About this Research Topic
Edge-centric approaches to functional brain networks have gained significant attention in recent years, particularly within the broader context of network science. Traditionally, network analysis has focused on vertices, representing elementary units of a system, and their roles in the structure and dynamics of networks. This vertex-centric perspective has been instrumental in identifying critical components, optimizing network performance, and understanding robustness and perturbations. However, the interactions between vertices, represented by edges, have not been as thoroughly explored. Recent studies have begun to highlight the importance of these interactions, suggesting that a deeper understanding of edges could provide new insights into the behavior and control of complex dynamical systems. Despite these advancements, there remains a gap in comprehensive edge-centric methodologies, which this Research Topic aims to address.
This Research Topic aims to advance the study of complex dynamical systems by focusing on edge-centric approaches. Specifically, it seeks to move beyond traditional vertex-specific analyses to explore the fundamental nature of network edges. The main objectives include assessing the role of edges in network dynamics, identifying critical edges and path structures, and understanding the impact of edge-based perturbations. By developing new edge-centric metrics and methodologies, this research aims to provide a more nuanced understanding of network behavior and control mechanisms. The goal is to contribute to the broader field of network science by offering novel insights and tools that can be applied across various domains, including natural, socioeconomic, and technological systems.
To gather further insights into the range and limitations of edge-centric approaches in functional brain networks, we welcome articles addressing, but not limited to, the following themes:
- Assessing the roles and properties of edges within networks.
- Identifying key edges which may dictate overall network functionality or stability.
- Exploring critical pathways and their structural and functional implications.
- Examining the effects of manipulations at the edge level on network dynamics.
- Techniques for controlling and forecasting behaviors in complex adaptive systems.
- Investigating the spatial and temporal dimensions of dynamically evolving networks.
- Strategies for network growth and density reduction while preserving essential dynamics.
This Research Topic aims to advance the study of complex dynamical systems by focusing on edge-centric approaches. Specifically, it seeks to move beyond traditional vertex-specific analyses to explore the fundamental nature of network edges. The main objectives include assessing the role of edges in network dynamics, identifying critical edges and path structures, and understanding the impact of edge-based perturbations. By developing new edge-centric metrics and methodologies, this research aims to provide a more nuanced understanding of network behavior and control mechanisms. The goal is to contribute to the broader field of network science by offering novel insights and tools that can be applied across various domains, including natural, socioeconomic, and technological systems.
To gather further insights into the range and limitations of edge-centric approaches in functional brain networks, we welcome articles addressing, but not limited to, the following themes:
- Assessing the roles and properties of edges within networks.
- Identifying key edges which may dictate overall network functionality or stability.
- Exploring critical pathways and their structural and functional implications.
- Examining the effects of manipulations at the edge level on network dynamics.
- Techniques for controlling and forecasting behaviors in complex adaptive systems.
- Investigating the spatial and temporal dimensions of dynamically evolving networks.
- Strategies for network growth and density reduction while preserving essential dynamics.
Keywords: complex networks, brain, structure-function relationship, nodes and links, vertices and edges, centrality, interactions, dynmacial systems, nonlinear dynamics, data analysis, modelling, network physiology
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
