Intraindividual variability across the life span: Moving toward computational developmental science

Nilam Ram, Lisa Gatzke-Kopp, Denis Gerstorf, Michael Coccia, Jennifer Morack, Peter C.M. Molenaar

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations

Abstract

Across domains of science, many theoretical and empirical frameworks have been developed to explain if, how, and when entities change. In computational biology, for example, researchers search for the physiological and chemical systems governing the emergence and development of patterns on animals’ skins. Intriguing are both the emergence of interspecies differences (e.g., leopard spots, zebra stripes) and the development of unique patterns on each animal within a species-intraspecies differences (Murray, 1988). A variety of computational methods are used to better understand how and why the spots and stripes emerge. Similar to biologists, life-span developmentalists conceptualize general principles about how individuals’ behaviors (used here as a general term encompassing actions, thoughts, feelings, perceptions, etc.) can change or be changed, and how those changes progress over the life span. Intriguing are the emergence of interindividual differences and the development of unique patterns of intraindividual change (Baltes, Reese, & Nesselroade, 1977). Playing in the interstices between disciplines, we explore in this chapter how computational methods used in systems biology might be integrated into the generating and testing of life-span developmental theory. Using examples from the study of intraindividual variability over the life span, we are starting to use these methods to develop and refine developmental and process-oriented theory. In the sections that follow, we begin moving toward what we think computational developmental science, as a mode of inquiry, might look like.

Original languageEnglish (US)
Title of host publicationHandbook of Intraindividual Variability Across the Life Span
PublisherTaylor and Francis
Pages16-34
Number of pages19
ISBN (Electronic)9781136285233
ISBN (Print)9780415534864
DOIs
StatePublished - Jan 1 2014

All Science Journal Classification (ASJC) codes

  • Psychology(all)
  • Social Sciences(all)

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