Most behavioural genetic studies focus on genetic and environmental influences on inter-individual phenotypic differences at the population level. The growing collection of intensive longitudinal data in social and behavioural science offers a unique opportunity to examine genetic and environmental influences on intra-individual phenotypic variability at the individual level. The current study introduces a novel idiographic approach and one novel method to investigate genetic and environmental influences on intra-individual variability by a simple empirical demonstration. Person-specific non-shared environmental influences on intra-individual variability (...) of daily school feelings were estimated using time series data from twenty-one pairs of monozygotic twins over two consecutive weeks. Results showed substantial inter-individual heterogeneity in person- specific non-shared environmental influences. The current study represents a first step in investigating environmental influences on intra-individual variability with an idiographic approach, and provides implications for future behavioural genetic studies to examine developmental processes from a microscopic angle. (shrink)
Three arguments are given to show that neural constructivism lacks an essential ingredient to explain cognitive development. Based on results in the theory of adaptive signal analysis, adaptive biological pattern information and self-organization in nonlinear systems of information processing, it is concluded that neural constructivism should be further extended to accommodate the occurrence of phase transitions generating qualitative development in the sense of Piaget.
A distinction should be made between the formation of stimulus-driven associations and cognitive concepts. To test the learning mode of a neural network, we propose a simple and classic input-output test: the discrimination shift task. Feed-forward PDP models appear to form stimulus-driven associations. A Hopfield network should be extended to apply the test.
Gintis's article is an example of growing awareness by social scientists of the significance of evolutionary theory for understanding human nature. Although we share its main point of view, we comment on some disagreements related to levels of behavioral analysis, the explanation of social cooperation, and the ubiquity of inter-individual differences in human decision-making. (Published Online April 27 2007).
Bifurcation analysis of a real-time implementation of an ART network, which is functionally similar to the generalized localist model discussed in Page's manifesto shows that it yields a phase transition from local to distributed representation owing to continuous variation of the range of inhibitory connections. Hence there appears to be a qualitative dichotomy between local and distributed representations at the level of connectionistic networks conceived of as instances of nonlinear dynamical systems.
Generalization of the standard behavior longitudinal genetic factor model for the analysis of interindividual phenotypic variation to a genetic state space model for the analysis of intraindividual variation enables the possibility to estimate subject-specific heritabilities.
Cramer et al. present an original and interesting network perspective on comorbidity and contrast this perspective with a more traditional interpretation of comorbidity in terms of latent variable theory. My commentary focuses on the relationship between the two perspectives; that is, it aims to qualify the presumed contrast between interpretations in terms of networks and latent variables.