Numerous studies have demonstrated that mood can af- fect emotional processing. The goal of this study was to explore which components of the decision process are af- fected when exposed to music; we do so within the context of a stochastic sequential model of simple decisions, the drift-diffusion model (DDM). In our experiment, partici- pants decided whether words were emotionally positive or negative while listening to music that was chosen to in- duce positive or negative mood. The behavioral results show that the music manipulation was effective, as par- ticipants were biased to label words positive in the positive music condition. The DDM shows that this bias was driven by a change in the starting point of evidence accumula- tion, which indicates an a priori response bias. In contrast, there was no evidence that music affected how participants evaluated the emotional content of the stimuli. To better understand the correspondence between auditory features and decision-making, we proceeded to study how individ- ual aspects of music affect response patterns. Our results have implications for future studies of the connection be- tween music and mood.

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In 16th International Society for Music Information Retrieval Conference (ISMIR), Malaga, Spain, October 2015.

@inproceedings{ismir2015-eladlieb, title={How Music Alters Decision Making: Impact of Music Stimuli on Emotional Classification}, author={Elad Liebman and Peter Stone and Corey N. White}, booktitle={16th International Society for Music Information Retrieval Conference (ISMIR)}, month={October}, address={Malaga, Spain}, url="http://www.cs.utexas.edu/users/ai-lab?liebman:ismir15", year={2015} }

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