Evidence for genetic influence on environmental measures will emerge in quantitative genetic analyses if genetically influenced characteristics of individuals are assessed by these environmental measures. Recent twin and adoption studies indicate substantial genetic influence when measures of the environment are treated as phenotypes in genetic analyses. Genetic influence has been documented for measures as diverse as videotaped observations of parental behavior toward their children, ratings by parents and children of their family environment, and ratings of peer groups, social support, and life events. Evidence for genetic influence on environmental measures includes some of the most widely used measures of environment – the Home Observation for Measurement of the Environment, the Family Environment Scales, and the Social Readjustment Rating Scale of life events, for example. The goal of this article is to document and discuss these findings and to elicit commentary that might help to shape the course of research on this topic, which has far-reaching implications for the behavioral and brain sciences.

During the first two years of human life a common neural substrate (roughly Broca's area) underlies the hierarchical organization of elements in the development of speech as well as the capacity to combine objects manually, including tool use. Subsequent cortical differentiation, beginning at age two, creates distinct, relatively modularized capacities for linguistic grammar and more complex combination of objects. An evolutionary homologue of the neural substrate for language production and manual action is hypothesized to have provided a foundation for the evolution of language before the divergence of the hominids and the great apes. Support comes from the discovery of a Broca's area homologue and related neural circuits in contemporary primates. In addition, chimpanzees have an identical constraint on hierarchical complexity in both tool use and symbol combination. Their performance matches that of the two-year-old child who has not yet developed the neural circuits for complex grammar and complex manual combination of objects.

A model is proposed for integrating the neural and cognitive aspects of the positive symptoms of acute schizophrenia, using evidence from postmortem neuropathology and neurochemistry, clinical and preclinical studies of dopaminergic neurotransmission, anatomical connections between the limbic system and basal ganglia, attentional and other cognitive abnormalities underlying the positive symptoms of schizophrenia, specific animal models of some of these abnormalities, and previous attempts to model the cognitive functions of the septohippocampal system and the motor functions of the basal ganglia. Anatomically, the model emphasises the projections from the septohippocampal system, via the subiculum, and the amygdala to nucleus accumbens, and their interaction with the ascending dopaminergic projection to the accumbens. Psychologically, the model emphasises a failure in acute schizophrenia to integrate stored memories of past regularities of perceptual input with ongoing motor programs in the control of current perception. A number of recent experiments that offer support for the model are briefly described, including anatomical studies of limbic-striatal connections, studies in the rat of the effects of damage to these connections, and of the effects of amphetamine and neuroleptics, on the partial reinforcement extinction effect, latent inhibition and the Kamin blocking effect; and studies of the latter two phenomena in acute and chronic schizophrenics.

This paper examines the strengths and weaknesses of one of science's most pervasive and flexible metaprinciples; optimality is used to explain utility maximization in economics, least effort principles in physics, entropy in chemistry, and survival of the fittest in biology. Fermat's principle of least time involves both teleological and causal considerations, two distinct modes of explanation resting on poorly understood psychological primitives. The rationality heuristic in economics provides an example from social science of the potential biases arising from the extreme flexibility of optimality considerations, including selective search for confirming vidence, ex post rationalization, and the confusion of prediction with explanation. Commentators are asked to reflect on the extent to which optimality is (1) an organizing principle of nature, (2) a set of relatively unconnected techniques of science, (3) a normative principle for rational choice and social organization, (4) a metaphysical way of looking at the world, or (5) something else still.