The paper reports recent results from the theory of Bayesian networks, which offer a viable formalizsm for realizing the computational objectives of connectionist models of knowledge. In particular, we show that the Bayseian network formalism is supportive of self-activated, multidirectional proagation of evidence that converges rapidly to a globally-consistent equilibrium.