Our findings represent the first demonstration of broad transfer of an educationally vital skill: Training in music-listening skills transfers to verbal ability. After a short music-training program, children exhibited enhanced performance on a measure of vocabulary knowledge reflecting verbal intelligence. Although there was no significant increase in verbal or spatial skills following visual-art training, there was a trend for an improvement in spatial skills (see Fig. S1 in the Supplemental Material
), but this trend cannot be distinguished from a practice effect. It is possible that the time course for significant transfer is different for these two domains. Preschool children are auditory experts with well-developed language abilities, but visuo-motor skills are less developed at this stage of life. This “in development” status may necessitate a longer time course for the transfer of visuospatial skills than for the transfer of verbal skills. In other words, a longer or more intensive training period in visual art might significantly influence spatial intelligence. Nonetheless, our results demonstrate that verbal performance can be improved independently of spatial performance and suggest that music and language are closely linked in cognition. One possible explanation for our finding is that music processing overlaps with mechanisms used in other cognitive activities (Patel, 2009
Only 20 days of music training also led to improved performance in an executive-function task (the go/no-go task) and induced brain modifications in a neurocorrelate of that performance (increased P2). An important aspect of our findings is that the brain plasticity observed in our executive-function task was related to improvements in behavioral measures of intelligence. The link between executive function and music is understandable if one considers that music training requires high levels of control, attention, and memorization. Therefore, the transfer effect may be due to these same executive functions being used to process different (i.e., nonmusic) stimuli.
It is possible that the effects of music training on verbal performance were mediated through enhanced attention and verbal memory rather than verbal ability. Other measures of executive function, such as span or task switching, may reveal indirect relationships between training and verbal outcomes. The study reported here cannot distinguish between these alternatives, so further studies using alternative behavioral tasks and structural neuroimaging are necessary to explore these possibilities.
Our findings highlight two phenomena that need to be explained in more detail: the speed of brain modification and far transfer effects. Some evidence suggests that training has a rapid effect on cognition and brain structures (for a review, see Kelly & Garavan, 2005
). For example, Taubert et al. (2010)
found significant increases in gray-matter volume in frontal and parietal areas after only two training sessions in a complex whole-body balancing task. Using a different technique, Scholz, Klein, Behrens, and Johansen-Berg (2009)
observed fractional anisotropy increases (i.e., increases in water diffusion in several brain areas) after 6 weeks of training with 5 training days per week, and Takeuchi et al. (2010)
found such increases after 2 months of daily practice.
Evidence also supports this impressive speed of transfer after music training. For example, Bangert, Haeusler, and Altenmüller (2001)
showed that audio-motor coupling occurred following a 20-min piano lesson, as shown by topographic analysis of very slow ERPs. More recently, Lappe, Herholz, Trainor, and Pantev (2008)
reported ERP changes in young adults after 2 weeks of music training, and Moreno and his colleagues (Moreno & Besson, 2006
; Moreno et al., 2009
) showed brain-plasticity effects in language after 8 weeks and 6 months of music training. These results confirm the powerful ability of music to induce brain plasticity and broad transfer effects.
In addition, the far transfer effect we found (i.e., functional brain plasticity) is consistent with previous reports of an influence of music training (Tremblay et al., 2001
) and auditory training (Reinke et al., 2003
) on the auditory P2. Increased P2 amplitude has been interpreted as reflecting an increased neuronal representation resulting from training (Recanzone, Schreiner, & Merzenich, 1993
) or as an improvement in neural synchrony (Tremblay et al., 2001
). However, these studies trained and tested performance in one modality, whereas our music training influenced a visual P2. Our explanation for this cross-modal effect is related to our interpretation of far transfer and the sharing of brain resources in cognitive processing: Music training stimulates cognitive processing related to parieto-occipital brain regions (Schulze, Mueller, & Koelsch, 2011
), and these same brain areas are also involved in the visual P2 (Omoto et al., 2010
). Thus, music training influences the P2 through brain resources that are common across cognitive tasks.
We advance a shared-resources explanation for the correlation we found between brain plasticity and intelligence. Studies investigating a visual P2 component have found associations between the P2 and higher-level processes (memory: Dunn, Dunn, Languis, & Andrew, 1998
, and Lefebvre, Marchand, Eskes, & Connolly, 2005
; semantic processing: Federmeier & Kutas, 2002
). Further, studies investigating the structural correlates of the P2 showed that this ERP component was evoked by parieto-occipital brain regions that are also involved in intelligence (P-FIT model: Jung & Haier, 2007
). Therefore, our finding of a correlation between this functional plasticity and verbal intelligence is further evidence that increased P2 amplitude is not solely a perceptual-training effect. This correlation also reflects the influence of music training on higher cognitive processing (Bialystok & DePape, 2009
) and highlights the possible identification of a brain mechanism that can be interpreted as a potentiator of a general processing network. In conclusion, these findings corroborate the shared-resources hypothesis and suggest that broad transfer is enabled by sharing of a brain network between higher-level cognitive activities.
Although the same tests were used in the pretest and posttest sessions, we do not believe that practice effects or item-specific memory can account for our results. Practice effects would be expected equally in the two training groups, especially because the children were pseudorandomly assigned to the groups. Although posttest improvements were found for both groups, the results showed improvements that were specific to the training (i.e., only verbal scores improved in the music group). Although a possible effect of item-specific memory may be of concern because there is some evidence for a correlation between verbal memory and musicianship (Ho, Cheung, & Chan, 2003
), we do not believe there is any evidence that the music group simply remembered more of the words for the posttest than the visual-art group did. First, memory span in early childhood is small (i.e., 7 ± 2 items), so it would be challenging for a 4- to 6-year-old child to memorize 32 words in less than 10 min. Moreover, the children were never aware of the correct answer, so memorizing the words would not have improved their scores. Most important, the fact that only one of the groups showed a positive correlation between brain plasticity (P2) and verbal IQ changes suggests a link between the specific training and the verbal IQ outcome, rather than improvement due to repeated testing. For these reasons, we believe that the use of the same instruments for the pretest and posttest sessions in our particular experimental design is not problematic.
Our findings demonstrate a causal relationship between music training and improvements in language and executive functions, supporting the possibility of broad transfer between high-level cognitive activities. The strength of our results (i.e., over 90% of our music-group participants showed improvement in verbal intelligence) confirms that our multidimensional computerized training fully engaged children. These findings are relevant for education for two reasons. First, evidence has shown that WPPSI Verbal IQ (i.e., composite Verbal score) is highly predictive of academic achievement (Kaplan, 1996
) and that there is a strong relationship between IQ evaluated at age 5 (using the WPPSI) and IQ evaluated later in life, with correlations ranging from .72 to .92 (Yule, Gold, & Busch, 1982
). Second, computerized tutorials make it easier to implement training in educational environments such as classrooms and clinical settings. Therefore, the success of our computerized training is encouraging. Our findings open a new path for conceptualizing both education and rehabilitation, for improving them by using computerized technologies, and for developing viable programs in neuroeducation and neurorehabilitation.