title: Nonlinear epigenetic variance: review and simulations.
abstract: We present a review of empirical evidence that suggests that a substantial portion of phenotypic variance is due to nonlinear (epigenetic) processes during ontogenesis. The role of such processes as a source of phenotypic variance in human behaviour genetic studies is not fully appreciated. In addition to our review, we present simulation studies of nonlinear epigenetic variance using a computational model of neuronal network development. In each simulation study, time series for monozygotic and dizygotic twins were generated and analysed using conventional behaviour genetic modelling. In the results of these analyses, the nonlinear epigenetic variance was subsumed under the non-shared environmental component. As is commonly found in behaviour genetic studies, observed heritabilities and unique environmentabilities increased with time, whereas common environmentabilities decreased. The fact that the phenotypic effects of nonlinear epigenetic processes appear as unsystematic variance in conventional twin analyses complicates the identification and quantification of the ultimate genetic and environmental causes of individual differences. We believe that nonlinear dynamical system theories provide a challenging perspective on the development of individual differences, which may enrich behaviour genetic studies.
authors.affiliation: Department of Psychology, University of Amsterdam, Roetersstraat 15, 1018 WB, Amsterdam, The Netherlands. k.j.kan@uva.nl
authors.forename: Kees-Jan
authors.initials: KJ
authors.lastname: Kan
authors.forename: Annemie
authors.initials: A
authors.lastname: Ploeger
authors.forename: Maartje E J
authors.initials: ME
authors.lastname: Raijmakers
authors.forename: Conor V
authors.initials: CV
authors.lastname: Dolan
authors.forename: Han L J
authors.initials: HL
authors.lastname: van der Maas
mesh_terms: D000818:Animals; D003198:Computer Simulation; D015509:Developmental Biology; D004777:Environment; D044127:Epigenesis, Genetic / Q000502:physiology*; D014644:Genetic Variation / Q000235:genetics*; D005824:Genetics, Behavioral; D006801:Humans; D008959:Models, Neurological; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D010641:Phenotype