Vertebrate evolution

General considerations

Organic evolution on Earth began in the border zone between the Earth's crust and its atmosphere. The interaction of solar energy with the Earth's surface, largely covered by the oceanic basins, resulted in mainly salt solutions. These would become an essential component of life and, eventually, of nervous systems. If we accept the view that the oceans and their rocky surroundings became the fertile grounds for organic evolution, then rock formations and marine sediments become important witnesses for evolution. The remains of early life in rocks and sediments had been known for a long time but it was only in the second half of the nineteenth century that their significance was recognised by science as documentary evidence of the evolution of life on Earth. Up to that time it was the teaching of the Church that the Earth and its inhabitants were created by a single act of God about 4000 years ago. This view was also accepted by scientists, although later modified by the French anatomist Cuvier (1769–1832) who assumed several creative acts in order to explain the different fossil findings in different geological periods. By the fifteenth century the study of mineralogy had attracted Bauer, a German doctor, who studied closely excavations made for the mining industry and who laid the foundation for a close relation between evolution and geology. Berry (1968) has given an excellent account of the interrelation between the exploration of the Earth's crust and the understanding of evolution.

The macroscopic structures of the brain were described by the anatomists of Ancient Greece and Rome and were given names taken from the world of plants and animals, such as arbor vitae (tree of life), hippocampus (seahorse) and cornus amonis (Amon's horn). The finer structural details, however, became known only with the invention of the microscope and the histological techniques of fixation and staining. This exploratory work started in the eighteenth and nineteenth centuries and the names of Ledermüller (1758), Fontana (1782), Remark (1843) and Newport (1834) have to be mentioned. The main difficulties facing histologists were the gel-like semi-solid consistency of the brain substance and the poor power of resolution of early microscopes. Ledermuller was of the opinion that nerve fibres were hollow tubes in which a special energy circulated to convey willpower to muscles or from sense organs to the ‘sensorium’ of the brain. Fontana, however, proved that the nerve tubes were not empty but were filled with a colloidal substance.

Helmholtz (1821–1894), a famous physiologist of his time, who would nowadays be described as a biophysicist and who wrote his thesis on the composition of nerves (Helmholtz, 1842) under Johannes Müller (1800–1858), a physiologist and embryologist, found that the droplet-like structure of nerves postulated by van Leeuwenhoek in the seventeenth century was wrong and was caused when nerves were observed in hypotonic media.

Cellular construction

The thesis which Helmholtz wrote was of great significance for future studies, for he showed the primary importance of proper fixation for studies of preserved neural tissue.

The hypothalamus

Structure

The central switchboard is composed of the hypothalamus and its endocrine outlet, the pituitary gland. The hypothalamus is a relatively small funnelshaped pouch of the ventral part of the diencephalon and lies on the basal surface of the brain (Figs 10.1 and 10.2). A stalk connects the hypothalamus with the pituitary gland, which consists of two different parts or lobes, often called hypophysis in contrast to the epiphysis – a dorsal pouch of the diencephalon.

The stalk connects with the posterior lobe and is thus an outgrowth from the hypothalamus. The posterior lobe is for this reason referred to as the neurohypophysis and the anterior lobe, developing in ontogeny from the roof of the oral cavity, is glandular in structure and also called the adenohypophysis. The two lobes in primates are closely approximated with an intermediate zone between, but in some vertebrates, such as the elephant, they are separated. The glandular or anterior part has a number of differently granulated cells, which also stain differently. Histology discriminates five cell types: (1) undifferentiated stem cells; (2) α cells; (3) β cells; (4) γ cells; and (5) δ cells (Fig. 10.1).

Immunohistochemistry shows that alpha-cells secrete growth hormone and prolactin, beta-cells adreno-cortico-trophic hormone and thyrotrophic hormone, and the delta-cells secrete gonadotrophic hormones (Martin et al., 1977; Bhatnagar, 1983).

The stalk itself carries pathways and also fibres which transport neurosecretory granules (Figs 10.3 and 10.4). These granes are taken up by the capillaries of the posterior lobe. In the hypothalamic nuclei (Figs 10.4 and 10.5) we encounter a clear double neuronal function, to produce action potentials and neurosecretory granules.

In this chapter we report results from model-fitting analyses of data from the Colorado Adoption Project using the simple sibling and parent–off-spring models developed in the preceding chapter as well as extending the model to include age-to-age genetic correlations and to consider the multivariate case. As discussed in Chapter 7, model fitting has several advantages over less sophisticated approaches to the interpretation of behavioral genetic data: It yields appropriate parameter estimates given the assumptions of a model; it provides standard errors for these parameter estimates; and it provides goodness-of-fit tests to aid in the evaluation of alternative models.

Sibling model

A simple model can be used to represent the sibling adoption design because the essence of this design lies in the comparison between two correlations: the correlations for adoptive and nonadoptive siblings. The sibling model, illustrated in the path diagram of Figure 7.3, was applied to the adoptive- and nonadoptive-sibling correlations presented in Chapter 6. The model involves only three parameters: heritability and shared and nonshared environment. As specified in Equations (7.4) and (7.5), the model assumes that the observed nonadoptive-sibling correlation is a function of half the heritability of the trait and of shared environmental influence; the adoptive-sibling correlation arises only from shared environmental influence – in the absence of selective placement, heredity does not contribute to the resemblance of adoptive siblings.

In addition to the descriptive and predictive changes discussed in the preceding chapter, developmental change can be seen in terms of etiology – changes in genetic as well as environmental influences. Changes in environmental influences can be explored without behavioral genetics; for example, the effects of prematurity on individual differences in social and mental development tend to diminish during infancy (Kopp, 1983). Behavioral genetics, however, provides a particularly powerful and general approach to the study of developmental changes in etiologies of individual differences.

From a behavioral genetics perspective, three kinds of etiological change can be considered; these mirror the phenotypic changes described in Chapter 5. The most basic phenotypic change that can occur is a change in variance, although changes in the magnitude of phenotypic variance are difficult to interpret because measures are not comparable across ages. The analogous genetic concept – change in heritability – is easier to interpret because it refers to a proportion of phenotypic variance due to genetic differences among individuals rather than to the absolute magnitude of variance.

As mentioned in the preceding chapter, quantitative genetic theory recognizes that genetic and environmental influences change during development, and it proposes new concepts and methods for exploring developmental change as well as continuity. This is the core of a new subdiscipline, developmental behavioral genetics. When the field of behavioral genetics is surveyed from a developmental perspective, it is clear that the relative roles of genetic and environmental influences change during development (Plomin, 1986a). If this were not the case, there would be no need for the field of developmental behavioral genetics – the story in childhood would be just the same as that in adulthood.

The conclusion that the relative magnitudes of genetic and environmental influences change during development is founded primarily on cross-sectional comparisons across studies, for the obvious reason that most behavioral genetic studies are cross-sectional. Although the cross-sectional design can be illuminating, the lifeblood of developmental analysis of change and continuity is the longitudinal design (McCall, 1977; see also Chapter 5). The few longitudinal behavioral genetic studies, discussed below, add disproportionately to the weight of these conclusions because the same subjects are studied at different ages and, at each age, subjects are usually studied within a relatively narrow age band.

It is reasonable to expect that descriptive and explanatory relationships in development involve complex interactions rather than simple main effects. For example, an easy temperament might buffer a child against a difficult environment; conversely, stress may have a disproportionate effect on vulnerable children (Garmezy & Rutter, 1983). Organismic specificity in reaction to environments is one of the major hypotheses that emerges from a thorough review of early experience and human development:

Both from basic and applied data it has become increasingly clear that the relationship of early experience to development will be mediated by the nature of the organism on which the experience impinges. Unfortunately, virtually nothing is known about the specific organismic characteristics which mediate differential reactivity to the early environment. (Wachs & Gruen, 1982, p. 247)

In this chapter, we explore interactions using the CAP data in early childhood. The word “interaction” has many connotations, and it is important to be clear about its use. We limit our search for interactions to statistical interactions, the type of interaction typically derived in analysis of variance that involves the sum of squares remaining after main effects and within-cell variation is removed: “The phenomenon is well named. Interaction variations are those attributable not to either of two influences acting alone but to joint effects of the two acting together” (Guilford & Fruchter, 1973, p. 249).

Behavioral genetic theory, methods, and research provide a unique perspective on nature and nurture during infancy and early childhood, that is, on the genetic and environmental origins of individual differences in behavioral development. The words “nature” and “nurture” each have warm associations until they are brought together. One of our goals is to emphasize the conjunction “and” rather than the projective test provided by the dash in “nature–nurture” or the explicit hostility in the phrase “nature versus nurture.” We believe that the perspective of behavioral genetics is as useful for understanding environmental influences in development as it is for exploring the role of heredity, and we hope that this book will convince developmentalists of the importance of both genetic and experiential factors in the origins of behavioral differences during infancy and early childhood. At the simplest level, the components-of-variance approach – which we explore in terms of simple correlations as well as by means of model-fitting analyses – often indicates that genetic variance is significant and invariably shows that nongenetic factors are important.

The decomposition of phenotypic variance into genetic and environmental components of variance is the standard fare of behavioral genetic research. Somewhat newer is an emphasis on the decomposition of the environmental component of variance into two components, one shared by family members, which increases their phenotypic resemblance, and the other not shared; correlations for genetically unrelated children reared together in the same adoptive homes are especially powerful for detecting the “bottom line” influence of growing up in the same family.

Interest in as well as understanding and acceptance of behavioral genetics are often hindered by a single issue: confusion between individual differences and group differences. That is, behavioral genetic theory and research address individual differences (variance), whereas most psychological research involves group comparisons (means). In this chapter, we contrast these two approaches and then discuss the advantages and disadvantages of an individual-differences perspective. In part, the relative neglect of an individual-differences approach is due to its apparent atheoretical orientation. For this reason, the next chapter considers quantitative genetics as the basis for a general theory of the origins of individual differences.

The group-differences approach focuses on average differences, such as gender, age, cultural, or species differences, among groups of individuals within a population. In contrast, the etiology of differences among individuals in a population is the focus of individual-differences research. The point of this chapter is not that the individual-differences approach is better than the group-differences approach. The two approaches are perspectives, and perspectives are neither right nor wrong, only more or less useful for a particular purpose. However, we do argue that the two approaches differ in important ways that affect theories and research. In the following section, the basic distinction between the two approaches is examined more closely.