Analysis of data collected on 131 species of primates, bats, and insectivores showed that the sizes of brain components, from medulla to forebrain, are highly predictable from absolute brain size by a nonlinear function. The order of neurogenesis was found to be highly conserved across a wide range of mammals and to correlate with the relative enlargement of structures as brain size increases, with disproportionately large growth occurring in late-generated structures. Because the order of neurogenesis is conserved, the most likely brain alteration resulting from selection for any behavioral ability may be a coordinated enlargement of the entire nonolfactory brain.
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.
A number of common practices and beliefs concerning multiple regression are criticized, and several paradoxical properties of the method are emphasized. Major topics discussed are the basic formulas; suppressor variables; measures of the "importance" of a predictor variable; inferring relative regression weights from relative validities; estimates of the true validity of population regression equations and of regression equations developed in samples; and statistical criteria for selecting predictor variables. The major points are presented in outline form in a final summary.In recent years, electronic computers have made the multiple regression method readily available to psychologists and other scientists, while simultaneously making it unnecessary for them to study in full the cumbersome computational details of the method. Therefore, there is a need for a discussion of multiple regression which emphasizes some of the less obvious uses, limitations, and properties of the method. This article attempts to fill this need. It makes no attempt to cover thoroughly computational techniques or significance tests, both of which are discussed in such standard sources as McNemar (1962), Hays (1963), DuBois (1957), and Williams (1959. The discussion of significance tests by Williams is especially complete, as is the presentation of computing directions by DuBois. The latter source also contains many basic formulas of considerable interest. Anderson (1958) gives a very complete mathematical presentation of the exact sampling distributions of many of the statistics relevant to multiple regression. Elashoff and Afifi (1966) reviewed procedures applicable when some observations are missing. Beaton (1964) described a set of elegantly simple computer subroutines which a FORTRAN programmer can use to write quickly almost any standard or special-purpose regression program he may require.
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.
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How does evolution grow bigger brains? It has been widely assumed that growth of individual structures and functional systems in response to niche-specific cognitive challenges is the most plausible mechanism for brain expansion in mammals. Comparison of multiple regressions on allometric data for 131 mammalian species, however, suggests that for 9 of 11 brain structures taxonomic and body size factors are less important than covariance of these major structures with each other. Which structure grows biggest is largely predicted by a conserved order of neurogenesis that can be derived from the basic axial structure of the developing brain. This conserved order of neurogenesis predicts the relative scaling not only of gross brain regions like the isocortex or mesencephalon, but also the level of detail of individual thalamic nuclei. Special selection of particular areas for specific functions does occur, but it is a minor factor compared to the large-scale covariance of the whole brain. The idea that enlarged isocortex could be a “spandrel,” a by-product of structural constraints later adapted for various behaviors, contrasts with approaches to selection of particular brain regions for cognitively advanced uses, as is commonly assumed in the case of hominid brain evolution.
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 rates, including fast developing experimental rodent species and slower developing humans. In this article, we introduce a database-driven website, which was created to address this problem using statistical-based algorithms to integrate hundreds of empirically derived developing neural events in 10 mammalian species (http://translatingtime.net/). The site, based on a statistical model that has evolved over the past decade, currently incorporates 102 different neurodevelopmental events obtained from 10 species: hamsters, mice, rats, rabbits, spiny mice, guinea pigs, ferrets, cats, rhesus monkeys, and humans. Data are arranged in a Structured Query Language database, which allows comparative brain development measured in postconception days to be converted and accessed in real time, using Hypertext Preprocessor language. Algorithms applied to the database also allow predictions for dates of specific neurodevelopmental events where empirical data are not available, including for the human embryo and fetus. By designing a web-based portal, we seek to make these comparative data readily available to all those who need to efficiently estimate the timing of neurodevelopmental events in the human fetus, laboratory species, or across several different species. In an effort to further refine and expand the applicability of this database, we include a mechanism to submit additional data.
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