A team of neuroscientists has published a paper
claiming it has developed a mathematical calculation that could potentially
predict the tipping point of any massive event -- from a market crash to a
brain seizure.
Neuroscientists are used to working on systems of
nodes, whereby one neuron in the brain ignites a stream of connected activity
when activated -- a web-like chain reaction that unfolds in seemingly
unpredictable ways. Of course, these can be predicted if you have the
right information.
For instance, when a team of neuroscientists monitored the
brain activity of a macaque while its hand was being touched in a recent study,
the team could identify which chain reaction of electrical stimulation in the
brain signified that sensation.
By replicating the same pattern, the team could
cause the macaque to "feel" that same sensation artificially. Now, in
a study let by professors at the University of Sussex, along with colleagues
working in psychology and physics, that kind of pattern hunting has been
translated into a computer simulation that those behind it say could one day
"predict calamitous events before they happen".
The team, also made up of professors from the Sackler
Centre for Consciousness Science and the Centre for Research in Complex
Systems at Charles Sturt University in Australia, developed an equation that
revealed the effects of information flow between multiple nodes.
According to
Lionel Barnett, lead author on the paper, they found the fact that all the
elements "casually influence each other" to be of most importance. It
means we must first identify all the parts of a system, then assess the
relationship between individual nodes and then their causal effect on the
whole.
In doing so, we can find out when the fate of a node is dependent on its
own behavior because it behaves so differently from the others, and when its
fate is dependent on all other nodes.
"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," said Barnett.
The team suggests it's possible to measure when a
system reaches that tipping point, when it moves from a healthy system to one
that is overwhelm- ingly indicating a change. It occurs when an overwhelming
number of nodes have caused an integrated change too big to remain stable. The
equation was tested, but not using seizure or financial data.
It was tested
using a model physicists use to predict "phase transitions" in
standard systems, know as the Ising model. It's a model of a ferromagnetic
material that depicts how atoms in a one-, two- and three-dimensional lattices
interact, and how these small phase transitions together generate a total state
change -- creating a magnetic field.
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