  Measures of spike train synchrony have become important tools in both
experimental and theoretical neuroscience. Three time-resolved measures called
the ISI-distance, the SPIKE-distance, and SPIKE-synchronization have already
been successfully applied in many different contexts. These measures are time
scale independent, since they consider all time scales as equally important.
However, in real data one is typically less interested in the smallest time
scales and a more adaptive approach is needed. Therefore, in the first part of
this Chapter we describe recently introduced generalizations of the three
measures, that gradually disregard differences in smaller time-scales. Besides
similarity, another very relevant property of spike trains is the temporal
order of spikes. In the second part of this chapter we address this property
and describe a very recently proposed algorithm, which quantifies the
directionality within a set of spike train. This multivariate approach sorts
multiple spike trains from leader to follower and quantifies the consistency of
the propagation patterns. Finally, all measures described in this chapter are
freely available for download.
