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A Multilayer Network Model for Motor Competence from the View of the Science of Complexity.
Paulo Felipe Ribeiro Bandeira1, Isaac Estevan2, Michael Duncan3
1Department of Physical Education, Universidade Regional do Cariri, Crato, Brazil.
Sports Medicine (Auckland, N.Z.)
|December 26, 2024
Summary
Motor competence involves complex, interconnected factors, not simple linear paths. A new multilayer network framework helps analyze these dynamic relationships for better understanding.
Area of Science:
- Motor Development
- Network Science
- Biophysics
Background:
- Motor competence arises from a complex system of interacting correlates, defying simple linear explanations.
- Studying motor competence is challenging due to the diversity of factors, their interconnections, and rapid changes over time.
Purpose of the Study:
- To introduce a novel multilayer framework for representing the complex, non-linear, and dynamic relationships within motor competence.
- To provide theoretical background and mathematical procedures for analyzing motor competence as a network.
Main Methods:
- Development of a multilayer network framework.
- Application of mathematical procedures to model non-linear and dynamic relationships between motor competence correlates.
Main Results:
- The proposed framework allows for a more accurate representation of motor competence's topology and dynamics.
- This approach facilitates a deeper understanding of the structure and function of motor competence across development.
Conclusions:
- A multilayer network perspective offers a promising new approach to studying motor competence.
- This framework could significantly advance the understanding of motor competence in developmental research.
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