We use a connectionist model which relies on the encoding of lempnjral relationships a m o n g events to investigate the role of causal mechanisms in causal attribution. Mechanisms are encoded as intervening events with temporal extent that occur between the offset of a causal event and the onset of an effect. In one set of simulations, the presence of intervening events facilitated acquisition of a relationship between cause and effect via the mechanism. In a second set of simulations, prior experience with mechanisms enhanced development of a cause-effect relationship during later training absent the mechanism. The results provide evidence that causal mechanisms can facilitate causal attribution via H u m e a n cues-to-causality.