Connectivity and complex systems: learning from a multi-disciplinary perspective

Area of Science:

• Interdisciplinary studies
• Complex systems science
• Network science

Background:

• Connectivity is a concept used across disciplines to describe complex systems.
• Disciplinary approaches to connectivity have evolved independently, yet share similarities.
• Implementing connectivity concepts faces ontological and epistemological challenges.

Purpose of the Study:

• To explore four key challenges in applying connectivity to complex systems.
• To examine discipline-specific insights from diverse fields.
• To propose a unified approach for connectivity studies.

Main Methods:

• Review of literature across Computational Neuroscience, Ecology, Geomorphology, Neuroscience, Social Network Science, and Systems Biology.
• Analysis of ontological and epistemological constraints in defining units, separating structural and functional connectivity, understanding emergent behavior, and measuring connectivity.
• Evaluation of how connectivity-based approaches enhance understanding of complex systems.

Main Results:

• Identified four major challenges in the conceptualization and application of connectivity across disciplines.
• Demonstrated similarities and differences in connectivity approaches across diverse scientific fields.
• Highlighted the potential of network-based methods to address these challenges.

Conclusions:

• A unified 'common toolbox' for connectivity studies is proposed, based on network approaches.
• Overcoming existing constraints can advance the understanding of complex systems through connectivity.
• Interdisciplinary collaboration is crucial for developing universal connectivity frameworks.