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The concept of emotion is a complex neural and psychological phenomenon, central to the organization of human social behavior. As the result of subjective experience, emotions involve bottom-up cognitive styles responsible for efficient adaptation of human behavior to the environment based on salient goals. Indeed, bottom-up cognitive processes are mandatory for clarifying emotion-cognition interactions. Accordingly, a huge number of studies and standardized affective stimuli databases have been developed (i.e., International Affective Picture System (IAPS), Geneva Affective Picture Database (GAPED), and Nencki Affective Picture System (NAPS)). However, these neither accurately reflect the complex neural system underlying emotional responses nor do they offer a comprehensive framework for researchers. The present article aims to provide an additional bottom-up validation of affective stimuli that are independent from cognitive processing and control mechanisms, related to the implicit relevance and evolutionistic significance of stimuli. A subset of 360 images from the original NAPS, GAPED, and IAPS datasets was selected in order to proportionally cover the whole dimensional affective space. Among these, using a two-step analysis strategy, we identified three clusters (“good performance”, “poor performance”, and “false alarm”) of stimuli with similar cognitive response profiles. Results showed that the three clusters differed in terms of arousal and database membership, but not in terms of valence. The new database, with accompanying ratings and image parameters, allows researchers to select visual stimuli independent from dimensional/discrete-categories, and provides information on the implicit effects triggered by such stimuli.

A Bottom-Up Validation of the IAPS, GAPED, and NAPS Affective Picture Databases: Differential Effects on Behavioral Performance