A study led by the University of Sussex has developed a mathematical equation that might be able to help predict complex calamities, such as financial crashes.
The model recognises that 'information flow' in a system reaches a peak just before it moves from a stable to an unstable state, a change known as a 'phase transition'.
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These are common to a wide variety of situations including epileptic seizures and climate change.
Until now these types of information flow appeared to happen unpredictably, or at least in a way that we didn't know how to predict.
Lead researcher Dr Lionel Barnett said: "The key insight in the paper is that the dynamics of complex systems – like the brain and the economy – depend on how their elements causally influence each other; in other words, how information flows between them.
"And that this information flow needs to be measured for the system as a whole, and not just locally between its various parts."
This meant identifying all the nodes in a system and then determining their relationship to the whole.
From this holistic approach, it can be seen if the fate of a node is dependant on its own behaviour, or that of the other nodes.
If a critical number of nodes are seen to be acting differently to the system as a whole, then this would predict a phase transition. Simple.
Professor Anil Seth, Co-Director of the Sackler Centre, was keen to point out the potential future implications of such an equation.
He said: "The implications of the work are far-reaching. If the results generalise to other real-world systems, we might have ways of predicting calamitous events before they happen, which would open the possibility for intervention to prevent the transition from occurring."
The team was also made up of scientists from the Sackler Centre for Consciousness Science and the Centre for Research in Complex Systems at Charles Sturt University in Australia.