the cortex long thought to be the result of special selection are revealed as the necessary product of a conserved mechanism.
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