The Mozart Effect Rediscovered

The so-called "Mozart effect" refers to an enhancement in performance associated with listening to Mozart’s music (K.448). The effect has been reported for spatial intelligence tasks (Rauscher et al. 1993). College students who had spent 10 minutes listening to Mozart’s Sonata K.448 scored 8-9 points higher on a Stanford-Binet spatial subtest (Paper Folding and Cutting – PF&C) than students who had listened to a relaxation tape or to nothing. The positive effects did not persist beyond the 10-15 min testing session. This finding at the end of the last century provoked a Mozart research mania. It was not only the intriguing explanation of the effect provided by Rauscher that sparked this research boom, but also several situational circumstances that could be summarized into a Zeitgeist category. The most important sociocultural components of this large scale phenomenon – which found particular resonance in late 20th century in the US –  were among others: (i) The statement made by George Bush in 1990, proclaiming it the ‘Decade of the Brain’ - budding the fascination for neuroscience and (ii) the interest in gifted education and the appealing possibility of influencing behavior, brain structure and activity in an effortless way, just by listening to music (Beauvais, 2015).

This brings us back to the explanation of the effect provided by Rauscher (Rauscher et al., 1995). It was proposed that the complexly structured music of the Mozart sonata in tempo, melody, organization, and predictability improves spatial-task performance. The link is subserved by similarities in neural activation between music listening and spatial reasoning, as specified by the Trion model of cortical organization (Shenoy et al., 1993).  Music primes cortical firing patterns similar to those involved in spatial reasoning, which improves subjects’ PF&C task performance (see figure below).

In contrast, Nantais and Schellenberg (1999) explained the Mozart effect as an artifact of preference, mood, and arousal. Listening to music affects arousal (degree of physiological activation), mood (long lasting emotions), and listeners’ enjoyment which in turn influence performance on a variety of cognitive tasks - an interpretation that has prevailed to the present day (Schellenberg and Weiss, 2013).

The Trion model of cortical organization was also criticized. As stressed by Schellenberg and Weiss, (2013), the Trion model is just an ad hoc construct created to support the priming explanation of the Mozart effect and should first be verified in neuropsychology or neuroscience before used in explanations. I must agree with this idea. Contrary to the Mozart effect, which is still an important part of music research with promising findings supporting the priming hypothesis, interest for the Trion model has considerably decreased. The most recent publication that involves the term "trion" (based on a Thomson Reuters Web of Science search) is a study by Sardesay et al. (2001) with Gordon Shaw as a coauthor, who is a member of Rauscher’s research group at Irwin. The Trion model coupled with Hebbs columnar structure of short-term memory was suggested as evidence for innate cortical language and grammar. In my opinion a theoretically more sound approach to decipher the neural code is graph theory (see the neural code of intelligence or this paper)

Research from our lab updated by recent neurobiological findings

The fascination with the Mozart effect eventually spread to Europe and to our lab. It coincided with my mentorship to Katarina Habe, a PhD student who is also a well-known Slovene singer in the female trio “The Katrinas" . Hence, the Mozart effect was a suitable and for her an enjoyable topic of research.

The objective of our first study was to investigate differences in brain activity of respondents who listened to three sound clips which differed in the complexity of their music structure, the mood they induced in listeners, musical tempo, and prominent frequency (Jaušovec and Habe, 2003). They were taken from Mozart’s sonata (K. 448) and Brahms’ Hungarian dance (no. 5). The third clip was a simplified version of the theme taken from Haydn’s symphony (no. 94) played by a computer synthesizer. In that way an attempt was made to test the conflicting explanations of the Mozart effect.

The obtained results were rather clear-cut. The clustering of the three clips based on EEG measures distinguished between the Mozart clip on the one hand, and the Haydn and Brahms clips on the other, even though the Haydn and Brahms clips were at the opposite extremes with regard to the mood they induced in listeners, musical tempo, and complexity of structure. This would suggest that other distinctive aspects of the Mozart sonata may have had a key influence on the observed brain activity. Such a characteristic could be related to modulations in the frequency domain. In our study the prominent frequency of the Mozart clip was much higher than the prominent frequency of the other two clips. A similar finding was reported by Hughes and Fino (2000). Their analysis of 402 music selections of 59 composers indicated that frequency played a key role in separating Mozart’s music from the music of other composers.

Additional support for a frequency-related explanation of the Mozart effect was provided by recent studies. For instance, Nozaradan (2014) suggested that entrainment and resonance phenomena may play a crucial role in processing musical rhythms in the human brain.  In the same direction points research by Verrusio et al. (2015), who compared EEG patterns while individuals listened to Mozart’s sonata or Beethoven’s Für Elise. Only while listening to Mozart’s sonata K.448 an increase in alpha band activity and the median frequency index – linked to memory and cognition – was observed. The authors concluded that Mozart’s music “is able to activate neuronal cortical circuits related to attentive and cognitive functions not only in young subjects, but also in the healthy elderly individuals” (Verrusio et al., 2015, p. 154). Furthermore it was found that the crucial distinctive feature of Mozart’s music is the frequent repetition of the melodic line with a lack of surprise elements that could distract the listener’s attention.

Recently the focus of explanations for the Mozart effect has moved from purely theoretical speculations (e.g., the Trion model) to neurobiological markers related to the acquisition and consolidation of memory, such as brain-derived neurotrophic factor (BDNF) and its receptor, tyrosine kinase receptor B (TrkB) (e.g., Pecci et al., 2016; Xing et al., 2016). Especially the study by Xing provided insight into the possible relationship between learning and specific characteristics of Mozart’s sonata. Human subjects and rats were exposed to different listening conditions: the original Mozart sonata, the same sonata played backward (retrograde), and versions in which pitch and rhythm were manipulated. In summary, it was demonstrated that only listening to Mozart’s Sonata K.448 induced positive cognitive effects in humans and rats, which were accompanied by changes in BDNF and its receptor TrkB. Furthermore, the rhythm and pitch manipulations of the normal and retrograde Mozart music indicated that rhythm was the crucial element in producing the behavioral effects. These findings are similar to those reported in our study and by Verrusio et al. (2015).

Xing et al. (2016) also provided the most up to date review of studies investigating the Mozart effect. Out of 67 studies, 52 (78%) supported the existence of the positive effect on cognition. It is worth mentioning that an analysis of the influence background music has on cognitive performance showed its dependence on several factors related to individual differences in personality, music training, music preferences, study habits, but also to situational variables, such as the type of cognitive tasks, the context, and the choice of background music in terms of its mood or pleasantness (Schellenberg and Weiss, 2013). Moreover, the observed inconsistency of the effects could be related to listeners’ genetic structure as shown in a recent fMRI study by Quarto et al. (2017) investigating the functional polymorphism of the dopamine D2 receptor gene. It was observed that the effects of sound (music and noise) on mood state and brain activity (prefrontal and striatal brain areas) during emotion processing are modulated by DRD2 genetic variation differentiating between GG and GT genotypes. Mood improvement after music exposure (just trend for noise) accompanied by decreased prefrontal brain activity was only observed for GG subjects. On the other hand, in GT subjects an opposite pattern with decreased striatal brain activity was observed in the noise listening condition (just trend for music).

Listening to Mozart’s sonata K.448 can also have a positive effect on learning, which was shown in another study carried out in our lab (Jaušovec et al., 2006). We conducted two experiments. In the first one students were randomly assigned to 4 groups: a control group (CG), in which the students relaxed prior to and after training, and three experimental groups; MM – who prior to and after training listened to music; MS – who prior to training listened to music and subsequently relaxed; and SM – who prior to training relaxed and afterwards listened to music. The music used was the first movement of Mozart’s Sonata K. 448. In the second experiment, the respondents were assigned into three groups: CG, MM (same procedure as in Experiment 1), and BM – who prior to and after training listened to Brahms’ Hungarian dance No. 5. In both experiments EEG data were collected during problem solving.

The behavioral data supported the expected beneficial influence of Mozart’s music on learning. However, the results showed that in the first experiment all experimental groups outperformed the controls, hence the test of the priming (listening to music prior learning) /consolidation (listening to music after learning) dichotomy was not positive. A possible reason for this could be that the tasks used were not sensitive enough to measure the potential differences. The same was true for the physiological measures used – no differences in EEG patterns between the control group and the two experimental groups SM and MS were observed. Only the MM respondents, who prior and after learning listened to the Mozart sonata showed reliable physiological changes in relation to the behavioral data. One probable explanation (which was also confirmed in the second experiment) could be that the prolonged exposure of the MM respondents to music might have had a more marked and permanent influence on brain activity subserving spatial reasoning, which could be detected by the EEG methodology.

The displayed pattern of brain activity (lower α and γ ApEn, more α and γ band synchronization) of respondents who prior to and after learning listened to Mozart’s music is similar to findings reported for more intelligent individuals in correlational studies investigating neurophysiological underpinnings of individual differences in intelligence (for a review see Neubauer and Fink, 2008).

In conclusion, it seems that investigating the Mozart effect is still a valuable source for gaining deeper insight into the brain code.

References

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Jaušovec, N., & Habe, K. (2005). The Influence of Mozart’s Sonata K. 448 on Brain Activity During the Performance of Spatial Rotation and Numerical Tasks. Brain Topography, 17(4), 207–218. https://doi.org/10.1007/s10548-005-6030-4

Hughes, J.R. and Fino, J.J. The Mozart effect: distinctive aspects of the music – a clue to brain coding? Clin. Electroencephalogr., 2000, 31: 94-103.

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Sardesai, M., Figge, C., Bodner, M., Crosby, M., Hansen, J., Quillfeldt, J. A., … Shaw, G. L. (2001). Reliable short-term memory in the trion model: Toward a cortical language and grammar. Biological Cybernetics, 84(3), 173–182.

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Verrusio, W., Ettorre, E., Vicenzini, E., Vanacore, N., Cacciafesta, M., & Mecarelli, O. (2015). The Mozart Effect: A quantitative EEG study. Consciousness and Cognition, 35, 150–155. https://doi.org/10.1016/j.concog.2015.05.005

Xing, Y., Xia, Y., Kendrick, K., Liu, X., Wang, M., Wu, D., … Yao, D. (2016). Mozart, Mozart Rhythm and Retrograde Mozart Effects: Evidences from Behaviours and Neurobiology Bases. Scientific Reports, 6, 18744. https://doi.org/10.1038/srep18744

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