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Humans can recognize their whole-body movements even when displayed as dynamic dot patterns. The sparse depiction of whole-body movements, coupled with a lack of visual experience watching ourselves in the world, has long implicated nonvisual mechanisms to self-action recognition. Using general linear modeling and multivariate analyses on human brain imaging data from male and female participants, we aimed to identify the neural systems for this ability. First, we found that cortical areas linked to motor processes, including frontoparietal and primary somatomotor cortices, exhibit greater engagement and functional connectivity when recognizing self-generated versus other-generated actions. Next, we show that these regions encode self-identity based on motor familiarity, even after regressing out idiosyncratic visual cues using multiple regression representational similarity analysis. Last, we found the reverse pattern for unfamiliar individuals: encoding localized to occipitotemporal visual regions. These findings suggest that self-awareness from actions emerges from the interplay of motor and visual processes. 

Human judgments of similarity and difference are sometimes asymmetrical, with the former being more sensitive than the latter to relational overlap, but the theoretical basis for this asymmetry remains unclear. We test an explanation based on the type of information used to make these judgments (relations versus features) and the comparison process itself (similarity versus difference). We propose that asymmetries arise from two aspects of cognitive complexity that impact judgments of similarity and difference: processing relations between entities is more cognitively demanding than processing features of individual entities, and comparisons assessing difference are more cognitively complex than those assessing similarity. In Experiment 1 we tested this hypothesis for both verbal comparisons between word pairs, and visual comparisons between sets of geometric shapes. Participants were asked to select one of two options that was either more similar to or more different from a standard. On unambiguous trials, one option was unambiguously more similar to the standard; on ambiguous trials, one option was more featurally similar to the standard, whereas the other was more relationally similar. Given the higher cognitive complexity of processing relations and of assessing difference, we predicted that detecting relational difference would be particularly demanding. We found that participants (1) had more difficulty detecting relational difference than they did relational similarity on unambiguous trials, and (2) tended to emphasize relational information more when judging similarity than when judging difference on ambiguous trials. The latter finding was replicated using more complex story stimuli (Experiment 2). We showed that this pattern can be captured by a computational model of comparison that weights relational information more heavily for similarity than for difference judgments. 

Creativity is typically defined as the generation of novel and useful ideas or artifacts. This generative capacity is crucial to everyday problem solving, technological innovation, scientific discovery, and the arts. A central concern of cognitive scientists is to understand the processes that underlie human creative thinking. We review evidence that one process contributing to human creativity is the ability to generate novel representations of unfamiliar situations by completing a partially-specified relation or an analogy. In particular, cognitive tasks that trigger generation of relational similarities between dissimilar situations—distant analogies—foster a kind of creative mindset. We discuss possible computational mechanisms that might enable relation-driven generation, and hence may contribute to human creativity, and conclude with suggested directions for future research.