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Aging Clinical and Experimental Research
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Does music enhance cognitive performance in healthy older adults? The Vivaldi effect Nicola Mammarella1, Beth Fairfield1, and Cesare Cornoldi2 of Biomedical Sciences, University of Chieti “G.D’Annunzio” and Università Telematica, “L. Da Vinci”, Chieti 2Department of General Psychology, University of Padova, Padova, Italy
1Department
ABSTRACT. Background and aims: controversial evidence suggests that music can enhance cognitive performance. In the present study, we examined whether listening to an excerpt of Vivaldi’s “Four Seasons” had a positive effect on older adults’ cognitive performance in two working memory tasks. Methods: with a repeated-measures design, older adults were presented with the forward version of the digit span and phonemic fluency in classical music, white-noise and no-music conditions. Results: classical music significantly increased working memory performance compared with the no-music condition. In addition, this effect did not occur with white noise. Conclusion: the authors discuss this finding in terms of the arousal-andmood hypothesis and the role of working memory resources in aging. (Aging Clin Exp Res 2007; 19: 00-00) ©2007,
Editrice Kurtis
INTRODUCTION During the past decade, there has been renewed interest in the use of environmental techniques for enhancing memory performance, and several studies have documented the value of using music to improve memory performance (1) and, more generally, intellectual performance (2). Some researchers for example, have used music to induce sad or happy moods in participants during cognitive tasks, and then explored its effect on participants’ answers along a depression scale. They found that those who listened to sad music reported depressive states that were prolonged and heightened with respect to those who listened to happy or neutral music (3). However, other studies (4) have shown that the benefits of music cannot be generalized to all cognitive processes. In fact, the introduction of music during the reading of a multimedia message (e.g., text and corresponding figures) seems to damage comprehension, evidencing how the
memory task and the cognitive load involved are both crucial in order for music to be effective. Researchers also initially agreed that the positive effects of music were not generalizable to all types of music. Above all, they reported that exposure to classical music, as in the so-called Mozart effect or Vivaldi effect (5, 6), increased cognitive performance on measures of spatial reasoning and autobiographical memories (e.g., recall). In their original paper, Rausher et al. (7) reported that 36 undergraduates increased their mean spatial-reasoning scores on portions of the Stanford-Binet Intelligence Scale after listening to a 10-minute excerpt of Mozart’s Sonata for two pianos in D major, K.448. Nonetheless, the numerous replications following this work (8-10) failed to reveal any advantage of listening to music on cognitive performance, and concluded that there was little evidence for this effect. One of the explanations advanced by researchers referred to the use of different dependent measures, different procedures and different tasks across experiments (11). Rausher et al., for instance, presented results from a combined performance on three Stanford-Binet subtests (specifically selected for their spatio-temporal components) and repeatedly tested participants for a total of 4 days, whereas other studies applied single more visuo-spatial measures (e.g., paper folding) and participants were tested only once. Thus, the uniqueness of the “Mozart effect” and the complementary idea that listening to music is associated with benefits in specific visuo-spatial abilities and/or verbal skills in children and younger adults has been repeatedly questioned (12). Interestingly, however, many studies about the elderly, as well as about patients with dementia of Alzheimer’s type (13), have successfully demonstrated the potential benefits of music, showing an increase in performance on various dependent measures (e.g., observed levels of social interaction and well-being, autobiographical memory, category fluency, etc.). Irish et al. (14), for example, re-
Key words: Aging, cognitive performance, music, working memory. Correspondence: Nicola Mammarella, Dipartimento di Scienze Biomediche, Facoltà di Psicologia, Università degli Studi “G. D’Annunzio”, Via dei Vestini 29 Blocco A, 66013 Chieti, Italy. E-mail:
[email protected] Received September 25, 2006; accepted in revised form April 17, 2007.
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cently found an increase in autobiographical memories in a group of Alzheimer patients and controls after listening to Vivaldi’s “Spring” movement. These results are particularly interesting, because it has been suggested that cognitive performance in the elderly is particularly sensitive to situational factors (15). Consequently, if music can create a situation that potentially optimizes performance in the elderly, this should have important practical implications for successful aging. Recent interest in the effect of music on memory and cognitive performance seems to reflect what some old studies called the “white noise” effect. More specifically, a series of experiments from the 1970s showed the beneficial effect of white noise on short-term memory (16). White noise is considered to be a special type of noise, because it contains every frequency within the range of human hearing (generally from 20 Hz to 20 kHz) in equal amounts, and has long been used as a relaxation technique. When the first studies were published, white noise was considered an arouser to learning that promotes recall. This benefit was explained by the fact that people tend to rehearse more during a white-noise presentation than during a silent condition. Subsequently, it was also suggested that white noise increases the duration of memory traces, because it reduces levels of interference. For example, it has been suggested that white background noise may improve cognitive performance by attenuating environmental distraction (17). Although there are inconsistencies in available data on the effect of white noise and music in memory, no studies, as far as we know, have compared the music effect with the white-noise effect in aging. Rausher et al. (18) found, for example, that the Mozart sonata (K. 448) was more effective than white-noise conditions in promoting spatial learning in rats, suggesting the supremacy of the effects of music on their spatial learning which could also be generalizable to humans. In most studies regarding the role of music in memory, older adults are usually exposed to a classical music excerpt, a relaxation tape, a popular song, or they are not exposed to music at all (silence). In many cases, there is only a music condition compared with a no-music condition. Thus, the conclusion that music enhances recall in aging mainly derives from comparison of music and nomusic conditions. Differently, the purpose of this study was to compare the effect of music on memory in both whitenoise and no-music conditions. As older adults are particularly sensitive to situational factors, comparison between these two conditions (music and white noise) may better highlight the nature of the positive effect of music. The interesting research question in this paper, then, was whether music is more effective than a white-noise condition in promoting cognitive performance. If the white-noise effect is mainly due to increased
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levels of arousal, the supremacy of music vs. white-noise conditions on cognitive performance cannot be attributed solely to increased levels of arousal. Thompson et al. (19), in line with many other studies (e.g., 12), have provided strong evidence supporting their so-called arousal-and-mood hypothesis of music effects according to which the beneficial effect of music is mediated by both arousal level and participants’ mood. The main assumption is that listening to music positively affects both the level of arousal and mood which, in turn, favors cognitive processing. In summary, in the present study, we explored the classical music effect on elderly people’s memory performance using a more controlled presentation condition, in an attempt to extend previous research. If memory performance in the Vivaldi condition exceeds memory performance in the no-music condition, and especially in the white-noise condition, the results would support the concept that music is effective in sustaining cognitive processes by promoting positive mood and emotional involvement. As participants were Italians, we thought that a piece by Vivaldi would be particularly suitable and familiar music to foster participants’ emotional involvement. Other studies (e.g., 20) have shown that, although older adults perform worse than younger adults on many memory tasks, they are still sensitive to emotional effects, and their performance is strongly linked to the level of emotional response. Consequently, a Vivaldi excerpt was chosen, as in previous studies in aging, to test the effect of music on memory (6, 14, 21). In particular, in classical music, white-noise and no-music conditions, older adults were presented with two working memory (WM) tasks. Baddeley (22) described WM as the system that temporarily maintains and manipulates information, playing an important role in many cognitive tasks, such as reading, problem-solving, and spatial orientation. They developed the concept of short-term memory into a three-component system, comprising a limited capacity attentional controller (central executive), aided by two subsystems, one concerned with acoustic and verbal information (phonological loop) and the other performing a similar function for visual and spatial information (visuo-spatial sketchpad). Musical information appears to be processed by the phonological loop (23, 24) and some studies have shown that musical ability correlates with phonological ability (25). Neuropsychology literature (26, 27) has also shown that musicians have a specifically enlarged left temporal lobe compared with non-musicians, suggesting a link between musical stimulation of this specific brain area (which is where the phonological loop is typically located) and the corresponding cognitive processing of verbal information. In accordance with these findings, we used two working memory tasks that were assumed to rely on the phonological components of working memory (22), i.e.,
Music and cognitive aging
the forward version of the digit span and phonemic fluency. The digit span task was introduced in order to have a baseline measure of older adults’ phonological loop capacity; whereas the phonemic fluency test was assumed to rely on a series of basic working memory functions, involving both the phonological loop and the Central Executive components of working memory (22), such as active search in long-term memory by means of phonemic cues, verbal response production, keeping track of the responses already given, and inhibition of irrelevant candidates. We chose the phonemic rather than the semantic version, because a series of studies has shown that semantic fluency mainly reflects problems with semantic memory (28), whereas phonemic fluency imposes stronger demands on executive functioning and, in general, on phonological working memory. Moreover, we believed that the phonemic nature of the task would better highlight the interaction between music and the phonological loop. Thus, we were also able to investigate whether music positively affects different phonological working memory functions (e.g., capacity, active search, and inhibition). In fact, increased attention to the sound properties coupled with emotional involvement may make a possible music effect more evident. This would also explain why previous studies on aging did not find the positive effect of music with every verbal working memory task (29). Lastly, mirroring the general method used by Thompson et al. (21), who found the positive effect of classical music on a category fluency test with a group of Alzheimer’s patients and controls, we wanted to generalize results to other verbal working memory tasks and to overcome some of the limitations presented in the above study (e.g., absence of white-noise condition and small sample size: 16 participants). METHOD Participants and design The study adopted a repeated-measures design, with type of background (Vivaldi vs. white noise vs. no-music) as within-subjects variable. Twenty-four older adults participated in the experiment. They were communitydwelling people in the area of Chieti (Italy) and reported being in good health; they were not paid for their participation. Their mean age was 81 years (SD=4.5; range between 73 and 86), and their mean level of education was 10.6 years (SD=3.6). They had a mean score of 27 (SD=2.7) on the Mini-Mental State Examination (MMSE; 30). Participants were non-musicians, but they were all very familiar with the Vivaldi excerpt. The type of background (music, white noise, no-music) was counterbalanced across participants with a Latin square design. In addition, half the participants were presented with the digit span first, whereas the other half took the fluency test first.
Material and procedure. Participants were first given a general explanation of the two tasks they would be asked to perform: the forward version of the Digit Span, in which they were required to repeat a sequence of digits following the presentation order (maximum possible= 8), and the Word Fluency Test, in which they were required to name as many words as possible beginning with a specified letter in a 60-s interval (maximum possible= 34). Both tests were derived from the ENB test (31). In the digit span task, we used the typical procedure adopted in the Wechsler batteries, i.e., participants were presented with two sequences for each length, starting with a series of two digits. The task was stopped when the participant failed both sequences of a given length: the score was defined by the number of digits of the longest recalled sequence. In the phonemic fluency task, participants were presented sequentially with three letters (e.g., c, p, s) and were asked to name as many words as possible beginning with the given letter. The score was given by the mean number of words retrieved for each letter. We developed three versions of the digit span and three versions of the phonemic fluency task by changing the digits participants had to recall and the starting letters for the fluency task. In this way, participants performed the same task in the three different background conditions. For example, in the digit span first condition, participants performed a digit span and a fluency test in the music condition, a digit span and a fluency test in the white-noise condition and a digit span and a fluency test in the no-music condition. Again, the type of background and the order of tests were counterbalanced across subjects. Vivaldi’s “Four Seasons”: “Spring” and the white noise were both presented to participants on a Sony cassette player. Participants did not wear headphones, and were asked to adapt the volume of the music and the noise to a level that allowed them to understand the experimenter’s instructions. Each participant was tested individually in a quiet room. The experimenter verbally explained the entire procedure to participants, to ensure that they understood the tasks before the experimental session. The music (and white noise) started 1 min before the digit span and phonemic fluency tasks were presented, and was stopped as soon as the tasks ended. In order to highlight the involvement of phonological abilities in auditory processing better, the music and white noise continued during the task. In order to have a comparable experimental time across conditions, participants were asked to be silent for 1 min before the no-music condition started. RESULTS Table 1 presents the means and standard deviations for the two memory tasks by type of background.
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Table 1 - Digit span and fluency test mean scores and standard deviations (SDs) as a function of background condition manipulation.
Digit span Fluency
Vivaldi
White noise
No-music
Mean SD
Mean SD
Mean SD
5.3 25.8
4.7 20.5
4.3 19.6
1.0 8.2
0.9 8.6
1.2 7.6
A repeated-measure ANOVA on digit span scores showed a significant background effect, F(2, 46)=10.33, MSE=0.50, p
