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Normative measures of verbal material are fundamental in psycholinguistic and cognitive research for the control of confounding in experimental procedures and for achieving a better comprehension of our conceptual system. Traditionally, normative studies have focused on classical psycholinguistic variables, such as concreteness and imageability. Recent works have shifted researchers' focus to perceptual strength, in which items are rated separately for each of the five senses. We present a resource that includes perceptual norms for 1,121 Italian words extracted from the Italian version of ANEW. Norms were collected from 57 native speakers. For each word, the participants provided perceptual-strength ratings for each of the five perceptual modalities. The perceptual norms performance in predicting human behavior was tested in two novel experiments, a lexical decision task and a naming task. Concreteness, imageability, and different composite variables representing perceptual-strength scores were considered as competing predictors in a series of linear regressions, evaluating the goodness of fit of each model. For both tasks, the model with imageability as the only predictor was found to be the best-fitting model according to the Akaike information criterion, whereas the model with the separately considered five modalities better described data according to the explained variance. These results differ from the ones previously reported for English, in which maximum perceptual strength emerged as the best predictor of behavior. We investigated this discrepancy by comparing Italian and English data for the same set of translated items, thus confirming a genuine cross-linguistic effect. We thus confirmed that perceptual experience influences linguistic processing, even though evaluations from different languages are needed to generalize this claim.

behavior research methods

Perceptual modality norms for 1,121 Italian words: A comparison with concreteness and imageability scores and an analysis of their impact in word processing tasks