Aging Clinical and Experimental Research
Does music enhance cognitive performance in healthy
older adults? The Vivaldi effect
Nicola Mammarella1, Beth Fairfield1, and Cesare Cornoldi2
1Department 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
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: 394-399)
©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: n.mammarella@unich.it
Received September 25, 2006; accepted in revised form April 17, 2007.
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©2007, Editrice Kurtis
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
Music and cognitive aging
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.,
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N. Mammarella, B. Fairfield, and C. Cornoldi
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.
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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.
Aging Clin Exp Res 19: 394-399, 2007
©2007, Editrice Kurtis
Music and cognitive aging
Table 1 - Digit span and fluency test mean scores and standard deviations (SDs) as a function of background condition manipulation.
Vivaldi
Mean SD
Digit span
Fluency
5.3
25.8
1.0
8.2
White noise
Mean SD
4.7
20.5
0.9
8.6
No-music
Mean SD
4.3
19.6
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<0.001. The mean digit span scores in the
music condition were 5.25 (SD=1.03), 4.67 (SD=0.87)
in the white noise and 4.33 (SD=1.20) in the no-music
conditions. Planned comparisons showed that there was
a significant advantage of the music condition over the
white-noise condition, t(23)=2.59, p<0.02, and the nomusic condition, t(23)=5.10 p<0.001. There was no
difference between the white-noise condition and the
no-music condition, t(23)=1.62, p=0.12.
When we introduced order (digit span first vs. fluency
first) as a factor in the analysis, we did not find any main
effect, nor was the interaction significant (in both cases,
F<1).
A repeated-measure ANOVA on phonemic fluency
scores also revealed the significant effect of background,
F(2, 46)=6.43, MSE=42.14, p<0.01. The mean phonemic fluency scores were 25.83 (SD=8.23) in the music
condition, 20.50 (SD=8.63) in white noise, and 19.62
(SD=7.59) in the no-music condition. Planned comparisons showed the significant advantage of music over
white noise, t(23)=2.36 p<0.03, and no-music,
t(23)=7.13 p<0.001. The difference between the whitenoise and no-music conditions was not significant,
t(23)=0.40, p=0.69.
Again, when we introduced order (digit span first vs. fluency first) as a factor in the analysis, we did not find any
main effect, nor was the interaction significant (in both
cases, F<1).
DISCUSSION
To summarize the results of this study, it was possible
to obtain the Vivaldi effect in a group of healthy elderly
people with two measures of working memory functions: listening to a Vivaldi excerpt led subjects to show a
significant increase in phonological working memory capacity and phonemic fluency. In addition, it was found that
the effect was stronger than white-noise background
conditions, supposed to increase memory performance.
In this study, we did not find a white-noise effect, as
performance in the white-noise condition was similar to
that obtained in the no-music condition in both tests. One
reason may be that some studies identified the best intensity by which the effect can be detected at 75 dB
(32). Although we did not control for white-noise intensity,
the mean scores show that participants had a slight increase in white-noise conditions. It is also possible that, by
asking participants to adjust volume individually may
have meant that they lowered it to a barely audible level,
preventing or hindering the white-noise effect. However,
it is also important to note that older adults may show specific difficulties with speech-in-noise conditions. For example, a study by Pichora-Fuller et al. (33) showed that,
when older adults with near-normal hearing were asked to
recall the last word of each sentence heard in a babble
background, their performance dropped, compared with
their younger counterparts. Further research would be
helpful in replicating these findings, using optimal levels
of intensity, comparing amplitudes of music and whitenoise conditions, and introducing a better measure of older adults’ hearing ability.
CONCLUSIONS
Overall, the results obtained in this study appear to support previous research on the effect of music on cognition
(2). The best explanation that put forward to account for
this effect is based on arousal and mood effects produced by music. The arousal-and-mood hypothesis (19)
claims that music enhances the level of arousal, and
consequently attentional processes benefit, and/or that it
promotes positive mood. In particular, the theory holds
that adding entertaining auditory backgrounds makes
the learning task more interesting and thereby increases
the learner’s overall level of arousal. This increase in
arousal results in a greater level of attention, so that
more material is processed by the learner, resulting in improved performance on retention tests. Given the high familiarity of the music excerpt used here, the music condition may have induced positive mood and emotional involvement as well as favoring generally better performance by older adults. Further research would be fruitful
in replicating this study, using unfamiliar excerpts and testing whether the beneficial effect of music on these two
memory tasks mainly derives from emotional involvement typically associated with familiar music.
Although not directly tested in this study, an interesting
assumption may also be that music backgrounds positively interact with phonological working memory tasks by providing a direct connection between the auditory components
of the melody and the phonological components of the
tasks (26). This information may stimulate increased attention towards auditory stimuli and connections between
items (e.g., digit span) as well as cues to guide memory
search (e.g., phonemic fluency) at encoding. The reasons
why some types of music (e.g., by Mozart or Vivaldi) are better than others in fostering these working memory processes, may regard rhythm, contour, interval size, note sequence and, in general, easy acquisition of the melody.
Generally speaking, music is an additional piece of in-
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N. Mammarella, B. Fairfield, and C. Cornoldi
formation that working memory has to process. Thus, in
order for it to be effective in aiding recall, it must be easily acquired and must not subtract relevant amounts of
resources from working memory components involved
in working memory tasks. Otherwise, the melody places
an additional load on attention and memory capacity (4).
Ease of acquisition is usually affected by clarity, repetition, and simplicity. However, it is not necessary for the
melody to be so easy that the subject can accurately follow it to facilitate recall; rather, it is important that the
melodic form of the piece should help participants focus
on the surface characteristics of the task and provide a
corresponding series of cues in remembering (1, 5).
Certainly, these assumptions need further investigation. In order to clarify the level of interaction between
phonological loop and music, it may be interesting,
for instance, to introduce a visuo-spatial test as a control
task, together with manipulation of attentional demands. Cornoldi and Vecchi (34) did distinguish between a continuity model of working memory which postulates different levels of active elaboration and integration from different sources. The use of different
verbal tasks (more passive vs. more active) may also shed
light on the role of control required by music to favor
cognitive performance. The literature seems to suggest (35) that music may have a beneficial effect especially on passive verbal working memory tasks (such as
forward digit span).
Research is thus recommended on the use of music in
promoting different types of cognitive performance, particularly working memory processes, in different boundary conditions, with the final aim also of converting this
short-term memory advantage into a long-term memory
one. This study supports the value of including music as
an active promoter of memory performance in cognitive
intervention with the elderly.
ACKNOWLEDGEMENT
We thank Luisa Scarlato for helping us with data collection.
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