Complex Dynamical Systems in Human Development

Ralf F A Cox,Ruud J R Den Hartigh,Michael J Richardson,Till D Frank,Chen Yu

doi:10.1155/2019/5010413

Ralf F A Cox, Ruud J R Den Hartigh + Show 3 more

Open Access

https://doi.org/10.1155/2019/5010413

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Abstract

Researchers from the complex dynamical systems perspective seek their explanations of human behavior and development in the dynamical interactions across many levels in an active, situated individual. Tat is to say, behavior and development are both constraining and constrained by the continuous exchange between a myriad of processes distributed across brain, body, and environment. This fundamentally questions the more traditional rationale that behavior and development of any kind can be explained by targeting a low number of domain-specific, static components or environmental factors. In such a mechanistic approach, components are typically thought to exert their causal effects in a chain-like fashion, and development is explained by the function and place of the components in the chain. However, compiling evidence demonstrates that human behavior and development are dynamic, multi-scaled, and emergent phenomena. It is for this reason that they should be studied from a complex dynamical systems perspective.

Highlights

Researchers from the complex dynamical systems perspective seek their explanations of human behavior and development in the dynamical interactions across many levels in an active, situated individual
Compiling evidence demonstrates that human behavior and development are dynamic, multiscaled, and emergent phenomena
Techniques are needed that enable a detailed analysis of the temporal structure in time series and that can handle both intraindividual and interindividual variability in developmental datasets, preferably in combination

Summary

Introduction

Researchers from the complex dynamical systems perspective seek their explanations of human behavior and development in the dynamical interactions across many levels in an active, situated individual. In the social sciences there is an increase in the use of nonlinear time series analysis and dynamical modeling as a means to study human development. Advancements are made in developing and applying techniques such as recurrence quantification analyses and longitudinal network modeling.

Results

Conclusion