There is a rare disorder that is apparently caused by certain lesions of the parietal neocortex of the left hemisphere, in which patients are unable to point on verbal command, to parts of their own bodies as well as to body parts of their examiner or of a picture of the human body. This disorder, known as autotopagnosia, is often accompanied by other cognitive deficits, such as a general difficulty in naming things, known as an anomia, or a difficulty understanding any words that refer to concrete as opposed to abstract concepts. If autotopagnosia is accompanied by these kinds of problem, then it is possible to argue that it is caused by a general difficulty with word names or an inability to understand the meaning of concrete words. There are cases, however, in which patients can name body parts on their own bodies when these parts are pointed to by the examiner, although they cannot point to their own body parts on command or point to their own body part that corresponds to a numbered part on a picture of a body. These autotopagnosias cannot be caused by verbal deficits, but some patients with this pattern of disorder also have difficulty pointing, on verbal command, to parts of inanimate objects. As such patients are also unable to relate a well-known story in logical sequence, it has been argued that autotopagnosia is caused by a general inability to analyse a whole into its component parts.

Research on short-term memory disorders, disorders of well-established memory, frontal memory disorders, and organic amnesia is still in a very open stage of development. Hypotheses about the functional deficits underlying these deficits as well as the lesions that cause them may well undergo a sea change in the face of new discoveries over the next few years. All the interpretations advanced in previous chapters are tentative suggestions that seem plausible in the light of available evidence. Currently, it is unwise to become strongly attached to hypotheses about the bases of organic memory disorders, but quite a bit has been learnt about their main features. The same cannot be said about disorders of the kinds of implicit memory that are probably preserved in organic amnesics. Nor can it be said about the memory disorders that form an often variable part of certain complex psychiatric and neurological disturbances, such as schizophrenia and Parkinson's disease. This chapter considers first the small amount of research that has been directed at exploring whether brain damage can cause selective impairments of priming, skill acquisition and retention, and conditioning (all kinds of implicit memory in which the evidence of remembering is indirect rather than direct). The evidence concerning the memory deficits associated with the complex psychiatric and neurological syndromes is then briefly reviewed in order to ascertain whether the memory deficits reported in these conditions can be interpreted as compounds of the elementary memory disorders, discussed earlier in the book.

Organic amnesia is a fairly common disorder, but most often the amnesia is intermixed with other cognitive symptoms because the brain damage that is responsible for it extends into regions unconnected with the amnesia, such as the association neocortex. Pure cases of amnesia show four major characteristics, two positive and two negative. First, intelligence, as assessed by standard tests, such as the WAIS, is preserved. Although the fine print of this claim is still disputed by some, patients with exceedingly poor memory have been described with IQs of 140. Subtle and selective cognitive deficits cannot be excluded yet, but there is no real evidence for them. Second, short-term memory, as assessed by digit span and the recency effect, is preserved. Third, there is poor acquisition and retention of new episodic and semantic information (anterograde amnesia). And fourth, there is poor memory for information that was acquired pre-traumatically (retrograde amnesia). As will be discussed in more detail later in this chapter, not all kinds of memory are disturbed in amnesics. It has been claimed that amnesics show preserved learning and memory for certain motor, perceptual, and cognitive skills, for conditioning, and for what was referred to in chapter 1 as priming (i.e., changed or more efficient processing of stimuli that results from having recently perceived them).

The evidence, reviewed in chapter 4, strongly suggests that PTO association neocortex stores many aspects of well-established semantic memory, and probably also the semantic components of episodic memory. In this chapter, the role in complex memory of the frontal association neocortex is considered. Although many issues remain unresolved and much research needs to be done, the role in memory of the frontal cortex is perhaps best approached by comparing it with the role in memory of PTO association cortex and of the structures damaged in organic amnesics. First, both PTO and frontal association cortex receive inputs of sensory information that has already undergone some processing, and the frontal region projects to areas that more directly control motor output. If they have broadly similar roles in memory, then one would expect the frontal cortex to be involved in storing certain kinds of well-established information. One possibility is that it may store action plans and ‘scripts’ that indicate what should be done in different kinds of situations, such as meeting friends or going to a restaurant. Strong evidence for a frontal cortex role in these kinds of storage does not yet exist. The second comparison is with the structures involved in organic amnesia. Warrington and Weiskrantz (1982) have argued that organic amnesia is caused by lesions that disconnect the frontal cortex from PTO association cortex. It is not the links across the neocortex that are severed, however, but those that connect frontal and PTO cortex via the limbic system and diencephalic structures. The effect of this disconnection is that amnesics cannot either store or retrieve all those kinds of information that require elaborative processing and planning during encoding.

Normal people forget some information in a few seconds but remember other things for years. It is widely believed that the information that is forgotten in seconds has been held in a limited-capacity short-term store and has not been transferred to a more stable, large-capacity long-term store. Of course, forgetting is a continuous process, and normal people forget things after seconds, minutes, hours, days, weeks, months, and years, but researchers do not propose that there are hundreds of stores to cover all these delays. Indeed, most workers believe that one kind of memory store is sufficient to explain all forgetting that occurs with delays of more than a few seconds. So why is belief in a separate kind of short-term store from which information is lost in seconds so widespread? As discussed in chapter 1, there are now psychologists, such as Wickelgren (1974), who argue that all the phenomena of rapid forgetting can be explained in terms of the properties of a single storage system. The evidence, based on studies of normal people, that immediate memory is affected differently from longer term memory by such variables as type of encoding and learning time can just as easily be interpreted in terms of a single storage hypothesis as it can in terms of the existence of separate short- and long-term stores. The short-term-storage hypothesis probably derives its appeal from two factors. First, rapid forgetting is something of which we are all very aware and distinguish from stable, long-term memory, which gives plausibility to the feeling that there is a discontinuity between rapid and slower kinds of forgetting.

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.