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. 2013 Aug 21;4:541.
doi: 10.3389/fpsyg.2013.00541. eCollection 2013.

Pleasurable Music Affects Reinforcement Learning According to the Listener

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Free PMC article

Pleasurable Music Affects Reinforcement Learning According to the Listener

Benjamin P Gold et al. Front Psychol. .
Free PMC article

Abstract

Mounting evidence links the enjoyment of music to brain areas implicated in emotion and the dopaminergic reward system. In particular, dopamine release in the ventral striatum seems to play a major role in the rewarding aspect of music listening. Striatal dopamine also influences reinforcement learning, such that subjects with greater dopamine efficacy learn better to approach rewards while those with lesser dopamine efficacy learn better to avoid punishments. In this study, we explored the practical implications of musical pleasure through its ability to facilitate reinforcement learning via non-pharmacological dopamine elicitation. Subjects from a wide variety of musical backgrounds chose a pleasurable and a neutral piece of music from an experimenter-compiled database, and then listened to one or both of these pieces (according to pseudo-random group assignment) as they performed a reinforcement learning task dependent on dopamine transmission. We assessed musical backgrounds as well as typical listening patterns with the new Helsinki Inventory of Music and Affective Behaviors (HIMAB), and separately investigated behavior for the training and test phases of the learning task. Subjects with more musical experience trained better with neutral music and tested better with pleasurable music, while those with less musical experience exhibited the opposite effect. HIMAB results regarding listening behaviors and subjective music ratings indicate that these effects arose from different listening styles: namely, more affective listening in non-musicians and more analytical listening in musicians. In conclusion, musical pleasure was able to influence task performance, and the shape of this effect depended on group and individual factors. These findings have implications in affective neuroscience, neuroaesthetics, learning, and music therapy.

Keywords: dopamine; listening strategy; music; musical experience; pleasure; reinforcement learning; reward; subjectivity.

Figures

Figure 1
Figure 1
Reinforcement learning model. In the reinforcement learning model (from Frank et al., 2004), phasic increases in dopamine promote action selection in the thalamus via the D1-receptor “Go” pathway, whereas phasic decreases promote action avoidance via the D2-receptor “NoGo” pathway. Both processes originate in the striatum and receive cortical and subcortical inputs. SNc, substantia nigra pars compacta; GPi, internal segment of the globus pallidus; GPe, external segment of the globus pallidus; SNr, substantia nigra pars reticula.
Figure 2
Figure 2
Probabilistic selection (PS) task. (A) Each trial in the PS task began with a jittered fixation cross followed by a pair of stimuli for 2500 ms. Following a left or right button response, the selected image appeared highlighted on the screen for the duration of the 2500 ms presentation. Choices during training then received probabilistic feedback, whereas those during testing were followed by the fixation cross marking the next trial. (B) In the training phase, participants learned to choose between three discrete pairs of Japanese Hiragana characters with different reward contingencies. Each pair had a better and worse choice, but the relative weights of these values changed. The reward probabilities of each stimulus are shown in parentheses. (C) In the test phase, participants generalized their knowledge of the training pairs to recombined stimulus pairs. There was no feedback in this phase. Learning to choose A over B during training could reflect approach learning, avoidance learning, or both, and so we assessed overall test performance as well as the accuracy of (A) choices and (B) avoidances when these stimuli appeared in novel pairs during testing.
Figure 3
Figure 3
Probabilistic selection task performance summary. Box plots with quartiles (upper values 75%, medians 50%, and lower values 25%). The whiskers show the range of the data, with no outliers. (A) Overall accuracy in training and testing for all subjects. (B) Overall reaction times in training and testing for all subjects.
Figure 4
Figure 4
Test Condition by Group interaction on test accuracy. There was a significant Test Condition by Group interaction (p < 0.05). Subjects did not differ in approach (Choose A) accuracy during the test, but subjects who listened to neutral music during both training and testing (NN) avoided B less accurately than those who listened to neutral music during training and pleasurable music during testing (NP; adjusted p < 0.005) and those who listened to pleasurable music during training and neutral music during testing (NP; adjusted p < 0.05). Bars depict the mean accuracy for each Group in Choose A and Avoid B conditions, plus or minus the standard error of the mean. PP, subjects who listened to pleasurable music during both training and testing. *p < 0.05; **p < 0.005.
Figure 5
Figure 5
Playing Years by Musical Condition interaction on training accuracy. There was a significant Playing Years by Musical Condition interaction on training accuracy (p < 0.001). Subjects with more years of musical experience were significantly more accurate when they listened to neutral music (p < 0.05), and there was a trend effect of more musically experienced subjects performing less accurately with pleasurable music (p = 0.07). +p < 0.10; *p < 0.05.
Figure 6
Figure 6
Playing Years by Musical Condition interaction on training reaction times. There was a significant Playing Years by Musical Condition interaction on training reaction times (p < 0.0001). Within neutral music listening, more musically experienced subjects exhibited faster reaction times (p < 0.0001). There was no significant correlation within pleasurable music listening (p > 0.95). N.S., not significant; ****: p < 0.0001.
Figure 7
Figure 7
Weekly Listening Hours by Group interaction on test reaction times. There was a significant Weekly Listening Hours by Group interaction on test reaction times (p < 0.0001). Subjects who listened to music more frequently responded faster when they trained with neutral music and tested with pleasurable music (NP; p < 0.01). There was also a trend correlation such that these subjects responded slower when they listened to neutral music during both training and testing (NN, p = 0.08). No other within-group correlations were significant (all ps > 0.37). PN: subjects who listened to pleasurable music during training and neutral music during testing; PP: subjects who listened to pleasurable music during both training and testing. N.S., not significant; +p < 0.10; **p < 0.01.
Figure 8
Figure 8
Covariate relationships on training and test accuracy and reaction times. Factors from the Helsinki Inventory of Music and Affective Behaviors (HIMAB) and the listening test significantly covaried with probabilistic selection task performance. (A) Training accuracy. (B) Training reaction times. (C) Test accuracy. (D) Test reaction times. Numerical values show the slopes of the covariations, and colors represent the directions and significance levels of the effects.
Figure 9
Figure 9
Multiple regression correlations on training and test accuracy and reaction times. Multiple linear regressions revealed many individual factors significantly correlated to probabilistic selection task performance. (A) Training accuracy. (B) Training reaction times. (C) Test accuracy. (D) Test reaction times. Numerical values show the slopes of the regressions, and colors represent the directions and significance levels of the effects.

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