Cognitive capacity is commonly assumed to predict performance in classic reasoning tasks because people higher in cognitive capacity are believed to be better at deliberately correcting biasing erroneous intuitions. However, recent findings suggest that there can also be a positive correlation between cognitive capacity and correct intuitive thinking. Here we present results from 2 studies that directly contrasted whether cognitive capacity is more predictive of having correct intuitions or successful deliberate correction of an incorrect intuition. We used a two-response paradigm in which people were required to give a fast intuitive response under time pressure and cognitive load and afterwards were given the time to deliberate. We used a direction-of-change analysis to check whether correct responses were generated intuitively or whether they resulted from deliberate correction (i.e., an initial incorrect-to-correct final response change). Results showed that although cognitive capacity was associated with the correction tendency (overall r = .13) it primarily predicted correct intuitive responding (overall r = .42). These findings force us to rethink the nature of sound reasoning and the role of cognitive capacity in reasoning. Rather than being good at deliberately correcting erroneous intuitions, smart reasoners simply seem to have more accurate intuitions.

Prospective memory (PM) refers to our ability to realize delayed intentions. In event-based PM paradigms, participants must act on an intention when they detect the occurrence of a pre-established cue. Some theorists propose that in such paradigms PM responding can only occur when participants deliberately initiate processes for monitoring their environment for appropriate cues. Others propose that perceptual processing of PM cues can directly trigger PM responding in the absence of strategic monitoring, at least under some circumstances. In order to address this debate, we present a computational model implementing the latter account, using a parallel distributed processing (interactive activation) framework. In this model PM responses can be triggered directly as a result of spreading activation from units representing perceptual inputs. PM responding can also be promoted by top-down monitoring for PM targets. The model fits a wide variety of empirical findings from PM paradigms, including the effect of maintaining PM intentions on ongoing response time and the intention superiority effect. The model also makes novel predictions concerning the effect of stimulus degradation on PM performance, the shape of response time distributions on ongoing and prospective memory trials, and the effects of instructing participants to make PM responses instead of ongoing responses or alongside them. These predictions were confirmed in two empirical experiments. We therefore suggest that PM should be considered to result from the interplay between bottom-up triggering of PM responses by perceptual input, and top-down monitoring for appropriate cues. We also show how the model can be extended to simulate encoding new intentions and subsequently deactivating them, and consider links between the model’s performance and results from neuroimaging.

No abstract