Exploring and integrating discrete and dimensional approaches while inducing negative emotional states

Abstract

Selecting visual stimuli for inducing specific emotional states is very challenging, since the choice relies on specific conceptualization of emotions. In this work, we present a set of 55 stimuli, realized integrating discrete and dimensional theories of emotions, and specifically selected to investigate anger, fear, and disgust reactions in non-clinical and clinical contexts. Our set of stimuli presents several aspects of novelty since (1) a large and heterogeneous sample of subjects from the general population was involved in the labelling task, and (2) bivariate and multivariate statistical techniques were applied to integrate emotion models. The proposed set of stimuli could be useful for researchers and other professionals in the affective sciences to address negative emotion recognition issues within a broader perspective both in general population and in psychiatric samples. The obtained comprehensive characterization of the stimuli allowed us to confirm the sexual dimorphism in emotional processing.

Keywords:

• Affective visual stimuli and ratings
• dimensional model
• discrete emotion theory
• emotion elicitation
• integrating models of emotions

Acknowledgments

We wish to thank Eng. Lorenzo Cibrario, from administrative system of Vita-Salute San Raffaele University, which technically and practically supported us in the realization of the online questionnaire.

Disclosure statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Author contributions

RMM designed data collection, contributed to interpret results, reviewing current literature in affective neuroscience. RDF reviewed the current literature on affective picture databases, contributed to interpret results. CB and PMVR designed and monitored data collection, analyzed the data and drafted the paper. CDS supervised statistical analyses and critically revised the draft paper. All authors read and approved the final manuscript.

Additional information

Funding

This work was supported by the Italian Ministry for Education, University and Research (MIUR) under the FIRB (“Futuro in ricerca”) project entitled “Interpreting emotions: a computational tool integrating facial expressions and biosignals based on shape analysis and bayesian networks”, grant no. RBFR12VHR7.