SCL’s researcher Igor Franović and his collaborators have published a review paper that has been featured in Chaos. Igor and his colleagues introduce a new paradigm of regime switching in complexity science, which involves not only sudden isolated switching events, called tipping or critical transitions, but also captures sequential activity patterns, such as tipping cascades, heteroclinic switching, noise-induced attractor hopping or chaotic itinerancy.

The review highlights the necessity for interdisciplinary exchange, from neuroscience and gene networks, over epidemic spreading, power grids and extreme events, to machine learning, adaptive networks and neuromorphic computing. Indicating the latest mathematical and data-driven approaches to explaining the dynamical mechanisms and the advanced methods to detect, predict and potentially control regime switching, the review considers both processes with critical impact, like the ones associated with climate change, and the processes that seamlessly blend into our everyday lives, shaping motor coordination, working memory or gene expression.