  The exact mechanisms leading to an earthquake are not fully understood and
the space-time structural features are non-trivial. Previous studies suggest
the seismicity of very low intensity earthquakes, known as micro-earthquakes,
may contain information about the source process before major earthquakes, as
they can quantify modifications to stress or strain across time that finally
lead to a major earthquake. This work uses the history of seismic activity of
micro-earthquakes to analyze the spatio-temporal statistical independence among
the monitoring stations of a seismic network. Using point process distance
measures applied to the micro-earthquakes' spike trains recorded in these
stations, a pre-earthquake state is defined statistically with the aim of
finding a relation between the level of dissimilarity among stations' readings
and the future occurrence of larger earthquakes in the region. This paper also
addresses the compatibility of this statistical approach with the
Burridge-Knopoff spring-block physical model for earthquakes. Based on the
results, there is evidence for an earthquake precursory state associated with
an increase in spike train dissimilarity as evaluated by a statistical
surrogate test.
