Scene perception and spatial navigation are interdependent cognitive functions, and there is increasing evidence that cortical areas that process perceptual scene properties also carry information about the potential for navigation in the environment (navigational affordances). However, the temporal stages by which visual information is transformed into navigationally relevant information are not yet known. We hypothesized that navigational affordances are encoded during perceptual processing and therefore should modulate early visually evoked ERPs, especially the scene-selective P2 component. To test this idea, we recorded ERPs from participants while they passively viewed computer-generated room scenes matched in visual complexity. By simply changing the number of doors (0 doors, 1 door, 2 doors, 3 doors), we were able to systematically vary the number of pathways that afford movement in the local environment, while keeping the overall size and shape of the environment constant. We found that rooms with 0 doors evoked a higher P2 response than rooms with three doors, consistent with prior research reporting higher P2 amplitude to closed relative to open scenes. Moreover, we found P2 amplitude scaled linearly with the number of doors in the scenes. Navigability effects on the ERP waveform were also observed in a multivariate analysis, which showed significant decoding of the number of doors and their location at earlier time windows. Together, our results suggest that navigational affordances are represented in the early stages of scene perception. This complements research showing that the occipital place area automatically encodes the structure of navigable space and strengthens the link between scene perception and navigation.

People are often considered cognitive misers. When given a free choice between two tasks, people tend to choose tasks requiring less cognitive effort. Such demand avoidance (DA) is associated with cognitive control, but it is still not clear to what extent individual differences in cognitive control can account for variations in DA. We sought to elucidate the relation between cognitive control and cognitive effort preferences by investigating the extent to which sustained neural activity in a task requiring cognitive control is correlated with DA. We hypothesized that neural measures of efficient filtering will predict individual variations in demand preferences. To test this hypothesis, we had participants perform a delayed-match-to-sample paradigm with their ERPs recorded, as well as a separate behavioral demand-selection task. We focused on the ERP correlates of cognitive filtering efficiency (CFE)—the ability to ignore task-irrelevant distractors during working memory maintenance—as it manifests in a modulation of the contralateral delay activity, an ERP correlate of cognitive control. As predicted, we found a significant positive correlation between CFE and DA. Individuals with high CFE tended to be significantly more demand avoidant than their low-CFE counterparts. Low-CFE individuals, in comparison, did not form distinct cognitive effort preferences. Overall, our results suggest that cognitive control over the contents of visual working memory contribute to individual differences in the expression of cognitive effort preferences. This further implies that these observed preferences are the product of sensitivity to cognitive task demands.