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Dynamic Bayesian Networks are widely used for modeling neural information flow and gene regulatory networks. Their assumption of first-order Markov, however, is recently being noted as a too restrictive assumption for some applications, specially when these have communication and processing of information at different time delays. Many authors are extending this Markov assumption to higher orders,...