Music and the brain in childhood development. (Review of Research).

Recent sophisticated techniques for measuring brain activity allow us to study brain development to a degree never before possible (Nelson & Bloom, 1997). Cerebral blood flow can be measured via positron emission tomography (PET) and magnetic resonance imaging (MRI). Researchers also can measure electrical brain activity with the relatively simple and inexpensive tests known as event-related potentials (ERP) and electroencephalograms (EEG). As a result of these advances, brain-related research has grown tremendously (Cowell, Allen, Zalatimo, & Denenberg, 1992; Dawson, Klinger, Panagiotides, Hill, & Spieker, 1992; Dawson, Panagiotides, Klinger, & Hill, 1992; De Bellis et al., 1999).

One area of research that appears to be of particular interest is the effect of music on the brain, especially in children (Altenmuller, Gruhn, Parlitz, & Kahrs, as cited in Weinberger, 1997; Elbert, Pantev, Wienbruch, Rockstroh, & Taub, 1995; Malyarenko et al., 1996; Pantev, Oostenveld, Engelien, Ross, Roberts, & Hoke, 1998; ScNaug, Jancke, Huang, Staiger, & Steinmetz, 1995). Researchers are exploring the cognitive benefits of music in the classroom (Douglas & Willatts, 1994; Gardiner, Fox, Knowles, & Jeffrey, 1996; Weber, Spychiger, & Patry, as cited in Overy, 2000). Their efforts to provide a clear picture of music's effect on brain development may play an essential role in decision-and policymaking concerning allocation of resources.

The first step in determining how music and musical activities can affect the brain is to understand the process of brain development. Understanding this process is important, as there may be times when the brain is more disposed to skill acquisition--times when the brain is particularly sensitive to the environment and, therefore, more receptive than usual to stimuli.

REVIEW OF LITERATURE

Early Synaptic Growth

Some researchers theorize that during certain sensitive periods, the brain goes through critical development. Huttenlocher (1994) describes an overabundance of synapses that are formed in three areas of the brain--the visual cortex, the auditory cortex, and the prefrontal cortex. He asserts that maximum synaptic growth occurs in the visual cortex at approximately four months of age, and in the prefrontal cortex at approximately one year. The auditory cortex is generally about 80 percent complete at age three months. After this rapid growth period, those synapses that are not used are gradually lost; the process continues through early adolescence.

Cowell et al. (1992) found that corpus callosum (CC) (the band of fibers uniting the cerebral hemispheres) follows a similar growth pattern. They studied 73 pairs of matched males and females between the ages of 2 and 79. The CC size of the males in this study seemed to peak at about 20 years of age. For the females, the maximum size occurred at about 50 years of age. Older participants showed a decline in CC size. This pattern was especially evident in the anterior and extreme posterior regions of the CCs. These results seem to support Huttenlocher's (1994) hypothesized pattern of synaptic growth, albeit with a longer period of brain plasticity.

Nature versus Nurture 

Greenough and Black (1992) describe two processes of synaptic growth--experience-expectant and experience-dependent. In experience-expectant synaptogenesis, the overproduction of synapses described by Huttenlocher (1994) prepares the brain to learn quickly from environmental experiences; a lack of experience results in the elimination of these excess synapses. Stereoscopic visual development in infants appears to fit this pattern, as suggested by Ron Boothe's cataract research (as cited in Egan, 1997). Boothe found that applying simulated cataracts to the eyes of rhesus monkeys in the first month of life resulted in irreversible visual defects, a condition that did not occur when the cataracts were applied after the first month.

Experience-dependent synaptogenesis refers to the development of synapses as a result of environmental stimulation (Greenough & Black, 1992). De Bellis et al. (1999) found a negative correlation between CC size and severity of posttraumatic stress disorder (PTSD) symptoms in abused children and adolescents, as compared to non-abused controls. Conversely, they found a positive correlation between the size of lateral ventricles and PTSD symptoms of intrusive thoughts, avoidance, and hypervigilance. Dawson, Klinger, et al. (1992) found that infants of depressed mothers showed a decrease in distress and an increase in left frontal lobe activity when separated from their mothers as compared to control infants, who showed an increase in distress and fight frontal lobe activity. These researchers hypothesized that the infants' higher left-brain activity indicates this hemisphere's role in inhibiting negative emotions. In both these studies, environmental differences were correlated with differential brain development.

In either type of synaptogenesis, environment affects brain development, both directly and indirectly. A direct influence would involve specific learning tasks, either verbal or physical, that generate new synapses in the brain (e.g., the effect of visual stimulation on the maintenance of synapses in the visual cortex). An indirect influence would involve changing the individual's internal state, or emotion, to one that is more or less receptive to learning new information (i.e., forming new synapses).

Background Music and the Brain

Dawson, Panagiotides, et al. (1992) studied the relationship between frontal lobe activity and emotional affect in 21 -month-old infants. They found that a sad affect was associated with greater right lobe activity, and that a happy affect was associated with greater left lobe activity. The authors further suggest that greater right lobe activation tends to interfere with motor and linguistic ability.

In a related study, Malyarenko et al. (1996) studied the effect of background music on 4-year-old males in a preschool setting. After six months of exposure to a variety of classical music played one hour a day, the boys showed significantly greater interhemispheric [alpha] range coherence than did the controls, whose [alpha] level decreased. In addition, the music group had a significant increase in left lobe intrahemispheric coherence in the [alpha] range, while the controls again experienced a decrease in all but the left frontal lobe. The music group members appeared to tire less easily than the controls. The authors further hypothesize that [alpha] rhythms increase the ability to process sequential and discrete information.

Thus, music may indirectly enhance or impede learning and ability, depending on which internal state is evoked. Music also may influence learning through associated physical activities. When a person physically manipulates an instrument, for example, the brain seems to form new synapses to accommodate the new skills.

Musical Practice and Brain Development

The purported benefits to brain growth of playing a musical instrument are highly controversial. Pantev et al. (1998) studied adults in their late 20s and found that musicians showed significantly greater auditory cortical activity for piano tones than for pure tones, as compared to non-musicians, who showed no significant difference in cortical activity for the different types of tones. The amount of cortical activity was greatest in those participants who began to play an instrument before age 9. Monaghan, Metcalfe, and Ruxton (1998) refuted those results, however, stating that Pantev et al.'s use of the one-tailed test to pinpoint the age-related effect of practice was inappropriate. The results, said Monaghan et al., are not significant when a two-tailed test is performed. They outlined alternative possibilities for the significant group difference, such as family environment and larger auditory cortical representation prior to practice.

Even so, other studies identify correlations between differential brain development and instrument practice. Elbert et al. (1995) found that string players (mean age = 24) had significantly greater cortical representation of their left-hand digits than did the non-musician controls. There was no significant difference between the groups for the right-hand digits. As with the Pantev et al. (1998) study, Elbert et al. found a significant correlation between age of first practice and the size of the cortical representation. Likewise, Schlaug et al. (1995) found that adult classical musicians (ages 21 to 36) had significantly larger anterior CCs than did the matched controls. Again, a strong correlation was found between beginning practice before age 7 and the larger CC size. The researchers suggest that this larger size allows greater communication between the frontal lobes, which coordinate motor activities. Although preexisting or environmental conditions may play a role, there seems to be some logic to the conclusion that increased use of motor activities would result in increased related cortical representations.

Music Learning and Cognitive Skills

Still another area of interest to researchers concerns the cognitive effects of musical instruction. Some researchers have studied the effect of different types of teaching styles (Altenmuller et al., as cited in Weinberger, 1997); others have focused increasingly on explaining how musical instruction affects other areas of learning (Douglas & Willatts, 1994; Gardiner et al., 1996; Weber et al., as cited in Overy, 2000).

Weinberger (1997) outlines Eckart Altenmuller et al.'s research in great detail. Altenmuller found passive and active music instruction to be equally effective in teaching the concept of musical periods to 13- and 14-year-old adolescents. However, the active instruction group appeared to retain the information better one year after the completion of the study. The authors suggest that a connection exists between this differential retention and the finding that the active instruction group showed electrical activation in more parts of the cerebral cortex than did the passive instruction group. During a post-test listening exercise, both music instruction groups showed greater electrical activity in the left hemisphere than did the controls. This seems to indicate that a person with musical training may use greater left hemispheric reasoning when analyzing music than someone with no musical training.

Transfer of Music Learning

Weber et al. (as cited in Overy, 2000) and Gardiner et al. (1996) showed positive transfer effects of music to language and math skills among elementary school students. Weber et al. (as cited in Overy, 2000) found that students in 50 Swiss elementary schools whose language and math courses were replaced with musical instruction did better in language and reading, and no worse in math, than those who attended the standard language and math courses. In a seven-month program, Gardiner et al. (1996) found that the final scores of 1st-graders who participated in "test arts" classrooms were the same in reading, and better in math, than those of students in "standard arts" classroom, despite the fact that the test arts students started the term behind the controls. In addition, the experimental students' attitude toward and behavior in school were roughly equivalent to that of controls at the end of the study, despite being significantly worse than controls at the start. In the follow-up study, the 2nd-grade test group scored equally well in reading and better in math after seven months of being in the test arts class. The effect was greatest in those who had participated in two years of the special class.

Douglas and Willatts (1994) found a significant correlation between rhythmic ability and reading ability in 8-year-old Scottish students. They hypothesized that this finding was due to the close proximity of rhythmic and reading representations in the brain. In a six-month pilot intervention study, they found that developing auditory, visual, and motor skills through musical activities significantly improved the experimental participants' reading ability. The control group, which focused its activities on discussion skills, showed no change in their reading ability. The researchers postulate a connection between musical learning and reading ability.

DISCUSSION

New measurement devices make it possible to pinpoint specific biological changes in the brain that appear to accompany changes in the environment. Difficulty remains in determining what conclusions can be drawn. Longitudinal studies are time-consuming and expensive, and ethical factors must be considered as well. Thus, much of the information on brain development is from short-term studies, most of which are co-relational. The study of human phenomena, then, requires that researchers maintain a logical and conservative perspective when drawing conclusions from research results.

Retrospective Studies of Musical Instrument Practice

Some researchers appeared not to maintain their objectivity when investigating the effects of musical instrument practice on children's brain development. By using the one-tailed test for the age correlation part of the study, Pantev et al. (1998) biased their results in such a way that an otherwise non-significant result became significant. Thus, introducing this bias cast doubt on all of their conclusions.

Other researchers, working with adult participants, show some correlation between growth in specific areas of the brain and playing an instrument at an early age (Elbert et al., 1995; Schlaug et al., 1995). Although there is no evidence of the bias found in the Pantev et al. study (1998), conclusions drawn from these studies also must be viewed with caution, as many possible variables could contribute to the reported results.

Children and Music

The effect of music on children in different settings is particularly interesting. The potential positive effect of background music on preschool students is intriguing (Malyarenko et al., 1996). An important point to remember, however, is that Malyarenko et al. employed a variety of classical music, changed the selected composer weekly, and tailored the selections to the children's preferences. Researchers have not, as yet, identified a set prescription of music that fits all situations. Indeed, this seems unlikely when considering the diversity of musical interests.

The Altenmuller et al. study (as cited in Weinberger, 1997) found that active participation in the learning process enhanced retention of learned material more than passive learning. Both groups learned the musical concept by the end of the study, negating the probability that the measure of learning was biased toward active learning. In addition, both music-learning groups showed a shift in musical processing to the left brain, as compared with those who received no musical instruction. Even so, participants who physically practiced the concept managed to remember the concept better than those who simply learned the concept from verbal instruction, possibly because of differential brain activation during learning.

Children and Transfer Effects

The learning of non-musical concepts also appears to be enhanced by the addition of music to school curricula. The Weber et al. study (as cited in Overy, 2000) showed that music instruction could have a transfer effect on language and math learning, even in the absence of standard classes in these areas. These researchers point out, however, that this type of transfer is contingent on the existence of similar aspects between the musical instruction and the targeted non-musical information. However, little or no research pinpoints which aspects of music learning overlap that of the different school subjects. While studies like those of Gardiner et al. (1996) and Douglas and Willatts (1994) may give some guidelines for music curricula that can teach specific language and math skills, there are no data on which parts of these curricula are instrumental in producing this transfer of learning. Even so, their findings present a compelling case for the use of music in classroom teaching, because of the potential for higher scores and improved attitudes toward, and behavior in, school (Gardiner et al., 1996).

IMPLICATIONS FOR PROGRAMS AND PROFESSIONALS

Rightly or wrongly, these research findings could have a tremendous impact on both school instruction and policy development. Educators must be careful when interpreting individual test results and applying them to a broader context. It is far too tempting to assume that an apparently effective procedure, designed for a specific population in a specific setting, will fit without modification into a different situation. It is imperative that teachers or policymakers realize that most of these studies cannot be generalized. There is no guarantee that group results will translate into individual results, whether it be individual students, individual classrooms, or individual school districts.

Keeping this caveat in mind, research on music and brain development suggests some potentially powerful education approaches. Considering the many different styles of learning that exist in the classroom, the addition of music to the curriculum may open a door for those students who find it difficult to learn from a strictly verbal presentation. When non-musical learning is the goal, it is important that the added musical activity be structured toward that non-musical goal; otherwise, such learning will not be likely. Another important point to take into account is the selection of music. For music to be an effective motivator, it must not have an adverse effect on the children. It can be especially difficult to select music that a class of 30 or 40 children can agree upon.

In the case of policymaking, even greater caution is needed when applying research results across school districts or larger areas. Using broad guidelines with built-in flexibility for individual classrooms is the only way to incorporate results from individual studies. Including this kind of latitude in policies that provide funds for school initiatives would give teachers the chance to provide children with a more enriched learning environment.

Another possible way policymakers can promote children's brain development through music is to fund additional research. If consistently effective and efficient musical interventions are to be developed, however, much more work needs to be done to pinpoint which parts of music or musical instruction enhance brain growth and learning. Identifying and funding carefully controlled studies that target specific musical effects on children's growth and development would provide important information for educators to use in their efforts to develop an enriching atmosphere in the classroom.

References

Cowell, P. E., Allen, L. S., Zalatimo, N. S., & Denenberg, V.H. (1992). A developmental study of sex and age interactions in the human corpus callosum. Developmental Brain Research, 66, 187-192.

Dawson, G., Klinger, L. G., Panagiotides, H., Hills, D., & Spieker, S. (1992). Frontal lobe activity and affective behavior of infants of mothers with depressive symptoms. Child Development, 63, 725-737.

Dawson, G., Panagiotides, H., Klinger, L. G., & Hill, D. (1992). The role of frontal lobe functioning in the development of infant self-regulatory behavior. Brain and Cognition, 20, 152-175.

De Bellis, M. D., Keshavan, M. S., Clark, D. B., Casey, B. J., Giedd, J. N., Boring, A.M., Frustaci, K., & Ryan, N.D. (1999). Developmental traumatology part II: Brain development. Biological Psychiatry, 45, 1259-1270.

Douglas, S., & Willatts, P. (1994). The relationship between musical ability and literacy skills. Journal of Research in Reading, 17, 99-107.

Egan, K. (1997, October 13). Yerkes discovery may help prevent childhood blindness. Emory Report, 50 [On-line serial]. Available: www.emory.edu/EMORY_REPORT/ erarchive/1997/October/eroctober.13/ 10_13_97Yerkes.html.

Elbert, T., Pantev, C., Wienbruch, C., Rockstroh, B., & Taub, E. (1995). Increased cortical representation of the fingers of the left hand in string players. Science, 270, 305-307.

Gardiner, M. F., Fox, A., Knowles, F., & Jeffrey, D. (1996). Learning improved by arts training. Nature, 381, 284.

Greenough, W. T., & Black, J. E. (1992). Induction of brain structure by experience: Substrates for cognitive development. In M. R. Gunnar & C. A. Nelson (Eds.), Developmental behavioral neuroscience: The Minnesota symposia on child psychology: Vol. 24 (pp. 155-200). Hillsdale, NJ: Lawrence Erlbaum. Huttenlocher, P. R. (1994). Synaptogenesis, synapse elimination, and neural plasticity in human cerebral cortex. In C. A. Nelson (Ed.), Threats to optimal development: The Minnesota symposia on child psychology: Vol. 27 (pp. 35-54). Hillsdale, NJ: Lawrence Erlbaum.

Malyarenko, T. N., Kuraev, G. A., Malyarenko, Y. E., Khvatova, M. V., Romanova, N. G., & Gurina, V. I. (1996). The development of brain electric activity in 4-year-old children by long-term sensory stimulation with music. Human Physiology, 22: 76-81.

Monaghan, P., Metcalfe, N. B., & Ruxton, G. D. (1998). Doespracticeshapethebrain? Nature, 394, 434.

Nelson, C. A., & Bloom, F. E. (1997). Child development and neuroscience. Child Development, 68, 970-987.

Overy, K. (2000). Dyslexia, temporal processing and music: The potential for music as an early learning aid for dyslexic children. Psychology of Music, 28, 218-229.

Pantev, C., Oostenveld, R., Engelien, A., Ross, B., Roberts, L. E., & Hoke, M. (1998). Increased auditory cortical representation in musicians' Nature, 392, 811-813.

Schlaug, G., Jancke, L., Huang, Y., Staiger, J. F., & Steinmetz, H. (1995). Increased corpus callosum size in musicians. Neuropsychologia, 33, 1047-1055.

Weinberger, N.M. (1997, Fall). The neurobiology of musical learning and memory. MUSICA Research Notes, 4, 3-5 [On-line serial]. Available: www.musica.uci.edu/mrn/ V4I2F97.html.