Barbara Clancy

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.

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.

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 neurodevelopmental 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.

Cortical GABAergic (γ-aminobutyric acidergic) neurons include a recently identified subset whose projections extend over relatively long distances in adult rodents and primates. A number of these inhibitory projection neurons are located in and above the conventionally identified white matter, suggesting their persistence from, or a correspondence with, the developmental subplate. GABAergic and subplate neurons share some unique properties unlike those of the more prevalent pyramidal neurons. To better understand the GABAergic and subplate populations, we constructed a database of neural developmental events common to the three species most frequently used in experimental studies: rat, mouse, and macaque, using data from the online database www.translatingtime.net as well as GABAergic and subplate developmental data from the empirical literature. We used a general linear model to test for similarities and differences, a valid approach because the sequence of most neurodevelopmental events is remarkably conserved across mammalian species. Similarities between the two rodent populations are striking, permitting us to identify developmental dates for GABAergic and subplate neural events in rats that were previously identified only in mice, as well as the timing in mouse development for events previously identified in rats. Primate comparative data are also compelling, although slight variability in statistical error measurement indicates differences in primate GABAergic and subplate events when compared to rodents. Although human extrapolations are challenging because fewer empirical data points are available, and because human data display more variability, we also produce estimates of dates for GABAergic and subplate neural events that have not yet been, or cannot be, determined empirically in humans.

Statistical properties such as distribution and correlation signatures were investigated using a temporal database of common neurodevelopmental events in the three species most frequently used in experimental studies, rat, mouse, and macaque. There was a fine nexus between phylogenetic proximity and empirically derived dates of the occurrences of 40 common events including the neurogenesis of cortical layers and outgrowth milestones of developing axonal projections. Exponential and power-law approximations to the distribution of the events reveal strikingly similar decay patterns in rats and mice when compared to macaques. Subsequent hierarchical clustering of the common event timings also captures phylogenetic proximity, an association further supported by multivariate linear regression data. These preliminary results suggest that statistical analyses of the timing of developmental milestones may offer a novel measure of phylogenetic classifications. This may have added pragmatic value in the specific support it offers for the reliability of rat/mouse comparative modeling, as well as in the broader implications for the potential of meta-analyses using databases assembled from the extensive empirical literature.

Biomedical researchers and medical professionals are regularly required to compare a vast quantity of neurodevelopmental literature obtained from an assortment of mammals whose brains grow at diverse...

As Striedter explores the concerted principles that drive brain evolution and the departures that create uniqueness, he scrutinizes and ultimately supports the (unnecessarily controversial) Finlay/Darlington model in which mathematical relationships across mammalian neural development are identified (Finlay & Darlington 1995). Pragmatic impact includes the ability to make novel comparisons across developing species, including humans.