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1. The representational glue for incidental category learning is alignment with task-relevant behavior

   Roark, C. L.; Lehet, M.; Dick, F.; Holt, L. L. (January 2021, Journal of experimental psychology)

   null (Ed.)

   Category learning is fundamental to cognition, but little is known about how it proceeds in real-world environments when learners do not have instructions to search for category-relevant information, do not make overt category decisions, and do not experience direct feedback. Prior research demonstrates that listeners can acquire task-irrelevant auditory categories incidentally as they engage in primarily visuomotor tasks. The current study examines the factors that support this incidental category learning. Three experiments systematically manipulated the relationship of four novel auditory categories with a consistent visual feature (color or location) that informed a simple behavioral keypress response regarding the visual feature. In both an in-person experiment and two online replications with extensions, incidental auditory category learning occurred reliably when category exemplars consistently aligned with visuomotor demands of the primary task, but not when they were misaligned. The presence of an additional irrelevant visual feature that was uncorrelated with the primary task demands neither enhanced nor harmed incidental learning. By contrast, incidental learning did not occur when auditory categories were aligned consistently with one visual feature, but the motor response in the primary task was aligned with another, category-unaligned visual feature. Moreover, category learning did not reliably occur across passive observation or when participants made a category-nonspecific, generic motor response. These findings show that incidental learning of categories is strongly mediated by the character of coincident behavior. 

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2. On the biological basis of beauty

   https://doi.org/10.1111/brv.70014  

   Mendelson, Tamra_C; Renoult, Julien_P; Rosenthal, Gil_G; Shuker, David_M (April 2025, Biological Reviews)

   ABSTRACT The world around us is full of beauty. Explaining a sense of the beautiful has beguiled philosophers and artists for millennia, but scientists have also pondered beauty, most notably Darwin, who used beauty to describe sexual ornaments that he argued were the subject of female mate choice. In doing so, he ascribed a ‘sense of the beautiful’ to non‐human animals. Darwin's ideas about mate choice and beauty were not widely accepted, however. Humans may experience beauty, but assuming the same about other animals risks anthropomorphism: we might find the tail of the peacock to be beautiful, but there is no reason to believe that peahens do. Moreover, mate choice, resurrected as an object of serious study in the 1970s, simply requires attraction, not necessarily beauty. However, recent advances in psychology and cognitive neuroscience are providing a new, mechanistic framework for beauty. Here we take these findings and apply them to evolutionary biology. First, we review progress in human empirical aesthetics to provide a biological definition of beauty. Central to this definition is the discovery that merely processing information can provide hedonic reward. As such, we propose thatbeauty is the pleasure of fluent information processing, independent of the function or consummatory reward provided by the stimulus. We develop this definition in the context of three key attributes of beauty (pleasure, interaction, and disinterestedness) and the psychological distinction between ‘wanting’ and ‘liking’. Second, we show how beauty provides a new, proximate approach for studying the evolution of sexual signalling that can help us resolve some key problems, such as how mating biases evolve. We also situate beauty within a more general framework for the evolution of animal signals, suggesting that beauty may apply not only to sexual ornaments, but also to traits as diverse as aposematic signals and camouflage. Third, we outline a variety of experimental approaches to test whether animal signals are beautiful to their intended receivers, including tests of fluency and hedonic impact using behavioural and neurological approaches. 

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3. Sparsity in an artificial neural network predicts beauty: Towards a model of processing-based aesthetics

   https://doi.org/10.1371/journal.pcbi.1011703  

   Dibot, Nicolas M; Tieo, Sonia; Mendelson, Tamra C; Puech, William; Renoult, Julien P (December 2023, PLOS Computational Biology)

   Fleming, Roland W (Ed.)

   Generations of scientists have pursued the goal of defining beauty. While early scientists initially focused on objective criteria of beauty (‘feature-based aesthetics’), philosophers and artists alike have since proposed that beauty arises from the interaction between the object and the individual who perceives it. The aesthetic theory of fluency formalizes this idea of interaction by proposing that beauty is determined by the efficiency of information processing in the perceiver’s brain (‘processing-based aesthetics’), and that efficient processing induces a positive aesthetic experience. The theory is supported by numerous psychological results, however, to date there is no quantitative predictive model to test it on a large scale. In this work, we propose to leverage the capacity of deep convolutional neural networks (DCNN) to model the processing of information in the brain by studying the link between beauty and neuronal sparsity, a measure of information processing efficiency. Whether analyzing pictures of faces, figurative or abstract art paintings, neuronal sparsity explains up to 28% of variance in beauty scores, and up to 47% when combined with a feature-based metric. However, we also found that sparsity is either positively or negatively correlated with beauty across the multiple layers of the DCNN. Our quantitative model stresses the importance of considering how information is processed, in addition to the content of that information, when predicting beauty, but also suggests an unexpectedly complex relationship between fluency and beauty. 

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4. Mind Melds: Verbal Labels Induce Greater Representational Alignment

   https://doi.org/10.1162/opmi_a_00153  

   Suffill, Ellise; van_Paridon, Jeroen; Lupyan, Gary (January 2024, Open Mind)

   What determines whether two people represent something in a similar way? We examined the role of verbal labels in promoting representational alignment. Across two experiments, three groups of participants sorted novel shapes from two visually dissimilar categories. Prior to sorting, participants in two of the groups were pre-exposed to the shapes using a simple visual matching task designed to reinforce the visual category structure. In one of these groups, participants additionally heard one of two nonsense category labels accompanying the shapes. Exposure to these redundant labels led people to represent the shapes in a more categorical way, which led to greater alignment between sorters. We found this effect of label-induced alignment despite the two categories being highly visually distinct and despite participants in both pre-exposure conditions receiving identical visual experience with the shapes. Experiment 2 replicated this basic result using more even more stringent testing conditions. The results hint at the possibly extensive role that labels may play in aligning people’s mental representations. 

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5. Nameability predicts subjective and objective measures of visual similarity

   Zettersten, M.; Suffill, E.; Lupyan, G. (January 2020, Proceedings of the 42nd Annual Virtual Meeting of the Cognitive Science Society)

   Denison, S.; Mack, M.; Xu, Y.; Armstrong, B.C. (Ed.)

   Do people perceive shapes to be similar based purely on their physical features? Or is visual similarity influenced by top-down knowledge? In the present studies, we demonstrate that top-down information – in the form of verbal labels that people associate with visual stimuli – predicts visual similarity as measured using subjective (Experiment 1) and objective (Experiment 2) tasks. In Experiment 1, shapes that were previously calibrated to be (putatively) perceptually equidistant were more likely to be grouped together if they shared a name. In Experiment 2, more nameable shapes were easier for participants to discriminate from other images, again controlling for their perceptual distance. We discuss what these results mean for constructing visual stimuli spaces that are perceptually uniform and discuss theoretical implications of the fact that perceptual similarity is sensitive to top-down information such as the ease with which an object can be named. 

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