Unveiling causal interactions in complex systems

Stavros K. Stavroglou, Athanasios A. Pantelous, H. Eugene Stanley, Konstantin M. Zuev

Research output: Contribution to journalArticleResearchpeer-review


Throughout time, operational laws and concepts from complex systems have been employed to quantitatively model important aspects and interactions in nature and society. Nevertheless, it remains enigmatic and challenging, yet inspiring, to predict the actual interdependencies that comprise the structure of such systems, particularly when the causal interactions observed in real-world phenomena might be persistently hidden. In this article, we propose a robust methodology for detecting the latent and elusive structure of dynamic complex systems. Our treatment utilizes short-term predictions from information embedded in reconstructed state space. In this regard, using a broad class of real-world applications from ecology, neurology, and finance, we explore and are able to demonstrate our method's power and accuracy to reconstruct the fundamental structure of these complex systems, and simultaneously highlight their most fundamental operations.

Original languageEnglish
Pages (from-to)7599-7605
Number of pages7
JournalProceedings of the National Academy of Sciences of the United States of America
Issue number14
Publication statusPublished - 7 Apr 2020


  • Brain
  • Causality
  • CDS markets
  • Complex systems
  • Ecosystem

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