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Living on the edge: network neuroscience beyond nodes
Richard F Betzel1, Joshua Faskowitz2, Olaf Sporns1
1Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA; Cognitive Science Program, Indiana University, Bloomington, IN 47405, USA; Program in Neuroscience, Indiana University, Bloomington, IN 47405, USA; Network Science Institute, Indiana University, Bloomington, IN 47405, USA.
Trends in Cognitive Sciences
|September 16, 2023
Summary
Network neuroscience is shifting focus from neural elements to the connections between them. An edge-centric approach offers a new perspective for understanding brain networks and their functions.
Area of Science:
- Neuroscience
- Network Science
- Computational Biology
Background:
- Traditional network neuroscience focuses on nodes (cells, regions) rather than the connections (edges).
- This node-centric view may limit understanding of complex neural systems.
- There is a need for methods that prioritize the study of connections.
Purpose of the Study:
- Introduce and review a novel 'edge-centric' method in network neuroscience.
- Explore the applications, advantages, and disadvantages of this new approach.
- Connect edge-centric methods with existing network science and neuroimaging techniques.
Main Methods:
- Review of a recently proposed 'edge-centric' analytical method.
- Conceptual and mathematical comparison with prior network science and neuroimaging approaches.
- Analysis of current applications and limitations of the edge-centric method.
Main Results:
- The edge-centric perspective offers a potentially fruitful new direction for network neuroscience.
- Established conceptual and mathematical links between edge-centric analysis and existing methods.
- Identified merits and limitations of the reviewed edge-centric approach.
Conclusions:
- Edge-centric analysis represents a promising paradigm shift in network neuroscience.
- Further research is needed to extend and refine edge-centric methodologies.
- This approach may unlock new insights into brain network organization and function.
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