Unveiling the Future of Data-Driven Network Analysis: Beyond Pairwise Interactions

This Research Topic envisions the future of multivariate data analysis in Network Physiology and beyond through the lens of high-order interactions. While it is nowadays acknowledged that the classical data-driven description of multivariate datasets based on standard graphs where nodes and links encode individual features and pairwise interactions cannot capture the variety of emergent phenomena in complex networks, several issues are still open about the design, validation, implementation and application of methods to detect and quantify high-order interactions involving three or more nodes in a network system. The present research topic aims at fostering interdisciplinary discussions about the characterization of high-order interactions in the fields of network physiology and neuroscience, as well as at expanding the outreach of multivariate data-driven approaches beyond these fields. Contributions are welcome covering (but not limited to) the following topics:

• Information Dynamics and Information Decomposition
• High-order Mechanisms and High-Order behaviors
• Synergy and redundancy
• Topological analysis: hypergraphs, simplicial complexes and beyond
• Null models for high-order measures
• Data-efficient estimation of high-order measures
• Parametric modeling of multivariate datasets
• Spectral analysis of oscillatory networks
• Non-stationary analysis of dynamic networks
• Applications to brain networks
• Applications to cardiovascular, cardiorespiratory, cerebrovascular networks
• High-order interactions and Artificial Intelligence

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• ... View all formats

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Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review
• Study Protocol
• Systematic Review
• Technology and Code

Keywords: High-order interactions, multivariate data analysis, 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.