Catherine Landry¹, Jasper JF van den Bosch², Vincent Taschereau-Dumouchel^3,4, Frédéric Gosselin¹, Ian Charest¹; ¹Cerebrum, Université de Montréal, CA, ²School of Psychology, University of Leeds, UK, ³Département de psychiatrie et d'addictologie, Université de Montréal, CA, ⁴Centre de recherche de l’Institut Universitaire en Santé Mentale de Montréal, CA

What makes an image easy to imagine? Previous research on mental imagery mostly used very limited samples, which prevented establishing a direct association between image characteristics and vividness ratings (i.e., the clarity and detail level of imagined images). Here, we present a large-scale database of vividness judgments associated with the natural scenes from the Natural Scenes Dataset (NSD; Allen et al., 2021), which consists of 73,000 annotated natural images. During each trial, participants sequentially view two NSD images and are then randomly asked to imagine one or the other (i.e., retro-cued target image) for 4 s. Participants then rate the vividness of their mental image (on a continuous scale from 0 to 100), followed by a test to ensure that they imagined the correct target. Participants (n = 1825), recruited from Prolific, are directed to the Meadows platform for online experiments. Each complete 120 trials of our vividness task, for a total of 219,000 vividness ratings across participants. They also complete the Vividness of Visual Imagery Questionnaire (Marks, 1973) to measure their visual imagery ability. Overall, preliminary data reveals excellent performance on the task (average accuracy of 95.83% correct target identification), as well as substantial interimage (M = 0.65 ± 0.25) and interindividual (M = 0.66 ± 0.17) variability in average vividness scores. This large-scale dataset of vividness ratings will offer invaluable insights into visual imagery by allowing to train predictive models of subjective imagery experiences. It will enable a deeper understanding of the visual and cognitive factors influencing mental image vividness, and serve as a guiding resource for future experiments. Furthermore, integrating these vividness judgments with neural data from the NSD will allow for an exploration of the relationship between subjective experience and objective brain responses.