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Reservoir computing (RC) is a recent paradigm in the field of recurrent neural networks. Networks in RC have a sparsely and randomly connected fixed hidden layer, and only output connections are trained. RC Networks have recently received increased attention as a mathematical model for generic neural microcircuits, to investigate and explain computations in neocortical columns. Applied to specific tasks, their fixed random connectivity, however, leads to significant variation in performance.doi:10.2976/1.3240502 pmid:20357891 pmcid:PMC2801534 fatcat:ek2ym26zijbureujlqnhnrfunq