The genetic analysis of repeated measures I. Simplex models

The well-known simplex model is extended to a model that may be used for the genetic and environmental analysis of covariance structures. This "double " simplex structure can be specified as a LISREL model. It is shown that data which give rise to a simplex correlation structure, such as repeated-measures data, do not fit a factor-analysis model. The parameter estimation of the simplex model is illustrated with computersimulated twin data. KEY WORDS: repeated measures; longitudinal data; simplex models; genetic correlations; environmental correlations; twin data; LISREL

The genetic analysis of repeated measures II. The Karhunen-Loève expansion

A new approach to the genetic analysis of time series of arbitrary length and with arbitrary covariance function is outlined. This approach is based on the simultaneous eigenvalue decomposition of the covariance matrices of the original time series obtained from monozygotic (MZ) and dizygotic (DZ) twins. The method is illustrated with computer-simulated twin data. © 1987 Plenum Publishing Corporation

A third source of developmental differences

An illustrative list is presented of human and animal studies which each point to the existence of a third source, in addition to genetic and environmental factors, underlying phenotypic differences in development. It is argued that this third source may consist of nonlinear epigenetic processes that can create variability at all phenotypical-somatic and behavioral-levels. In a quantitative genetic analysis with human subjects, these processes are confounded with within-family environmental influences. A preliminary model to quantify these influences is introduced. KEY WORDS: Developmental noise; epigenetic processes; neural networks; chaotic dynamics

Using factor scores to detect G x E interactive origin of "pure" genetic or environmental factors obtained in genetic covariance structure analysis

Moment expressions for individual factor scores can serve as simple tests for the presence of a particular class of interaction factors that are disguised as pure genetic and/or environmental factors. That is, individual genetic and environmental factor scores may be used to construct fourth‐order moments of these factors in order to test whether a common genetic or environmental factor in the multivariate genetic factor model is in fact of the interactive origin concerned. Expected fourth‐order moments are derived for cases with and without interaction. Application of fourth‐order moments of factor scores to detect interactive origin of common factors is illustrated with simulated twin data. Copyright © 1990 Wiley‐Liss, Inc., A Wiley Compan

A genetic perspective on the developing brain: electrophysiological indices of neural functioning in young and adolescent twins.

Changes in genetic and environmental influences on electroencephalographic (EEG) and event-related potential (ERP) indices of neural development were studied in two large cohorts of young (N = 418) and adolescent (N = 426) twins. Individual differences in these indices were largely influenced by genetic factors, and throughout development, the stable part of the variance was mainly genetic. Both EEG power (which describes the amount of variability in brain electrical potentials that can be attributed to different frequencies) and long-distance EEG coherence (which is the squared cross-correlation between two EEG signals at different scalp locations and can be regarded as an index for cortico-cortical connectivity) were highly heritable. ERP-P300 latencies and amplitudes were low to moderately heritable. Clear differences between young children and adolescents could be observed in the heritabilities of EEG and ERP indices. The heritabilities of EEG power and EEG coherence were higher in adolescents than in children, whereas the heritabilities of P300 latencies were lower. Both cohorts (young children and adolescents) were measured twice: The children were tested when they were 5 and again at 7 years, the adolescents when they were 16 and again at 18 years. Therefore, within these age ranges a more detailed analysis of age-related changes in heritabilities and in the emergence of new genetic influences could be studied. The heritabilities of EEG powers and P300 amplitudes and latencies did not change much from age 5 to age 7 and from age 16 to 18 years. The heritabilities of a substantial number of connections within the cortex, however, as indexed by EEG coherence, changed significantly from age 5 to age 7, though not from age 16 to 18. The only changes in the heritabilities in adolescents were connections within the prefrontal cortex, which is in agreement with theories of adolescent development. These age-related changes in the heritabilities may reflect a larger impact of maturation on cortico-cortical connectivity in childhood than in adolescence. Evidence was found for qualitative changes in brain electrophysiology in young children: New genetic factors emerged at age 7 for posterior EEG coherences and for P300 latency at some scalp locations. This supports theories of qualitative stage transitions in this age range, as previously suggested using behavioral and EEG data

Stability of genetic and environmental influences om P300 amplitude: a longitudinal study in adolescent twins

Examined the stability of genetic and environmental influences on individual differences in P300 amplitude during adolescence. The P300 component is an event-related brain potential (ERP) that has attracted much attention as a biological marker for disturbed cognitive processing in psychopathology. Understanding the genetics of this biological marker may contribute to understanding the genetics of the associated psychopathologies. In a group of 213 adolescent twin pairs, the P300 component was measured twice, the first time at age 16 and the second time 18 months later. A large part of the variance of the P300 amplitude could be explained by familial factors, with estimates ranging from 30% to 81%. Whether the familial resemblance was due to genetic or shared environmental factors depended on sex. For males, genetic factors explained familial resemblance in P300 amplitude, but for females such resemblance was likely due to shared environmental factors. The phenotypic stability of the P300 amplitude from 16 to 18 years was high in both sexes, and stability could be attributed largely to the same familial factors. There was no evidence that new familial influences emerged at age 18

Control Theory Forecasts of Optimal Training Dosage to Facilitate Children’s Arithmetic Learning in a Digital Educational Application

Education can be viewed as a control theory problem in which students seek ongoing exogenous input—either through traditional classroom teaching or other alternative training resources—to minimize the discrepancies between their actual and target (reference) performance levels. Using illustrative data from n= 784 Dutch elementary school students as measured using the Math Garden, a web-based computer adaptive practice and monitoring system, we simulate and evaluate the outcomes of using off-line and finite memory linear quadratic controllers with constraints to forecast students’ optimal training durations. By integrating population standards with each student’s own latent change information, we demonstrate that adoption of the control theory-guided, person- and time-specific training dosages could yield increased training benefits at reduced costs compared to students’ actual observed training durations, and a fixed-duration training scheme. The control theory approach also outperforms a linear scheme that provides training recommendations based on observed scores under noisy and the presence of missing data. Design-related issues such as ways to determine the penalty cost of input administration and the size of the control horizon window are addressed through a series of illustrative and empirically (Math Garden) motivated simulations