Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.06.03.131573v1?rss=1 Authors: Sotomayor-Gomez, B., Battaglia, F. P., Vinck, M. Abstract: Neuronal coding and memory formation depend on temporal activation patterns spanning high-dimensional ensembles of neurons. To characterize these high-dimensional spike sequences, it is critical to measure their dissimilarity across different epochs (e.g. stimuli, brain states) in terms of all the relative spike-timing relationships. Such a dissimilarity measure can then be used for dimensionality reduction, clustering of sequences or decoding. Here, we present a new measure of dissimilarity between multi-neuron spike sequences based on optimal transport theory, called SpikeShip. SpikeShip computes the optimal transport cost (Earth Mover's Distance) to make all the relative spike-timing relationships (across N neurons) identical between two spiking patterns. It achieves this by computing the optimal transport of spikes across time, per neuron separately, and then decomposing this transport cost in a temporal rigid translation term and a vector of neuron-specific transport flows. This yields a suitable geometry for spike sequences. SpikeShip can be effectively computed for high-dimensional neuronal ensembles and has linear O(N) cost. Furthermore, it is explicitly based on the higher-order structure in the spiking patterns. SpikeShip opens new avenues for studying neural coding and memory consolidation by finding patterns in high-dimensional neural ensembles. Copy rights belong to original authors. Visit the link for more info