هنگامی که موسیقی تمپو تجانس زمانی بین عمل فیزیکی و تصویرسازی حرکتی را تحت تاثیر قرار می دهد

When people listen to music, they hear beat and a metrical structure in the rhythm; these perceived patterns enable coordination with the music. A clear correspondence between the tempo of actual movement (e.g., walking) and that of music has been demonstrated, but whether similar coordination occurs during motor imagery is unknown. Twenty participants walked naturally for 8 m, either physically or mentally, while listening to slow and fast music, or not listening to anything at all (control condition). Executed and imagined walking times were recorded to assess the temporal congruence between physical practice (PP) and motor imagery (MI). Results showed a difference when comparing slow and fast time conditions, but each of these durations did not differ from soundless condition times, hence showing that body movement may not necessarily change in order to synchronize with music. However, the main finding revealed that the ability to achieve temporal congruence between PP and MI times was altered when listening to either slow or fast music. These data suggest that when physical movement is modulated with respect to the musical tempo, the MI efficacy of the corresponding movement may be affected by the rhythm of the music. Practical applications in sport are discussed as athletes frequently listen to music before competing while they mentally practice their movements to be performed.

Whether music influences our physical movement, especially in sport psychology and physical rehabilitation, has raised considerable interest among researchers over last two decades (Karageorghis and Terry, 1997, Karageorghis et al., 2012, Koelsch, 2009 and Zimmerman and Lahav, 2012). Although different features of music have been shown to have large effects on aspects of human behavior ranging from mood to endurance, one of the most important components underlying motor skill acquisition and performance is the rhythm of the music (Smoll & Schult, 1982). Indeed, when people listen to musical rhythm, they perceive a tempo corresponding to the strongest or most salient temporal pulse, and these perceived patterns enable body coordination with the music (Large, 2000). Accordingly, Moelants (2002) stated that there is a clear correspondence between the tempo of spontaneous movements, as observed in walking, clapping and finger tapping, and tempo perceived in music. In a seminal experiment, Styns, van Noorden, Moelants, and Leman (2007) focused on the basic link between walking tempo, walking speed, and musical tempo. They showed that people can synchronize walking movements with music over a broad range of tempi, and concluded that music, as a background phenomenon, is likely to influence a basic bodily activity in an unconscious way. Nowadays, a substantial number of experimental studies found that faster tempo in music makes people move faster when doing physical work compared to slow music (Crust and Clough, 2006, Edworthy and Waring, 2006 and Waterhouse et al., 2010). Motor imagery (MI) has been extensively used to improve an athlete's or musician's performance, and to accelerate recovery from injury. MI is the conscious mental simulation of actions involving our brain's motor representations in a way that is similar to when we actually perform movements (Jeannerod & Decety, 1995). Psychophysical experiments have shown that imagined and executed movements preserve the same spatiotemporal characteristics, especially in highly automatic or cyclical movements, hence suggesting that covert and overt stages of actions share similar motor representations (for review, see Guillot, Hoyek, Louis, & Collet, 2012), that support the principal of functional equivalence (Holmes & Collins, 2001). Accordingly, mental chronometry paradigms are commonly used to assess the ease/difficulty encountered in preserving the temporal characteristics of the motor performance (Guillot and Collet, 2005, Malouin et al., 2007 and Papaxanthis et al., 2002). It is worth noting that previous research provided strong evidence that unless MI time is equivalent to that of physical practice (PP), it will not be as effective in achieving its desired effects (Guillot and Collet, 2008 and Holmes and Collins, 2001). Such temporal congruence between MI and PP, however, is not systematic as several influencing factors may lead to an over- or underestimation of the movement duration during MI (e.g., complexity and duration; Debarnot et al., 2012 and Guillot and Collet, 2005). Previous research has integrated music into imagery in order to contribute to the vividness of the imagined scenes, and facilitate the formation of the mental images. Indeed, it has been demonstrated that participants used visual imagery more readily when listening to music (Osborne, 1981 and Quittner and Glueckauf, 1983. Tham (1994) further found significantly higher movement imagery vividness when participants imagined while listening to music, when compared to a no-music group. However, these studies failed to mention the types of music, how the music was selected, the imagery instructions, or the modality of imagery used. Yet, research that has examined the effect of musical features (e.g., tempo) on imagery ability remain unknown, despite the fact that Clark, Williamon, and Redding (2012) recently confirmed the reliability of mental chronometry recordings for assessing musical imagery ability. Spurred by the results mentioned above and considering the growing interest and application of both MI and music in sport and rehabilitation, the present study was designed to determine whether and to what extent different music tempi may contribute to MI ability (i.e., temporal equivalence between MI and PP). We tested whether fast and slow tempi of music could elicit a modulation of PP and MI locomotion times with respect to soundless condition, and consequently whether the temporal congruence may be maintained with respect to such different patterns of musical tempo.

The mean Stanford Sleepiness Score was 1.85 (.74), and no subject was assessed above the sleepy value (i.e., 3), thus attesting to the “good level” of alertness. Mean MIQ-3 scores were 22.05 (.99) for external visual imagery, 20.35 (1.13) for internal visual imagery, and 18.15 (1.14) for kinesthetic imagery. An ANOVArm showed a main effect of MI modalities (F3,53 = 1.55, p = .21), and as expected, external visual imagery scores were higher than kinesthetic imagery scores (p < .05), but did not differ from internal visual imagery scores (p = .79).