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Superstatistical analysis and modelling of heterogeneous random walks

Search and rescue teams routinely use Bayesian updating to track down crashed airplanes or sunken ships: they draw a map with a first guess of the most probable locations and then continuously update the probability map as new information comes in. Physicists from the University of Erlangen-Nuremberg describe in the current issue of Nature Communications how Bayesian updating can be applied to moving objects even when they slowly or abruptly change their behavior. The researchers tracked migrating tumor cells through an artificial tissue matrix and discovered that the cells frequently switch their migration mode, but over time a distinct pattern in the Bayesian probability map emerged. Like a fingerprint, this pattern was specific for different environments in which the tumor cells migrated. The authors suggest that this fingerprint can be used as a diagnostic marker of tumor aggressiveness.

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Read the full publication in Nature Communications.