Measuring spike train synchrony between neuronal populations

With the increasing availability of multi-unit recordings the focus of attention starts to shift from bivariate methods towards methods that provide the possibility to study patterns of activity across many neurons. Measures of multi-neuron spike train synchrony are becoming indispensable tools for addressing issues such as network synchronization, spike timing reliability and neuronal coding. However, many multi-neuron synchrony measures are extensions of bivariate measures. Two of the most prominent bivariate approaches are the spike train metrics by Victor-Purpura and van Rossum [1,2]. The former evaluates the cost needed to transform one spike train into the other using only certain elementary steps [1], while the latter measures the Euclidean distance between the two spike trains after convolution of the spikes with an exponential function [2]. Both methods involve one parameter that sets the time scale. In contrast, a more recent bivariate approach, the ISI-distance [3], is time scale independent and self-adaptive. Another essential difference is that the ISI-distance relies on the relative length of interspike intervals (ISI) and not on the timing of spikes. Finally, this method also allows the visualization of the relative firing pattern in a time-resolved manner. ... ...