Abstract
Neural spike train analysis methods are mainly used for understanding the temporal aspects of neural information processing. One approach is to measure the dissimilarity between the spike trains of a pair of neurons, often referred to as the spike train distance. The spike train distance has been often used to classify neuronal units with similar temporal patterns. Several methods to compute spike train distance have been developed so far. Intuitively, a desirable distance should be the shortest length between two objects. The Earth Mover’s Distance (EMD) can compute spike train distance by measuring the shortest length between two spike trains via shifting a fraction of spikes from one spike train to another. The EMD could accurately measure spike timing differences, temporal similarity, and spikes time synchrony. It is also robust to firing rate changes. Victor and Purpura (1996) distance measures the minimum cost between two spike trains. Although it also measures the shortest path between spike trains, its output can vary with the time-scale parameter. In contrast, the EMD measures distance in a unique way by calculating the genuine shortest length between spike trains. The EMD also outperforms other existing spike train distance methods in measuring various aspects of the temporal characteristics of spike trains and in robustness to firing rate changes. The EMD can effectively measure the shortest length between spike trains without being considerably affected by the overall firing rate difference between them. Hence, it is suitable for pure temporal coding exclusively, which is a predominant premise underlying the present study.
Highlights
A spike train is the sequence of neuronal firing timings, where a spike refers to the firing of an action potential
If one aims to measure a distance between a pair of spike trains independent of the overall rate difference, which we call as purely timingsensitive, the distance should reflect only a difference of spike timing distributions, no matter how different the overall firing rate is between trains
In our development of spike train distance, we focus on a particular aspect of the firing rate profile, an overall firing rate difference between spike trains, whereas we refer a temporal pattern of spike train to the distribution of spike timings in time within a spike train
Summary
A spike train is the sequence of neuronal firing timings, where a spike refers to the firing of an action potential. The simulations are designed to evaluate the performance of the spike train distances with respect to essential aspects of temporal patterns, including spike timing differences, temporal similarity, and spike time synchrony, as well as the robustness against firing rate changes in spike trains to deal with pure temporal coding. We evaluate how various spike train distance methods, including the proposed one, represent pure temporal coding using a spike generation probabilistic model, in which a spiking probability varies with time independent of the number of spikes. This includes the test of the robustness of each method against firing rate changes by alternating the total number of spikes while maintaining temporal coding unchanged. It should be noted that these advantages are not directly transferable to rate coding
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