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We present a neural network that is capable of completing and correcting a spiking pattern given only a partial, noisy version. It operates in continuous time and represents information using the relative timing of individual spikes. The network is capable of correcting and recalling multiple patterns simultaneously. We analyse the network's performance in terms of information recall. We explore two measures of the capacity of the network, one that values the accurate recall of individual spikedoi:10.1162/neco_a_00306 pmid:22509970 fatcat:7jz553zwbzesdhenprdpyoj4yi