EPJ ST Collection: Self-Organization and Higher-Order Interactions in Complex Networks

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Published on 19 January 2026

Guest Editors: Alexander Pisarchik, Jürgen Kurths, Alexander Hramov, Semyon Kurkin, Drozdstoy Stoyanov

The science of complex networks has fundamentally reshaped our understanding of interconnected systems across disciplines. Traditionally, network science has relied on pairwise interactions to model system dynamics. However, many real-world systems—from functional brain networks and ecological communities to social systems and collaborative networks—are driven by higher-order interactions (HOIs), where the relationship between elements cannot be decomposed into simple binary links. Concurrently, self-organization, the process where a system's internal interactions lead to the spontaneous emergence of ordered structure and function without external control, is a hallmark of complex adaptive systems. The interplay between self-organization and HOIs is a frontier of modern network science, crucial for developing accurate models of real-world complexity.

This special issue aims to explore the cutting-edge intersection of self-organization principles and the modeling of higher-order interactions in complex networks and complex systems. We seek to bridge theoretical foundations with applications, highlighting how moving beyond pairwise representations allows for a more profound understanding of emergent phenomena, collective dynamics, and system resilience. The issue will foster interdisciplinary dialogue, bringing together research from physics, mathematics, computer science, neuroscience, social science, and engineering.

The special issue will cover a broad range of topics at the intersection of self-organization and higher-order interactions, including but not limited to:

Theoretical and Methodological Advances:

• Mathematical frameworks for higher-order interactions: simplicial complexes, hypergraphs, and related structures
• General principles of self-organization in complex systems and networks
• Self-organizing dynamics on hypergraphs and simplicial complexes
• Emergence of synchronization, consensus, and collective behavior in systems with HOIs
• Phase transitions and critical phenomena in self-organizing systems with higher-order structure
• Topological data analysis (TDA) and persistent homology for uncovering higher-order patterns
• Generative models for self-organizing networks with non-pairwise interactions
• Dynamical systems theory and control for systems with HOIs
• Information theory and entropy measures for higher-order networks
• Resilience, robustness, and fragility of self-organized systems with HOIs

Applications in Natural, Social, and Engineering Sciences:

• Neuroscience: HOIs in functional brain networks, self-organization of neural assemblies, and modeling of cognition, clinical neuroscience
• Ecology: Species interactions beyond competition/predation (e.g., higher-order mutualism), and self-organization in ecosystems
• Social Systems: Emergence of collaboration, consensus, and social contagion in groups with multi-agent interactions
• Physics and Chemistry: Self-organization in condensed matter systems and active matter with non-pairwise forces
• Engineering: Design and control of self-organizing robotic swarms, multi-agent systems, and smart infrastructure
• Computer Science: Complex networks in machine learning (e.g., Graph Neural Networks for hypergraphs), self-organizing data structures

Interdisciplinary and Cross-Cutting Themes:

• Comparative analysis of self-organization in pairwise vs. higher-order network models
• Data-driven discovery of higher-order structures from real-world datasets
• The role of higher-order interactions in facilitating or constraining emergent order
• AI and machine learning for analyzing and predicting self-organization in hypergraphs

We invite original research articles, reviews, and perspective papers that contribute to the theoretical understanding or practical applications of self-organization and higher-order interactions in complex networks. Submissions should present novel methodologies, empirical analyses, or interdisciplinary approaches that address fundamental challenges in the field. All submissions will undergo a rigorous peer-review process to ensure the highest quality and relevance to the special issue.

This special issue will provide a timely and centralized platform for researchers to disseminate groundbreaking work on one of the most exciting developments in complex systems science. By moving beyond the paradigm of pairwise connections, this collection will showcase how a deeper consideration of system structure is essential for understanding self-organization and emergence. It will serve as a foundational reference for academics across physics, life sciences, and social sciences, and inspire new research directions for theorists, computational scientists, and engineers tackling the complexity of real-world networks.

We look forward to receiving your contributions and advancing the dialogue on the intricate relationship between structure and dynamics in complex systems.

Articles should be submitted to the Editorial Office of EPJ ST via the submission system, and should be clearly identified as intended for the topical issue “Self-Organization and Higher-Order Interactions in Complex Networks’”.

More detailed author information including paper types can be found in the Submission Guidelines. For the preparation of the manuscripts a special latex template (preferably single-column layout) is available here.

Prof. Alexander Pisarchik, Center for Biomedical Technoogy, Universidad Politécnica de Madrid, Campus de Montegancedo, Spain, Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

Prof. Jürgen Kurths, Potsdam Institute for Climate Impact Research, Germany, Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

Prof. Alexander Hramov, Research Institute of Applied AI and Digital Solutions, Plekhanov Russian University of Economics, Russia, Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

Prof. Semyon Kurkin, Research Institute of Applied AI and Digital Solutions, Plekhanov Russian University of Economics, Russia, Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

Prof. Drozdstoy Stoyanov, Medical University of Plovdiv, Bulgaria, Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

Open Access: EPJST is a hybrid journal offering Open Access publication via the Open Choice programme and a growing number of Transformative Agreements. If the institution of the CORRESPONDING AUTHOR is part of such a Transformative Agreement, the Open Access fee will be covered by the agreement partner. All agreements are listed with more details under TRANSFORMATIVE Agreements. Eligibility will be automatically verified when the corresponding author is requested to complete the relevant affiliation information after acceptance of the paper during the production process. Corresponding authors not affiliated to institutes with Transformative Agreements are redirected to proceed with “Please select your publishing model” and have to decide between paying the current Open Access fee or choosing the subscription option without any publication charges.