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.
Individual variation is the foundation for evolutionary change, but little is known about the nature of normal variation between brains. Phylogenetic variation across mammalian brains is characterized by high inter-correlations in brain region volumes, distinct allometric scaling for each brain region and the relative independence in olfactory and limbic structures volumes from the rest of the brain. Previous work examining brain variation in individuals of some domesticated species showed that these three features of phylogenetic variation were mirrored in individual variation. We extend this analysis to the human brain and 10 of its subdivisions (e.g., isocortex, hippocampus) by using magnetic resonance imaging scans of 90 human brains ranging between 16 to 25 years of age. Human brain variation resembles both the individual variation seen in other species, and variation observed across mammalian species. That is, the relative differences in the slopes of each brain region compared to medulla size within humans and between mammals are concordant, and limbic structures scale with relative independence from other brain regions. This non-random pattern of variation suggests that developmental programs channel the variation available for selection.
Allometry; Variation; Human; Brain; Evolution
A central question in brain evolution is how species-typical behaviors, and the neural function-structure mappings supporting them, can be acquired and inherited. Advocates of brain modularity, in its different incarnations across scientific subfields, argue that natural selection must target domain-dedicated, separately modifiable neural subsystems, resulting in genetically-specified functional modules. In such modular systems, specification of neuron number and functional connectivity are necessarily linked. Mounting evidence, however, from allometric, developmental, comparative, systems-physiological, neuroimaging and neurological studies suggests that brain elements are used and reused in multiple functional systems. This variable allocation can be seen in short-term neuromodulation, in neuroplasticity over the lifespan and in response to damage. We argue that the same processes are evident in brain evolution. Natural selection must preserve behavioral functions that may co-locate in variable amounts with other functions. In genetics, the uses and problems of pleiotropy, the re-use of genes in multiple networks have been much discussed, but this issue has been sidestepped in neural systems by the invocation of modules. Here we highlight the interaction between evolutionary and developmental mechanisms to produce distributed and overlapping functional architectures in the brain. These adaptive mechanisms must be robust to perturbations that might disrupt critical information processing and action selection, but must also recognize useful new sources of information arising from internal genetic or environmental variability, when those appear. These contrasting properties of “robustness” and “evolvability” have been discussed for the basic organization of body plan and fundamental cell physiology. Here we extend them to the evolution and development, “evo-devo,” of brain structure.
cortex; modularity; evo-devo; visual system; neural re-use
Biologists have long been interested in both the regularities and the deviations in the relationship between brain, development, ecology, and behavior between taxa. We first examine some basic information about the observed ranges of fundamental changes in developmental parameters (i.e. neurogenesis timing, cell cycle rates, and gene expression patterns) between taxa. Next, we review what is known about the relative importance of different kinds of developmental mechanisms in producing brain change, focusing on mechanisms of segmentation, local and general features of neurogenesis, and cell cycle kinetics. We suggest that a limited set of developmental alterations of the vertebrate nervous system typically occur and that each kind of developmental change may entail unique anatomical, functional, and behavioral consequences for the organism. Thus, neuroecologists who posit a direct mapping of brain size to behavior should consider that not any change in brain anatomy is possible.
Neurogenesis; Evolution; Development; Mammals; Birds
Brain size, body size, developmental length, life span, costs of raising offspring, behavioral complexity, and social structures are correlated in mammals due to intrinsic life-history requirements. Dissecting variation and direction of causation in this web of relationships often draw attention away from the factors that correlate with basic life parameters. We consider the “social brain hypothesis,” which postulates that overall brain and the isocortex are selectively enlarged to confer social abilities in primates, as an example of this enterprise and pitfalls. We consider patterns of brain scaling, modularity, flexibility of brain organization, the “leverage,” and direction of selection on proposed dimensions. We conclude that the evidence supporting selective changes in isocortex or brain size for the isolated ability to manage social relationships is poor. Strong covariation in size and developmental duration coupled with flexible brains allow organisms to adapt in variable social and ecological environments across the life span and in evolution.
evolution; primate; cortex; social; variation
The cellular and areal organization of the cerebral cortex impacts how it processes and integrates information. How that organization emerges and how best to characterize it has been debated for over a century. Here we demonstrate and describe in the isocortices of seven primate species a pronounced anterior-to-posterior gradient in the density of neurons and in the number of neurons under a unit area of the cortical surface. Our findings assert that the cellular architecture of the primate isocortex is neither arranged uniformly nor into discrete patches with an arbitrary spatial arrangement. Rather, it exhibits striking systematic variation. We conjecture that these gradients, which establish the basic landscape that richer areal and cellular structure is built upon, result from developmental patterns of cortical neurogenesis which are conserved across species. Moreover, we propose a functional consequence: that the gradient in neurons per unit of cortical area fosters the integration and dimensional reduction of information along its ascent through sensory areas and toward frontal cortex.
cortex; cortical areas; cytoarchitecture; evolutionary development; gradient; neurogenesis; primate evolution
Understanding relationships between the sequence and timing of brain developmental events across a given set of mammalian species can provide information about both neural development and evolution. Yet neuro-developmental event timing data available from the published literature are incomplete, particularly for humans. Experimental documentation of unknown event timings requires considerable effort that can be expensive, time consuming, and for humans, often impossible. Application of suitable statistical models for translating neurodevelopmental event timings across mammalian species is essential. The present study implements an established statistical model and related functions as an open-source R package (ttime, translating time). The model incorporated into ttime allows predictions of unknown neurodevelopmental timings and explorations of phylogenetic relationships. The open-source package will enable transparency and reproducibility while minimizing redundancy. Sustainability and widespread dissemination will be guaranteed by the active CRAN (Comprehensive R Archive Network) community. The package updates the web-service (Clancy et al. 2007b) www.translatingtime.net by permitting predictions based on curated event timing databases which may include species not yet incorporated in the current model. The R package can be integrated into complex workflows that use the event predictions in their analyses. The package ttime is publicly available and can be downloaded from http://cran.r-project.org/web/packages/ttime/index.html.
Open-source; R package; Cross-species modeling; Cross-species comparisons; Neurodevelopment
The developmental mechanisms by which the network organization of the adult cortex is established are incompletely understood. Here we report on empirical data on the development of connections in hamster isocortex and use these data to parameterize a network model of early cortical connectivity. Using anterograde tracers at a series of postnatal ages, we investigate the growth of connections in the early cortical sheet and systematically map initial axon extension from sites in anterior (motor), middle (somatosensory) and posterior (visual) cortex. As a general rule, developing axons extend from all sites to cover relatively large portions of the cortical field that include multiple cortical areas. From all sites, outgrowth is anisotropic, covering a greater distance along the medial/lateral axis than along the anterior/posterior axis. These observations are summarized as 2-dimensional probability distributions of axon terminal sites over the cortical sheet. Our network model consists of nodes, representing parcels of cortex, embedded in 2-dimensional space. Network nodes are connected via directed edges, representing axons, drawn according to the empirically derived anisotropic probability distribution. The networks generated are described by a number of graph theoretic measurements including graph efficiency, node betweenness centrality and average shortest path length. To determine if connectional anisotropy helps reduce the total volume occupied by axons, we define and measure a simple metric for the extra volume required by axons crossing. We investigate the impact of different levels of anisotropy on network structure and volume. The empirically observed level of anisotropy suggests a good trade-off between volume reduction and maintenance of both network efficiency and robustness. Future work will test the model's predictions for connectivity in larger cortices to gain insight into how the regulation of axonal outgrowth may have evolved to achieve efficient and economical connectivity in larger brains.
To better understand the neurotoxic effects of diverse hazards on the developing human nervous system, researchers and clinicians rely on data collected from a number of model species that develop and mature at varying rates. We review the methods commonly used to extrapolate the timing of brain development from experimental mammalian species to humans, including morphological comparisons, “rules of thumb” and “event-based” analyses. Most are unavoidably limited in range or detail, many are necessarily restricted to rat/human comparisons, and few can identify brain regions that develop at different rates. We suggest this issue is best addressed using “neuroinformatics”, an analysis that combines neuroscience, evolutionary science, statistical modeling and computer science. A current use of this approach relates numeric values assigned to ten mammalian species and hundreds of empirically derived developing neural events, including specific evolutionary advances in primates. The result is an accessible, online resource (http://www.translatingtime.net/) that can be used to equate dates in the neurodevelopmental literature across laboratory species to humans, predict neurodevelopmental events for which data are lacking in humans, and help to develop clinically relevant experimental models.
brain maturation; comparative development; cross-species development; humans; neurodevelopment
Neural systems are necessarily the adaptive products of natural selection, but a neural system, dedicated to any particular function in a complex brain, may be composed of components that covary with functionally unrelated systems, owing to constraints beyond immediate functional requirements. Some studies support a modular or mosaic organization of the brain, whereas others emphasize coordination and covariation. To contrast these views, we have analysed the retina, striate cortex (V1) and extrastriate cortex (V2, V3, MT, etc.) in 30 mammals, examining the area of the neocortex and individual neocortical areas and the relative numbers of rods and cones. Controlling for brain size and species relatedness, the sizes of visual cortical areas (striate, extrastriate) within the brains of nocturnal and diurnal mammals are not statistically different from one another. The relative sizes of all cortical areas, visual, somatosensory and auditory, are best predicted by the total size of the neocortex. In the sensory periphery, the retina is clearly specialized for niche. New data on rod and cone numbers in various New World primates confirm that rod and cone complements of the retina vary substantially between nocturnal and diurnal species. Although peripheral specializations or receptor surfaces may be highly susceptible to niche-specific selection pressures, the areal divisions of the cerebral cortex are considerably more conservative.
evolution; mammalian visual system; neocortex; retina; nocturnal; diurnal