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CompleNet is an international conference on complex networks that unites researchers and practitioners from various disciplines, including sociology, biology, physics, and computer science, who share a common desire to gain a deeper comprehension of interdependencies within and across systems. CompleNet provides a platform to exchange ideas and present discoveries related to diverse network types, encompassing biological, technological, informational, and social networks. CompleNet's primary objective is to delve into and commemorate the interdisciplinary essence of complex networks.

Applications of Network Science Algorithms Biological Systems Community Structure Dynamics on and of Networks Disease Spread in Populations and Social Networks Ecological Networks Financial Networks Human Behavior and Social Influence Impact Performance and Success Prediction Networks of Coupled Nonlinear Systems Multiplex and Temporal Networks Network Topology and Geometry Network Controllability and Resilience Networks and Humanities Networks and Mobility Higher-order Networks Network Visualisation Network Neuroscience Machine Learning for Network Analysis Network-based Machine Learning and AI Science of Science Social Media and Social Networks Spatial Networks Sustainable Development and Networks

Réseaux complexes,    Cours et évènements pour étudiants en mathématiques

CIEM and IUMA, Computational Dynamics group of the University of Zaragoza.

Email.: cody@unizar.es

Neuroscience is nowadays one of the most collaborative and active scientific research fields as it has been increasingly involving the participation of experts from other disciplines. Computational and mathematical aspects of neuroscience are currently playing an important role both in modeling and replicating experimental findings and in explaining the underlying mechanisms of neurophysiological or cognitive processes. The aim of this Fourth Workshop on Neurodynamics, NDy'26 (previous editions were NDy'23 NDy'18, NDy'14) is to present an overview of successful achievements in this rapidly developing collaborative field by putting together different types of applications of nonlinear dynamics (geometrical tools in dynamical systems, numerical methods, computational schemes, dynamical measures, machine learning...) to different problems in neuroscience (mononeuronal dynamics, network activity, cognitive problems, ...).