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Learning spatiotemporal signals using a recurrent spiking network that discretizes time

Fig 4

Learning sequences in parallel.

(A) The recurrent network projects to two sets of neurons. (B) Two different sequences, ABCBA and DEDED, are learned by alternating between them and presenting each for 2 seconds at a time. (C) The read-out weight matrix after 24 seconds of learning. (D) Raster plot of spontaneous sequence reactivations, where an external inhibitory current is assumed to control which sequence is replayed.

Fig 4

doi: https://doi.org/10.1371/journal.pcbi.1007606.g004