  Techniques for recording large-scale neuronal spiking activity are developing
very fast. This leads to an increasing demand for algorithms capable of
analyzing large amounts of experimental spike train data. One of the most
crucial and demanding tasks is the identification of similarity patterns with a
very high temporal resolution and across different spatial scales. To address
this task, in recent years three time-resolved measures of spike train
synchrony have been proposed, the ISI-distance, the SPIKE-distance, and event
synchronization. The Matlab source codes for calculating and visualizing these
measures have been made publicly available. However, due to the many different
possible representations of the results the use of these codes is rather
complicated and their application requires some basic knowledge of Matlab. Thus
it became desirable to provide a more user-friendly and interactive interface.
Here we address this need and present SPIKY, a graphical user interface which
facilitates the application of time-resolved measures of spike train synchrony
to both simulated and real data. SPIKY includes implementations of the
ISI-distance, the SPIKE-distance and SPIKE-synchronization (an improved and
simplified extension of event synchronization) which have been optimized with
respect to computation speed and memory demand. It also comprises a spike train
generator and an event detector which makes it capable of analyzing continuous
data. Finally, the SPIKY package includes additional complementary programs
aimed at the analysis of large numbers of datasets and the estimation of
significance levels.
