In experimental settings, characteristics of presented stimuli influence cognitive processes. Knowledge about stimulus features is important to manipulate or control the influence of stimuli. To date, there are a lack of standardized data incorporating such information for complex abstract stimuli. Thus, we provide norms for a database of 400 abstract and complex stimuli. Grey-scaled fractals were rated by 512 participants on the stimulus features of abstractness, animacy, verbalizability, complexity, familiarity, favorableness, and memorability. Moreover, 111 participants labeled the fractals, enabling us to calculate indices of naming agreement and modal names. Overall, the results confirmed high abstractness and low verbalizability of the provided stimuli. To establish external validation for selected stimulus features, we evaluated (a) classifier probability of a deep neural network labeling the fractals, negatively correlated with ratings of abstractness and positively with verbalizability and naming agreement; (b) data compression rate of fractal image files, positively correlated with the rating of complexity; and (c) performance of 212 participants in a recognition-memory task, positively correlated with the rating of memorability. The present work fills the gap of a standardized database for abstract stimuli and provides a database with valid norms for abstract and complex stimuli based on ratings and external validation measures. This database can be used to control and manipulate these stimulus features in experimental settings using abstract stimuli. Such a database is essential in experimental research using abstract stimuli for instance to control for verbal influence and strategy or to control for novelty and familiarity.
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