Exploring the Role of Micro-Valence in Conscious Perception: Insights from Similarity Judgments and Deep Learning Models

Is valence an intrinsic dimension of conscious experience, as different authors (Barrett & Bar, 2009, Cleeremans & Tallon-Baudry, 2022, Jacobson, 2021) have suggested? If so, all conscious perceptions should be valenced, even if only minimally so, and similarity judgements should be at least partly driven by one’s affective dispositions. Here, we leverage the concept of micro-valence, which claims that even a priori neutral objects elicit some affective reactions (Lebrecht, 2012) and explore the extent to which valence judgments correlate with similarity judgments and with the different stages of processing in deep neural networks (DNNs). One hundred forty-nine participants provided both similarity and valence judgments for 120 images of everyday objects, using an odd-one-out task (Study 1), a spatial arrangement task (Study 2), and the birthday task (Lebrecht et al., 2012), which asks people to choose an object they would like to keep (or give away) as their birthday gift. We also extracted activations from the layers of DNNs trained to classify objects in response to the same images. Representation similarity analysis and multidimensional scaling analyses highlight the role of micro-valence in the similarity space, suggesting that valence permeates similarity judgments. DNN analysis showed that this valence-similarity relationship was not entirely mediated by stimulus perceptual features captured by the different DNN layers. Surprisingly, micro-valence correlated with activations in the early DNN layers, suggesting that low-level visual features play a role in the computation of valence. Our results suggest that valence computation occurs in early visual processing, and that valence is indeed involved in similarity judgments.