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Different mental rotation performance in students of music, sport and education
Learning and Individual Differences 22 (2012) 159–163
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Different mental rotation performance in students of music, sport and education Stefanie Pietsch, Petra Jansen ⁎ University of Regensburg, Institute of Sport Science, University Street 31, 93053 Regensburg, Germany
a r t i c l e
i n f o
Article history: Received 27 April 2011 Received in revised form 7 October 2011 Accepted 19 November 2011 Keywords: Mental rotation performance Music and sport students Gender differences
a b s t r a c t In this study the effect of long-term physical and musical activity on spatial cognitive performance, measured by mental rotation performance, is investigated in detail. Mental rotation performance is the ability to rotate a three-dimensional object using the imagination. Three groups, each consisting of 40 students, and divided by the subjects, music, sports, and education, solved a psychometrical mental rotation task with threedimensional block figures. The results showed a better mental rotation performance for music and sports students compared to the education students. Furthermore, the well known gender difference favoring males was found for both sports and education students but not for music students. © 2011 Elsevier Inc. All rights reserved.
1. Introduction Parents often are advised that having their child learn to play an instrument and participate in consistent physical activity is important for their children's basic development. This recommendation is based on the idea that encouraging children to do these activities can help them to reach their full academic potential. However, what exactly is the positive effect of such additional education? Concerning physical activity, health orientated training verifiably decreases the danger of things such as postural deformity and cardiovascular disease. However, the influence of sports and music on cognitive performance is a topic of debate and there are only a few studies which have investigated this relationship. The main goal of this paper is to investigate the influence of longterm physical and musical activity on one specific part of cognitive performance, spatial cognition. Spatial abilities are classified into three domains: visualization, orientation, and mental rotation (Linn & Petersen, 1985). Mental rotation is currently the most intensely investigated. It is defined as the ability to imagine how an object would look if rotated away from the plane or depth in which it is actually presented (Shepard & Metzler, 1971). This ability is involved in problem solving (Geary, Saults, Liu, & Hoard, 2000), acquiring mathematical knowledge (Hegarty & Kozhevnikov, 1999), and academic thinking (i.e. Peters, Chisholm, & Laeng, 1995).
1.1. Influence of sports and music on cognitive and visual–spatial performance In sport science, a meta-analysis found a positive correlation between motor and cognitive performance (Etnier, Nowell, Landers,
⁎ Corresponding author. Tel.: + 49 941 943 2518. E-mail address: [email protected] (P. Jansen). 1041-6080/$ – see front matter © 2011 Elsevier Inc. All rights reserved. doi:10.1016/j.lindif.2011.11.012
& Sibley, 2006; Etnier, Salazar, Landers, & Petruzello, 1997). Regarding the influence of listening to music on cognitive abilities, there now seems to be agreement that there is little evidence for a specific effect of listening to a Mozart-sonata on cognitive performance (e.g. Chabris, 1999; Pietschnig, Voracek, & Formann, 2010) as it was investigated by Rauscher, Shaw, and Ky (1993). However in a study by Schellenberg (2004) the IQ of six-year-old children who took either keyboard lessons or voice lessons and a control group was investigated. Both music groups exhibited greater full scale increases in IQ than the control group. Until now there are only a few investigations of the influence of physical activity or musical training on mental rotation performance. A study of Jansen, Titze, and Heil (2009) found that juggling training over three months improved mental rotation performance in adults, while there was no improvement demonstrated by the control group which did not have juggling training. Jansen and Pietsch (2010) also found an increased mental rotation performance of participants after they attended a sport class for 45 min. A control group did not improve their spatial performance after listening to a lecture between the two tests. To our knowledge no study exists investigating the influence of musical training on mental rotation performance. Practicing effects on mental rotation are, until now, limited to investigations of the mental rotation performance of students from a BSc program compared to a BA program (Peters, Laeng, Latham, & Jackson, 1995), or with respect to transfer effects from one test version to another one (Peters et al., 1995). 1.2. Influence of sports and music from a neuropsychological point of view Concerning the relationship between musical education and mental rotation skills, Sluming, Brooks, Howard, Dovnes, and Roberts (2007) have found that musical training can enhance cognitive
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performance on a three dimensional mental rotation task. These results were found by testing professional orchestral musicians compared to a control group which were matched by age, gender, and intelligence. Using fMRI measurements the authors showed that the musicians had more diffuse neuronal activation, including Broca's area, while solving mental rotations tasks. In addition, a comparison of professional musicians, amateur musicians, and non musicians has indicated a pattern of differences in gray matter distribution of the motor, auditory, and visual–spatial regions of the cortex (Gaser & Schlaug, 2003). Zatorre, Halpern, and Bouffard (2010) showed that the intraparietal sulcus is activated when musicians are asked to mentally reverse imagined melodies. They hypothesized that this region is involved in both visual and auditory mental rotation. In addition to these findings, researchers in neuroscience have shown that after juggling training there is an increase in gray matter densities in the intraparietal sulcus (Draganski et al., 2004), which is one of the activated regions of the brain during a mental rotation task (Jordan, Heinze, Lutz, Kanowski, & Jäncke, 2001; Jordan, Wüstenberg, Heinze, Peters, & Jäncke, 2002). 1.3. Main goal of this study The main goal of this paper is to investigate if young adults, who have had long-term intensive training in sports or music but who are still not professionals, as in the study of Sluming et al. (2007), show superior development in their mental rotation ability compared to a control group comprised students who have not had extensive sports or musical training. It is assumed that motor and visual–spatial cognitive abilities are enhanced by intensive musical or athletic training. High levels of training might also lead to structural brain changes (i.e. Hyde et al., 2009). Due to the well known gender differences in mental rotation performance (i.e., Peters et al., 1995), gender was considered as a factor. To investigate these possible differences the amount of musical and sports activity was recorded for all students as well as the speed of cognitive processing, which correlates highly with intelligence. 2. Method 2.1. Participants 120 students from the same university, 60 males (mean age 22.27 years, SD = 2.10) and 60 females (mean age 21.75 years, SD = 3.22), participated. The main subjects of the students were music (20 male, 20 female), sports (20 male, 20 female), or education science (20 male, 20 female). Among the music students, 30% (7 male, 8 female) practice a wind instrument and 40% a keyboard instrument (13 male, 14 female). The other music students were almost equally distributed between percussion and stringed instruments. Among the sports students, 48% play mostly ball sports (18 males, 11 females) and the other sports students were mostly engaged in running, fitness, climbing, biking, dancing, horseback riding, and winter sports. All participants gave their written consent for participation. They were tested during normal courses in a 30-minute long group testing session. Participation was optional, and the students were allowed to terminate the test at any time, but none of them took this option.
2.2. Material and procedure First, a questionnaire was filled out by all participants measuring demographic data and the amount of time spent practicing music and sports. Participants had to answer how many hours they spent practicing a) sports and b) music per week on average and how many years they have actively practicing a) sports and b) music. Years of practicing (sports or music) was defined as the total number of years of sports or music practicing. Practice of music and sports per week was defined as the mean hours of music and sports practiced per week. Next, all participants took part in a measurement of their cognitive processing speed, tested by the ZVT (Oswald & Roth, 1987), which is equivalent to the Trail Making Test (Reitan, 1956). This test consisted of four sheets of paper. The numbers 1–90 were presented on each sheet in a scrambled order. Participants had to connect the numbers in an ascending order as fast as possible. This data was collected to exclude possible differences in cognitive processing speed between the three groups. ZVT-scores can be converted into IQ estimations. There is a correlation between ZVT and standard IQ tests of about r = .60 to .80 (Vernon, 1993). Because of this rather high correlation the ZVT measurement was chosen as an estimate of intelligence. To assess the mental rotation performance the paper–pencil mental rotation test, MRT (Version A) redrawn by Peters et al. (1995), was used. This test was first developed by Vandenberg and Kuse (1978) using the cube figures created by Shepard and Metzler (1971). It is composed of two sets of 12 items each. Each item consists of 5 stimuli, one target stimuli on the left side and four sample stimuli on the right side (see Fig. 1). Two of the four items were identical but in depth rotated versions of the target item. Participants had to mark these two identical stimuli. The items were presented to the participants on four DIN A-4 sheets with six items per sheet and a 3-min deadline to solve two sheets with a set of 12 items resulting in 6 min for the entire test. Instructions were given in written form, followed by three training items so that participants could get accustomed to the task. The correct solutions of these training items were shown at the end of the page. After the training phase, participants were instructed to solve all 12 items within 3 min. After a break of 30 s the next 12 items were tested in another 3 min. The scoring method used is the standard scoring developed by Peters et al. (1995): One point was given if and only if both correct sample stimuli of a target figure were marked correctly. Participants could achieve a maximum of 24 points. The MRT used in this study is the most used paper–pencil mental rotation test besides the original test of Vandenberg and Kuse (compare Peters & Battista, 2008). 2.3. Statistical analysis First, four univariate analyses of variance with the dependent variables a) “hours of sports practice per week”, b) “years of actively practicing sports”, c) “hours of music practice per week”, and d) “years of actively practicing music” and the factors “group” (students of music, sports, and education science) and “gender” (male, female) were performed. Second, a univariate analysis of variance with the dependent variable “speed of cognitive processing” and the two independent factors “gender” (male, female) and “group” (students of music, sports, and education science) was performed.
Fig. 1. Example items from the MRT (Peters, Chisholm, et al., 1995; Peters, Laeng, et al., 1995).
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Third, a univariate analysis of variance with the dependent variable “correctly solved items in the MRT” and the two independent factors “gender” (male, female) and “group” (students of music, sports, and education science) was performed. Finally, to investigate if possible effects of “group” and “gender” on the “correctly solved items in the MRT” can be attributed to the differences in “group” effects in the following variables: a) “hours of sports practice per week”, b) “years of actively practicing sports” between students of sports and education science and c) “hours of music practice per week” and d) “years of actively practicing music” between students of music and education science, two co-variance analyses with the practicing variables as co-variate were performed. 3. Results 3.1. Practicing of sports and music The two analyses of variance with the dependent variables “hours of sports practice per week” and “years spent practicing sports” revealed a significant main effect for the factor “group”, F(2,114) = 62.05, p b .001, η 2 = .52 and F(2,114) = 30.54, p b .001, η 2 = .35, and a significant influence of the factor gender for “years spent practicing sports”, F(2,114) = 3.41, p b .05, η 2 = .06, but not for “hours of sports practice per week, F(2,114) = .16, n.s.. There was no significant interaction. Sports students practice more sports during the week and for more years than education students and students of music. Female sports students had practiced for fewer years sports than males (see Table 1). The two analyses of variance with the dependent variables “hours of music practice per week” and “years spent practicing music” revealed only significant main effects for the factor “group”, F(2,114) = 73.27, p b .001, η2 = .56 and F(2,114) = 37.21, p b .001, η 2 = .39. Music students practice more hours of music during the week and for more years than students of education and students of sports (see Table 1). There was neither a significant influence of the factor “gender” nor a significant interaction. 3.2. Speed of cognitive processing There was neither a significant influence in the speed of cognitive processing of the factor “group” F(2,114) = .68, n.s., nor of the factor “gender”, F(1,114) = .00, n.s., but a significant interaction between both factors, F(2,114) = 3.54, p b .05, η 2 = .06. There was a significant gender difference for music students, F(1,38) = 4.62, p b .05, η 2 = .11 but not for sport students, F(1,38) = 2.92, n.s., or for education students, F(1,38) = .31, n.s.. Male music students had a lower speed of cognitive processing than their female counterparts. Furthermore they showed a significantly lower speed of cognitive processing than the male sport students. 3.3. MRT-performance 3.3.1. Univariate analysis of variance There was a significant effect of the factors “gender” F(1,114) = 8.78, p b .01, η 2 = .08 and “group” F(2,114) = 4.92, p b .01, η 2 = .07.
Fig. 2. Correctly solved items on the MRT (means and standard errors) dependent on gender and group.
The interaction between both factors, F(2,114) = 2.92, p = .058, η 2 = .05 did not reach significance. Fig. 2 shows that males (M = 13.33, SE = 0.62) solved more items correctly than females (M = 11.05, SE = .52), and that sports students (M = 13.25, SE = 0.68) and music students (M = 12.83, SE = 0.72) solved more items correctly than students of education science (M = 10.5, SD = 0.69) (Bonferroni corrected). The almost significant interaction is due to the fact, that only within the music students there was no gender difference, F(1,38) = 0.58, n.s., but a gender difference was found in the sports students, F(1,38) = 8.84, p b .01, η 2 = .19 and education students, F(1,38) = 7.35, p = .01, η 2 = .16. 3.3.2. Co-variate analysis To investigate the difference between the performance of students of sports and education science a co-variate analysis was calculated. The variables “hours of sports practice per week” and “years of actively practicing sports” were included as co-variates. The co-variance analysis showed no main effect of “group” F(1,74) = 2.37, n.s., but of “gender” F(1,74) = 11.59, p = .001, η 2 = .14 and no significant interaction between these factors, F(1,74) = .001, n.s.. To investigate the difference between the performance of students of music and education science a co-variate analysis was calculated including “hours of music practice per week”, and “years of actively practicing music” as co-variates. The co-variance analysis showed no main effect of “group” F(1,74) = 2.79, n.s., or “gender” F(1,74) = 2.6, n.s., and only an almost significant interaction between both factors, F(1,74) = 3.61, p = .062, η 2 = .05. 4. Discussion This study has shown that students of sports and music demonstrate a better performance on mental rotations tasks when compared to students of education science who did not have additional sports or musical training. This result could not be explained by the different ages or environmental variables. Environmental factors
Table 1 Time spent practicing music and sports and speed of cognitive processing (means and standard deviation). Music Male Music per week (h) Years of music Sports per week (h) Years of sports Speed of processing
9.6 14.4 2.52 6.10 2.78
(4.57) (3.96) (2.09) (4.95) (.46)
Sports
Education
Female
Male
Female
Male
Female
8.3 13.35 1.86 4.67 3.06
.9 (1.62) 4.5 (7.47) 12.02 (6.89) 17.55 (2.37) 3.09 (.39)
.78 4.1 10.65 10.63 2.9
.96 (1.89) 4.65 (6.13) 3.35 (1.91) 8.92 (6.03) 2.93 (.52)
.85 (1.69) 3.3 (6.4) 3.35 (1.98) 6.30 (4.78) 2.85 (.41)
(6.31) (4.78) (1.86) (6.35) (.34)
(1.19) (5.72) (5.57) (5.29) (.32)
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were determined to be similar because all students were from the same university and grew up in the surrounding area. 4.1. The enhanced mental rotation performance of music and sport students The question arises why both sports and music students show almost the same high level of mental rotation performance compared to a group of education students. Due to the co-variate analysis it seems to be that the influence of practicing is a factor for the better mental rotation performance in both music and sport students: However, the advantage of sports and music students compared to those of education science disappeared when “hours of practice” and “years of practicing” were both included in the analysis. This suggests that both measurements of sport and music activity contribute to the better performance on the mental rotation task for sport and music students. Because the three groups of students did not differ in their speed of cognitive processing, which highly correlates with IQ-measurements, it can be excluded that this result is due to differences in intelligence. One relevant explanation for the group differences in mental rotation performance might be that both groups had a high motor competence. It is evident that sport students who have been training since the age of 14 have a higher motor performance than those students who have not. Musicians also have a high motor performance, at least at finemotor skills, as it is demanded in tapping tasks (Jäncke, Schlaug, & Steinmetz, 1997). Watanabe, Savion-Lemieux, and Penhune (2007) showed that musicians who trained before the age of seven, the so called “early trained musicians”, showed a better performance in a timed motor sequence task than musicians who began their training when they were older than seven. Early training seems to have its greatest effect on sensorimotor integration and timing. Another explanation is that musicians not only improved their motor performance but also their spatial performance because notes are coded in terms of their spatial position. Patston, Corballis, Hogg, and Tippett (2006) showed that musicians are more accurate when asked to mark the center of a horizontal line than non-musicians and argued that spatial attention seems to be more balanced among musicians. The same argument concerning spatial improvement can be given for athletes who practice a co-coordinative sport which requires spatial perception and cognition, such as tennis, soccer or golf. One neuropsychological explanation might be that the brains of athletes and musicians differ in respect to non-athletes and nonmusicians. It has been shown that musicians have anatomical differences in brain areas that are involved in motor processing (Münte, Altenmüller, & Jäncke, 2002). In a longitudinal study with six year old children structural brain changes in motor and auditory areas were shown after only 15 months of musical training (Hyde et al., 2009). All of the studies which show benefits of musical education on motor functions — cross-sectional and longitudinal studies on functional plasticity — are summarized in Jäncke (2009). Furthermore, it may be that the same brain regions are involved in mental rotation, certain sports (e.g. juggling), and imagining reversed melodies (see Introduction). In addition, Jäncke, Koeneke, Hoppe, Rominger, and Hänggi (2009) have recently shown that golf experts (professional golfers and golfers with handicap 1–14) showed an increase in gray matter in the intraparietal sulcus compared to less experienced golfers. But this specific neuroanatomical relationship has not been investigated at this point and remains speculative in this study. Overall the positive influence of motor experience in athletes and musicians is not yet conclusive. More research needs to be done in this area and gender differences need to be examined. 4.2. The effect of gender on mental rotation performance The results show a significant influence of gender as well as an almost significant interaction between gender and mental rotation. The
well known gender effect favoring males is present in sports and education students but not in music students. This is due to the fact that only female musicians had enhanced mental rotation performance but not the male musicians. Concerning mental rotation performance, the musical motor training in the male musicians did not have the same effect as the athletic motor training in the sports students. Both males and females spend the same amount of time playing their respective instruments. Due to this it appears that the different types of instruments being played does not explain the lack of mental rotation gender difference in musicians. Because the female musicians in this study show a higher speed of cognitive processing it is possible that their ability to process information quickly combined with their long term motor training may explain their enhanced mental rotation ability. The possible effect of motor training reducing gender differences in mental rotation performance has only been investigated in the study of Feng, Spence, and Pratt (2007). They showed that playing an action video game for 10 h eliminated gender differences in the mental rotation task. Further studies have to follow to investigate the possible gender differences of music students solving mental rotation problems as well as other spatial tasks. Another explanation might be that female musicians have a higher degree of androgynous characteristics and that they show some traits which are more observable in males (compare Kemp, 1985). This aspect deserves further attention in following studies as does the influence of the hormonal status of female music and sport students on mental rotation performance. Hausmann, Slabbekoorn, Van Goozen, CohenKettenis, and Güntürkün (2000) found a cycle-related difference in solving a mental rotation test, suggesting that menstrual cycle should be controlled for in further studies. Concerning the gender difference in general, one has to be aware that the paper–pencil mental rotation test is only one instrument often used to investigate mental rotation performance, another options are chronometric tests. Even though both tests investigate the same concept they seem to differ particularly in respect to detecting gender differences. Chronometric test often fail to detect them whereas they seem to be present in paper–pencil tests (compare Jansen-Osmann & Heil, 2007; Peters & Battista, 2008). Obviously, it has to be considered that the psychometric and the chronometric tests differ with respect to various aspects: the psychometric test is often a time-limited test and is mainly based on a two-out-of-four-alternatives choice task whereas the chronometric test is not time limited and often a same-different choice task. But since Titze, Heil, and Jansen (2008) showed that gender differences persist when the MRT is used as a one-out-of-two alternatives choice task, the kind of choice task might not be crucial to explain the differences between the results in the psychometric and chronometric task (but compare Glück & Fabrizii, 2009). Due to this it would be quite interesting to investigate if the results obtained here could be confirmed using chronometric mental rotation tests. 5. Conclusions, limitations and further research The results obtained in this study have important implications for sport science, musicology, and psychology. For people who work in the fields of sport science and musicology it is important to see that a long-time activity in these disciplines, such as playing an instrument or sport for many years, has an enhancing effect on a specific cognitive task. In other words playing sports or playing a musical instrument might have positive physical and cognitive effects. For cognitive psychologists the assumed link between cognitive and motor processes is further supported. But this study also has some limitations. Since this was a quasiexperimental design, participants could not be randomized to experimental groups. The results could be influenced by other variables, even though we did match groups for age, gender, and controlled
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for speed of cognitive processing and time spent of practicing. In the future the influence of motor and music training on mental rotation performance has to be investigated within an experimental design. Acknowledgment The authors would like to thank Prof. Dr. Hans Gruber, education science and Prof. Dr. Bernard Hoffmann, music science, by helping in data acquisition. References Chabris, C. F. (1999). Prelude or requiem for the ‘Mozart effect’? Nature, 400, 826–827. Draganski, B., Gaser, C., Busch, V., Schuierer, G., Bogdahn, U., & May, A. (2004). Neuroplasticity: Changes in grey matter induced by training. Nature, 427, 311–312. Etnier, J., Nowell, P., Landers, D., & Sibley, B. (2006). A meta-regression to examine the relationship between aerobic fitness and cognitive performance. Brain Research Reviews, 52, 119–130. Etnier, J., Salazar, W., Landers, D., & Petruzello, S. (1997). The influence of physical fitness and exercise upon cognitive funktioning: A meta-analysis. Journal of Exercise & Sport Psychology, 19, 249–277. Feng, J., Spence, I., & Pratt, J. (2007). Playing an action video game reduces gender difference in spatial cognition. Psychological Science, 18, 850–855. Gaser, C., & Schlaug, G. (2003). Brain structures differ between musicians and nonmusicians. Journal of Neuroscience, 23, 9240–9245. Geary, D. C., Saults, S. J., Liu, F., & Hoard, M. K. (2000). Sex differences in spatial cognition, computational fluency, and arithmetical reasoning. Journal of Experimental Child Psychology, 77, 337–353. Glück, J., & Fabrizii, C. (2009). Gender differences in the mental rotations test are partly explained by response format. Journal of Individual Differences, 31, 106–109. Hausmann, M., Slabbekoorn, D., Van Goozen, S. H. M., Cohen-Kettenis, P. T., & Güntürkün, O. (2000). Sex hormones affect spatial abilities during the menstrual cycle. Behavioural Neuroscience, 114, 1245–1250. Hegarty, M., & Kozhevnikov, M. (1999). Types of visual–spatial representations and mathematical problem solving. Journal of Educational Psychology, 91, 684–689. Hyde, K. L., Lerch, J., Norton, A., Forgeard, M., Winner, E., Evans, A. C., & Schlaug, G. (2009). Musical training shapes structural brain development. Journal of Neuroscience, 29, 3019–3025. Jäncke, L. (2009). The plastic human brain. Restorative Neurology and Neuroscience, 27, 521–538. Jäncke, L., Koeneke, S., Hoppe, A., Rominger, Ch., & Hänggi, J. (2009). The architecture of the golfer's brain. Plos One, 4(3), e4785. Jäncke, L., Schlaug, G., & Steinmetz, H. (1997). Hand skill asymmetry in professional musicians. Brain and Cognition, 34, 424–432. Jansen, P., & Pietsch, S. (2010). Physical activity improves mental rotation performance. Creative Education, 1, 58–61. Jansen, P., Titze, C., & Heil, M. (2009). The influence of juggling on mental rotation performance. International Journal of Sport Psychology, 40, 351–359.
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Learning and Individual Differences journal homepage: www.elsevier.com/locate/lindif
Different mental rotation performance in students of music, sport and education Stefanie Pietsch, Petra Jansen ⁎ University of Regensburg, Institute of Sport Science, University Street 31, 93053 Regensburg, Germany
a r t i c l e
i n f o
Article history: Received 27 April 2011 Received in revised form 7 October 2011 Accepted 19 November 2011 Keywords: Mental rotation performance Music and sport students Gender differences
a b s t r a c t In this study the effect of long-term physical and musical activity on spatial cognitive performance, measured by mental rotation performance, is investigated in detail. Mental rotation performance is the ability to rotate a three-dimensional object using the imagination. Three groups, each consisting of 40 students, and divided by the subjects, music, sports, and education, solved a psychometrical mental rotation task with threedimensional block figures. The results showed a better mental rotation performance for music and sports students compared to the education students. Furthermore, the well known gender difference favoring males was found for both sports and education students but not for music students. © 2011 Elsevier Inc. All rights reserved.
1. Introduction Parents often are advised that having their child learn to play an instrument and participate in consistent physical activity is important for their children's basic development. This recommendation is based on the idea that encouraging children to do these activities can help them to reach their full academic potential. However, what exactly is the positive effect of such additional education? Concerning physical activity, health orientated training verifiably decreases the danger of things such as postural deformity and cardiovascular disease. However, the influence of sports and music on cognitive performance is a topic of debate and there are only a few studies which have investigated this relationship. The main goal of this paper is to investigate the influence of longterm physical and musical activity on one specific part of cognitive performance, spatial cognition. Spatial abilities are classified into three domains: visualization, orientation, and mental rotation (Linn & Petersen, 1985). Mental rotation is currently the most intensely investigated. It is defined as the ability to imagine how an object would look if rotated away from the plane or depth in which it is actually presented (Shepard & Metzler, 1971). This ability is involved in problem solving (Geary, Saults, Liu, & Hoard, 2000), acquiring mathematical knowledge (Hegarty & Kozhevnikov, 1999), and academic thinking (i.e. Peters, Chisholm, & Laeng, 1995).
1.1. Influence of sports and music on cognitive and visual–spatial performance In sport science, a meta-analysis found a positive correlation between motor and cognitive performance (Etnier, Nowell, Landers,
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& Sibley, 2006; Etnier, Salazar, Landers, & Petruzello, 1997). Regarding the influence of listening to music on cognitive abilities, there now seems to be agreement that there is little evidence for a specific effect of listening to a Mozart-sonata on cognitive performance (e.g. Chabris, 1999; Pietschnig, Voracek, & Formann, 2010) as it was investigated by Rauscher, Shaw, and Ky (1993). However in a study by Schellenberg (2004) the IQ of six-year-old children who took either keyboard lessons or voice lessons and a control group was investigated. Both music groups exhibited greater full scale increases in IQ than the control group. Until now there are only a few investigations of the influence of physical activity or musical training on mental rotation performance. A study of Jansen, Titze, and Heil (2009) found that juggling training over three months improved mental rotation performance in adults, while there was no improvement demonstrated by the control group which did not have juggling training. Jansen and Pietsch (2010) also found an increased mental rotation performance of participants after they attended a sport class for 45 min. A control group did not improve their spatial performance after listening to a lecture between the two tests. To our knowledge no study exists investigating the influence of musical training on mental rotation performance. Practicing effects on mental rotation are, until now, limited to investigations of the mental rotation performance of students from a BSc program compared to a BA program (Peters, Laeng, Latham, & Jackson, 1995), or with respect to transfer effects from one test version to another one (Peters et al., 1995). 1.2. Influence of sports and music from a neuropsychological point of view Concerning the relationship between musical education and mental rotation skills, Sluming, Brooks, Howard, Dovnes, and Roberts (2007) have found that musical training can enhance cognitive
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performance on a three dimensional mental rotation task. These results were found by testing professional orchestral musicians compared to a control group which were matched by age, gender, and intelligence. Using fMRI measurements the authors showed that the musicians had more diffuse neuronal activation, including Broca's area, while solving mental rotations tasks. In addition, a comparison of professional musicians, amateur musicians, and non musicians has indicated a pattern of differences in gray matter distribution of the motor, auditory, and visual–spatial regions of the cortex (Gaser & Schlaug, 2003). Zatorre, Halpern, and Bouffard (2010) showed that the intraparietal sulcus is activated when musicians are asked to mentally reverse imagined melodies. They hypothesized that this region is involved in both visual and auditory mental rotation. In addition to these findings, researchers in neuroscience have shown that after juggling training there is an increase in gray matter densities in the intraparietal sulcus (Draganski et al., 2004), which is one of the activated regions of the brain during a mental rotation task (Jordan, Heinze, Lutz, Kanowski, & Jäncke, 2001; Jordan, Wüstenberg, Heinze, Peters, & Jäncke, 2002). 1.3. Main goal of this study The main goal of this paper is to investigate if young adults, who have had long-term intensive training in sports or music but who are still not professionals, as in the study of Sluming et al. (2007), show superior development in their mental rotation ability compared to a control group comprised students who have not had extensive sports or musical training. It is assumed that motor and visual–spatial cognitive abilities are enhanced by intensive musical or athletic training. High levels of training might also lead to structural brain changes (i.e. Hyde et al., 2009). Due to the well known gender differences in mental rotation performance (i.e., Peters et al., 1995), gender was considered as a factor. To investigate these possible differences the amount of musical and sports activity was recorded for all students as well as the speed of cognitive processing, which correlates highly with intelligence. 2. Method 2.1. Participants 120 students from the same university, 60 males (mean age 22.27 years, SD = 2.10) and 60 females (mean age 21.75 years, SD = 3.22), participated. The main subjects of the students were music (20 male, 20 female), sports (20 male, 20 female), or education science (20 male, 20 female). Among the music students, 30% (7 male, 8 female) practice a wind instrument and 40% a keyboard instrument (13 male, 14 female). The other music students were almost equally distributed between percussion and stringed instruments. Among the sports students, 48% play mostly ball sports (18 males, 11 females) and the other sports students were mostly engaged in running, fitness, climbing, biking, dancing, horseback riding, and winter sports. All participants gave their written consent for participation. They were tested during normal courses in a 30-minute long group testing session. Participation was optional, and the students were allowed to terminate the test at any time, but none of them took this option.
2.2. Material and procedure First, a questionnaire was filled out by all participants measuring demographic data and the amount of time spent practicing music and sports. Participants had to answer how many hours they spent practicing a) sports and b) music per week on average and how many years they have actively practicing a) sports and b) music. Years of practicing (sports or music) was defined as the total number of years of sports or music practicing. Practice of music and sports per week was defined as the mean hours of music and sports practiced per week. Next, all participants took part in a measurement of their cognitive processing speed, tested by the ZVT (Oswald & Roth, 1987), which is equivalent to the Trail Making Test (Reitan, 1956). This test consisted of four sheets of paper. The numbers 1–90 were presented on each sheet in a scrambled order. Participants had to connect the numbers in an ascending order as fast as possible. This data was collected to exclude possible differences in cognitive processing speed between the three groups. ZVT-scores can be converted into IQ estimations. There is a correlation between ZVT and standard IQ tests of about r = .60 to .80 (Vernon, 1993). Because of this rather high correlation the ZVT measurement was chosen as an estimate of intelligence. To assess the mental rotation performance the paper–pencil mental rotation test, MRT (Version A) redrawn by Peters et al. (1995), was used. This test was first developed by Vandenberg and Kuse (1978) using the cube figures created by Shepard and Metzler (1971). It is composed of two sets of 12 items each. Each item consists of 5 stimuli, one target stimuli on the left side and four sample stimuli on the right side (see Fig. 1). Two of the four items were identical but in depth rotated versions of the target item. Participants had to mark these two identical stimuli. The items were presented to the participants on four DIN A-4 sheets with six items per sheet and a 3-min deadline to solve two sheets with a set of 12 items resulting in 6 min for the entire test. Instructions were given in written form, followed by three training items so that participants could get accustomed to the task. The correct solutions of these training items were shown at the end of the page. After the training phase, participants were instructed to solve all 12 items within 3 min. After a break of 30 s the next 12 items were tested in another 3 min. The scoring method used is the standard scoring developed by Peters et al. (1995): One point was given if and only if both correct sample stimuli of a target figure were marked correctly. Participants could achieve a maximum of 24 points. The MRT used in this study is the most used paper–pencil mental rotation test besides the original test of Vandenberg and Kuse (compare Peters & Battista, 2008). 2.3. Statistical analysis First, four univariate analyses of variance with the dependent variables a) “hours of sports practice per week”, b) “years of actively practicing sports”, c) “hours of music practice per week”, and d) “years of actively practicing music” and the factors “group” (students of music, sports, and education science) and “gender” (male, female) were performed. Second, a univariate analysis of variance with the dependent variable “speed of cognitive processing” and the two independent factors “gender” (male, female) and “group” (students of music, sports, and education science) was performed.
Fig. 1. Example items from the MRT (Peters, Chisholm, et al., 1995; Peters, Laeng, et al., 1995).
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Third, a univariate analysis of variance with the dependent variable “correctly solved items in the MRT” and the two independent factors “gender” (male, female) and “group” (students of music, sports, and education science) was performed. Finally, to investigate if possible effects of “group” and “gender” on the “correctly solved items in the MRT” can be attributed to the differences in “group” effects in the following variables: a) “hours of sports practice per week”, b) “years of actively practicing sports” between students of sports and education science and c) “hours of music practice per week” and d) “years of actively practicing music” between students of music and education science, two co-variance analyses with the practicing variables as co-variate were performed. 3. Results 3.1. Practicing of sports and music The two analyses of variance with the dependent variables “hours of sports practice per week” and “years spent practicing sports” revealed a significant main effect for the factor “group”, F(2,114) = 62.05, p b .001, η 2 = .52 and F(2,114) = 30.54, p b .001, η 2 = .35, and a significant influence of the factor gender for “years spent practicing sports”, F(2,114) = 3.41, p b .05, η 2 = .06, but not for “hours of sports practice per week, F(2,114) = .16, n.s.. There was no significant interaction. Sports students practice more sports during the week and for more years than education students and students of music. Female sports students had practiced for fewer years sports than males (see Table 1). The two analyses of variance with the dependent variables “hours of music practice per week” and “years spent practicing music” revealed only significant main effects for the factor “group”, F(2,114) = 73.27, p b .001, η2 = .56 and F(2,114) = 37.21, p b .001, η 2 = .39. Music students practice more hours of music during the week and for more years than students of education and students of sports (see Table 1). There was neither a significant influence of the factor “gender” nor a significant interaction. 3.2. Speed of cognitive processing There was neither a significant influence in the speed of cognitive processing of the factor “group” F(2,114) = .68, n.s., nor of the factor “gender”, F(1,114) = .00, n.s., but a significant interaction between both factors, F(2,114) = 3.54, p b .05, η 2 = .06. There was a significant gender difference for music students, F(1,38) = 4.62, p b .05, η 2 = .11 but not for sport students, F(1,38) = 2.92, n.s., or for education students, F(1,38) = .31, n.s.. Male music students had a lower speed of cognitive processing than their female counterparts. Furthermore they showed a significantly lower speed of cognitive processing than the male sport students. 3.3. MRT-performance 3.3.1. Univariate analysis of variance There was a significant effect of the factors “gender” F(1,114) = 8.78, p b .01, η 2 = .08 and “group” F(2,114) = 4.92, p b .01, η 2 = .07.
Fig. 2. Correctly solved items on the MRT (means and standard errors) dependent on gender and group.
The interaction between both factors, F(2,114) = 2.92, p = .058, η 2 = .05 did not reach significance. Fig. 2 shows that males (M = 13.33, SE = 0.62) solved more items correctly than females (M = 11.05, SE = .52), and that sports students (M = 13.25, SE = 0.68) and music students (M = 12.83, SE = 0.72) solved more items correctly than students of education science (M = 10.5, SD = 0.69) (Bonferroni corrected). The almost significant interaction is due to the fact, that only within the music students there was no gender difference, F(1,38) = 0.58, n.s., but a gender difference was found in the sports students, F(1,38) = 8.84, p b .01, η 2 = .19 and education students, F(1,38) = 7.35, p = .01, η 2 = .16. 3.3.2. Co-variate analysis To investigate the difference between the performance of students of sports and education science a co-variate analysis was calculated. The variables “hours of sports practice per week” and “years of actively practicing sports” were included as co-variates. The co-variance analysis showed no main effect of “group” F(1,74) = 2.37, n.s., but of “gender” F(1,74) = 11.59, p = .001, η 2 = .14 and no significant interaction between these factors, F(1,74) = .001, n.s.. To investigate the difference between the performance of students of music and education science a co-variate analysis was calculated including “hours of music practice per week”, and “years of actively practicing music” as co-variates. The co-variance analysis showed no main effect of “group” F(1,74) = 2.79, n.s., or “gender” F(1,74) = 2.6, n.s., and only an almost significant interaction between both factors, F(1,74) = 3.61, p = .062, η 2 = .05. 4. Discussion This study has shown that students of sports and music demonstrate a better performance on mental rotations tasks when compared to students of education science who did not have additional sports or musical training. This result could not be explained by the different ages or environmental variables. Environmental factors
Table 1 Time spent practicing music and sports and speed of cognitive processing (means and standard deviation). Music Male Music per week (h) Years of music Sports per week (h) Years of sports Speed of processing
9.6 14.4 2.52 6.10 2.78
(4.57) (3.96) (2.09) (4.95) (.46)
Sports
Education
Female
Male
Female
Male
Female
8.3 13.35 1.86 4.67 3.06
.9 (1.62) 4.5 (7.47) 12.02 (6.89) 17.55 (2.37) 3.09 (.39)
.78 4.1 10.65 10.63 2.9
.96 (1.89) 4.65 (6.13) 3.35 (1.91) 8.92 (6.03) 2.93 (.52)
.85 (1.69) 3.3 (6.4) 3.35 (1.98) 6.30 (4.78) 2.85 (.41)
(6.31) (4.78) (1.86) (6.35) (.34)
(1.19) (5.72) (5.57) (5.29) (.32)
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were determined to be similar because all students were from the same university and grew up in the surrounding area. 4.1. The enhanced mental rotation performance of music and sport students The question arises why both sports and music students show almost the same high level of mental rotation performance compared to a group of education students. Due to the co-variate analysis it seems to be that the influence of practicing is a factor for the better mental rotation performance in both music and sport students: However, the advantage of sports and music students compared to those of education science disappeared when “hours of practice” and “years of practicing” were both included in the analysis. This suggests that both measurements of sport and music activity contribute to the better performance on the mental rotation task for sport and music students. Because the three groups of students did not differ in their speed of cognitive processing, which highly correlates with IQ-measurements, it can be excluded that this result is due to differences in intelligence. One relevant explanation for the group differences in mental rotation performance might be that both groups had a high motor competence. It is evident that sport students who have been training since the age of 14 have a higher motor performance than those students who have not. Musicians also have a high motor performance, at least at finemotor skills, as it is demanded in tapping tasks (Jäncke, Schlaug, & Steinmetz, 1997). Watanabe, Savion-Lemieux, and Penhune (2007) showed that musicians who trained before the age of seven, the so called “early trained musicians”, showed a better performance in a timed motor sequence task than musicians who began their training when they were older than seven. Early training seems to have its greatest effect on sensorimotor integration and timing. Another explanation is that musicians not only improved their motor performance but also their spatial performance because notes are coded in terms of their spatial position. Patston, Corballis, Hogg, and Tippett (2006) showed that musicians are more accurate when asked to mark the center of a horizontal line than non-musicians and argued that spatial attention seems to be more balanced among musicians. The same argument concerning spatial improvement can be given for athletes who practice a co-coordinative sport which requires spatial perception and cognition, such as tennis, soccer or golf. One neuropsychological explanation might be that the brains of athletes and musicians differ in respect to non-athletes and nonmusicians. It has been shown that musicians have anatomical differences in brain areas that are involved in motor processing (Münte, Altenmüller, & Jäncke, 2002). In a longitudinal study with six year old children structural brain changes in motor and auditory areas were shown after only 15 months of musical training (Hyde et al., 2009). All of the studies which show benefits of musical education on motor functions — cross-sectional and longitudinal studies on functional plasticity — are summarized in Jäncke (2009). Furthermore, it may be that the same brain regions are involved in mental rotation, certain sports (e.g. juggling), and imagining reversed melodies (see Introduction). In addition, Jäncke, Koeneke, Hoppe, Rominger, and Hänggi (2009) have recently shown that golf experts (professional golfers and golfers with handicap 1–14) showed an increase in gray matter in the intraparietal sulcus compared to less experienced golfers. But this specific neuroanatomical relationship has not been investigated at this point and remains speculative in this study. Overall the positive influence of motor experience in athletes and musicians is not yet conclusive. More research needs to be done in this area and gender differences need to be examined. 4.2. The effect of gender on mental rotation performance The results show a significant influence of gender as well as an almost significant interaction between gender and mental rotation. The
well known gender effect favoring males is present in sports and education students but not in music students. This is due to the fact that only female musicians had enhanced mental rotation performance but not the male musicians. Concerning mental rotation performance, the musical motor training in the male musicians did not have the same effect as the athletic motor training in the sports students. Both males and females spend the same amount of time playing their respective instruments. Due to this it appears that the different types of instruments being played does not explain the lack of mental rotation gender difference in musicians. Because the female musicians in this study show a higher speed of cognitive processing it is possible that their ability to process information quickly combined with their long term motor training may explain their enhanced mental rotation ability. The possible effect of motor training reducing gender differences in mental rotation performance has only been investigated in the study of Feng, Spence, and Pratt (2007). They showed that playing an action video game for 10 h eliminated gender differences in the mental rotation task. Further studies have to follow to investigate the possible gender differences of music students solving mental rotation problems as well as other spatial tasks. Another explanation might be that female musicians have a higher degree of androgynous characteristics and that they show some traits which are more observable in males (compare Kemp, 1985). This aspect deserves further attention in following studies as does the influence of the hormonal status of female music and sport students on mental rotation performance. Hausmann, Slabbekoorn, Van Goozen, CohenKettenis, and Güntürkün (2000) found a cycle-related difference in solving a mental rotation test, suggesting that menstrual cycle should be controlled for in further studies. Concerning the gender difference in general, one has to be aware that the paper–pencil mental rotation test is only one instrument often used to investigate mental rotation performance, another options are chronometric tests. Even though both tests investigate the same concept they seem to differ particularly in respect to detecting gender differences. Chronometric test often fail to detect them whereas they seem to be present in paper–pencil tests (compare Jansen-Osmann & Heil, 2007; Peters & Battista, 2008). Obviously, it has to be considered that the psychometric and the chronometric tests differ with respect to various aspects: the psychometric test is often a time-limited test and is mainly based on a two-out-of-four-alternatives choice task whereas the chronometric test is not time limited and often a same-different choice task. But since Titze, Heil, and Jansen (2008) showed that gender differences persist when the MRT is used as a one-out-of-two alternatives choice task, the kind of choice task might not be crucial to explain the differences between the results in the psychometric and chronometric task (but compare Glück & Fabrizii, 2009). Due to this it would be quite interesting to investigate if the results obtained here could be confirmed using chronometric mental rotation tests. 5. Conclusions, limitations and further research The results obtained in this study have important implications for sport science, musicology, and psychology. For people who work in the fields of sport science and musicology it is important to see that a long-time activity in these disciplines, such as playing an instrument or sport for many years, has an enhancing effect on a specific cognitive task. In other words playing sports or playing a musical instrument might have positive physical and cognitive effects. For cognitive psychologists the assumed link between cognitive and motor processes is further supported. But this study also has some limitations. Since this was a quasiexperimental design, participants could not be randomized to experimental groups. The results could be influenced by other variables, even though we did match groups for age, gender, and controlled
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