Arms flail, little bodies propel into the air, and torsos spin and bend in unnatural ways. Feet alternate between steady bouncing and sporadic jumps, kicks and spins. More than the occasional collision or fall occurs yet only smiles appear on the faces of the young children. The scene described here happens often; at a kindergarten dance party the children dance uninhibited while the music plays. But to say they dance to the music may be misleading. The children observed could not accurately dance to the beat of the music. One could speculate many explanations for this perceived difficulty:
- The processing skills of young children are too undeveloped to undertake such a complicated task as coordinating movements to an external beat. Several neural components help execute the task of dancing to a beat, including the auditory system, the musculoskeletal system and the synchronization of these different systems. (Todd 2002)
- Many motor tasks, such as writing or catching a ball, prove difficult for preschool aged children; therefore, to assume that the motor control required for dancing to a beat has yet to develop seems plausible. The sporadic, primitive movements observed in dancing children also support this hypothesis.
- Perhaps dancing to the beat of music is a socially learned activity. Who says we have to dance to the beat of the music anyway? The lack of exposure to public dancing prevents children from learning the socially accepted way to dance to music.
- People feel pleasure when they successfully dance to the beat of music. If children have not discovered this sense of pleasure, they would have no desire for it and therefore not attempt to dance to the beat.
- Adults perform and compose most popular children's music. As a result, the music better suits adult's movement than children's movement.
- In physical activity an adult will tend to conserve energy, a learned survival skill. Children, on the other hand, not only have more energy but have not learned to conserve this energy. Their dancing mirrors this, containing quick and sporadic movements. Faster music may be more appropriate for this style of dancing. Faster music may also suit children better because of their smaller size.
- Children can have difficulty focusing on more than one thing at once. If children focus their attention solely on dancing perhaps they may not listen closely to the music. With little attention paid to the music, they certainly would not dance to its beat.
- The awareness of self and one's own movement develops as children reach preschool age. Children may think in time to the music but may not execute movement in time to music because the awareness of their own movement is inaccurate. The observation of children colliding or falling as they dance supports this conclusion.
- Many young children have received no musical training. Dancing to the beat of the music may be facilitated by formal training.
 Research regarding children and dance is scarce and relatively inconclusive. Though many of the above speculations may be supported by future studies, existing research supports one account in particular. First, this article briefly explores the inability of children to synchronize movement to an external beat. Then, through research and experimentation, this article aims to test whether this rhythmic deficiency might result from a discrepancy between average musical tempi and a child's natural rate of movement as established by spontaneous motor tempo and body morphology.
The Inability of Children to Dance to the Beat of Music
 The motivation for this research was an observation in a preschool classroom that children do not synchronize to the beat of the music when dancing. Before continuing with an experimental investigation, it is appropriate to establish that this observation is not an isolated case.
 Several studies support the observation that children have difficulty synchronizing movement to an external source. Many of these studies involve finger tapping tasks. In one such study (Drewing, Aschersleben, Li, 2006), a sensorimotor synchronization task was presented to 286 participants ranging in age from 6 to 88. Participants were given three different types of sequences with which to synchronize their tapping. In the first two sequences participants were presented with a regular pulse containing an interstimulus onset interval (ISI) of 333 ms and 999 ms, respectively. In the third trial participants heard three short ISIs followed by three long ISIs creating an irregular beat. Children's ability to synchronize their tapping with the stimulus increased at a steady rate until the age of fifteen. A similar study by Volman (2000) also found that the stability of tapping increases with age.
 A more relevant study by Eerola et al. (2006) recorded children's movement to music in a more natural setting. In their study forty-six children, ages 2–4, were videotaped dancing to a familiar song with a tempo of 140 beats per minute (BPM). The tempo of different structural sections in the music was manipulated by ten percent in both directions-slower and faster. The goal was to observe the types of movement present and measure the ability of individual children to synchronize to the music. The children moved in three different ways: circling, swaying or hopping, the most representative movement being hopping. As far as synchronization, the children moved in unstable ways with only brief periods of synchronization. Children did not adjust to the changing tempos.
 In addition to tapping studies, studies on gross motor movement in children have also been carried out. These studies also support the findings that children have difficulty synchronizing movement to music. Rainbow (1981) showed that children, ages three and four, can vocalize rhythms adequately but have difficulty with larger motor movements such as marching or clapping in time to music. Another study by Sims (1985) studied types of creative movement in children and their reactions to changes in music type. Sims' research also supports the idea that children have difficulty in matching body movement with the rhythm of a musical stimulus.
 These studies provide evidence that the majority of children do indeed have a difficult time in synchronization tasks. The Eerola study also shows that when asked to dance or move to music, most children will engage in a hopping motion. This becomes relevant in chapter six as a part of an experimental design to measure the spontaneous or preferred dance tempo of children.
Spontaneous Motor Tempo in Children and Its Implications on Preferred Dance Tempo and Synchronization Tasks
 Many aspects of daily life are controlled by internal, biological rhythms. These biological rhythms, defined by Koukkari and Sothern as "a change that is repeated with a similar pattern, probability, and period" (Koukkari and Sothern, 2006), may influence our rhythmic perception. Circadian rhythms, an example of biological rhythm, create a regular pattern of sleeping and eating which correlates with external environmental and social factors. Recent research shows that internal timing mechanisms in our body could also have a significant effect on our spontaneous motor activity, such as walking or dancing. Humans have a tendency to move at a certain rates and these rates vary depending on age. Methods of measuring spontaneous motor tempo include measuring features of walking and finger tapping. This chapter focuses on spontaneous motor tempo (SMT) in children as exhibited in finger tapping tasks and the effect SMT has on children's dancing.
 A study by Provasi and Bobin-Bègue (2003) also provides insight into the spontaneous motor tempo of children. Before the synchronization task was executed, children were prompted to tap at their preferred rate. Results showed that children, even as young as 2½ years old produced a steady tempo. The rate of the tempo had an average interstimulas interval of 400 ms which translates to 150 beats per minute. This is somewhat faster than the spontaneous motor tempo of adults which has an interstimulus interval of 600 ms or 120 beats per minute (Fraisse, as cited in Provase and Bobin-Bègue, 2003 and Eerola et al, 2006).
 Many other studies have produced similar results. Vanneste, Pouthas, and Wearden (2001) found a mean SMT of around 536 ms for young adults (18 to 30 years old) and 747 ms for older adults (60 to 80 years old). While this has no direct bearing about the spontaneous motor tempo of children it supports the idea that spontaneous motor tempo decreases with age. Pouthas and Jacquet (Pouthas and Jacquet, 1987) observed spontaneous motor tempo in 4½- and 5½-year-old children and found it to be 411 to 478 ms—faster than the SMT of adults.
 Spontaneous motor tempo may have an effect on children's ability to dance to the beat of music in at least two ways. First of all, one might assume that children prefer to move faster because of their faster internal tempo. Second, the closer an external beat is to a person's spontaneous motor tempo, the easier the task of synchronization. It has been established that adults can synchronize tapping to external beats between 200 and 1800 ms with the most accuracy between 400 and 800 ms (Fraisse, as cited in Provase and Bobin-Bègue, 2003 and Eerola et al, 2006). Adults' SMT lies perfectly in the middle of that range. Children synchronize best to tempos around 150 beats per minute; yet in a survey of a wide range of music, Moelants (Moelants, 2002) found an average musical tempo of around 120 beats per minute. This tempo coincides much better with the SMT of adults rather than the SMT of children—supporting the idea that much music may be too slow for children, causing difficulty in dancing to the beat.
The Effects of Anthropometric Features and Movement on Rhythm Perception
 Other than spontaneous motor tempo, another significant difference between children and adults is size, which has a significant effect on movement. This section will explore some of the vast amount of research in this area and their implications for rhythm perception. The findings in music perception provide a foundation for the ensuing two chapters which explore the relationship between body morphology and preferred dance tempi in adults and children.
 The possible importance of anthropometric factors in rhythm-related behaviors has figured prominently in the work of Neil Todd (1992, 1995, 1999, 2000). In the first instance Todd has noted that the vestibular system is shared with the sense of hearing within a single anatomical organ which includes both the cochlea and the semi-circular canals. Todd has proposed a physiologically-based model that attempts to account for the often observed parallel between musical "motion" and corporeal motion.
 Evidence in support of an association between rhythm and locomotion is found in studies by Friberg and Sundberg (1999) and by MacDougall and Moore (2005). In their study of ritardandi, Friberg and Sundberg found that the final slowing in recorded music closely corresponds to the application of a constant breaking force similarly to the manner in which runners stop. In the MacDougall and Moore study, participants wore an accelerometer that continuously monitored body movements in three dimensions over the course of a day. In analyzing the recorded data, MacDougall and Moore found a marked peak at about 1 Hz for movements when measured at the wrist, ankle, and hip. This 1 Hz resonance relates to the pace of walking. However, analysis of head movements showed a peak at about 2 Hz for vertical movements. This 2 Hz resonance strongly relates to the pace of walking, however, the head "bobs" at twice the rate of a given arm or leg movement. The combination of both the left and right leg movements dictates the cycle of head movements. MacDougall and Moore plotted their aggregate acceleration data against a histogram of tempi from a large database of contemporary Western music assembled by Moelants (2002). The two distributions proved nearly identical, with both showing a dominant peak at 2 Hz.
 Throughout history, observers have noted the close relationship between musical tempo and pace of walking. However, the empirical research suggests that it is not the movement of arms and legs during walking per se that accounts for the observed correlation. More precisely, the relationship arises from movements of the head. This interpretation is consistent with a remarkable set of experiments by Phillips-Silver and Trainor (2005, 2007).
 Phillips-Silver and Trainor showed that bouncing an infant at different meters influences the infants' rhythmic perception. Using a series of controls, Phillips-Silver and Trainor showed that the effect is attributed solely to movements of the head—not the body as a whole. Furthermore, through electrical stimulation of the vestibular nerve, they traced the effect directly to the activation of the vestibular system. The activation of the vestibular system and not the body movement "per se" accounts for the close relationship between musical tempo and movement. However, the movement of the body as a whole remains important because the body movement causes the head movements, which in turn stimulate the vestibular system.
 In recently published research by Todd, Cousins and Lee (2006), a significant correlation was found between tempo classification of different auditory rhythms and anthropometric measures such as leg length. The measured factors included stature, mass, sitting height, shoulder width, pelvic bone width, and ankle width. Four factors produced a significant effect on preferred beat rate: mass, height, leg length, and shoulder width. Mass was the most significant. The effect size ranged from 27 to 32 ms in the predicted direction. The range of preferred beat rate, 451-635 ms, is consistent with other research.
The Effects of Anthropomorphic Factors on Preferred Dance Tempo
 Where Todd's work suggests a relationship between body and perception, a study by Dahl and Huron investigates whether a relationship exists between body morphology and preferred dance tempo. In light of the extant research, it is not implausible that preferred dance tempos might relate to anthropometric factors like body mass and height.
 Dahl and Huron (2007) carried out a correlational study in which adult participants were placed alone in a room with a drum machine. Participants were instructed to dance (unobserved) while tuning the tempo of the drum machine to match their preferred dance tempo. They found that leg length and body weight were significant predictors of preferred dance tempo. As in any oscillating system, the resonant frequency relates to mass and elasticity. In the case of the human body, leg length may be an index of elasticity, while weight is a direct index of mass.
 One difficulty with the Dahl and Huron study was that the participants were self selected. Recruitment materials indicated that, as part of the experiment, participants would be weighed. As a consequence one might expect that heavy-set individuals would refrain from volunteering as participants limiting the range of body types in that experiment. In testing the relationship between body morphology and preferred dance tempo, a wider range of body sizes would produce greater statistical power. One way to increase this variability is to examine children.
Preferred Dance Tempo in Children: A study by Huron and Utley
 Children's dancing might be regarded as stylized bouncing. That is, dancing elaborates on the natural oscillation of the body. We assume that the most efficient dance movements capitalize on the resonance of body movement while bouncing. In brief, our experiment involved videotaping children bouncing up and down. Previous research suggests that "hopping" is the most common movement type when children move to music (Eerola et al, 2006). We subsequently took morphological measures of each child. Note that, in carrying out this study we initially assumed that the instruction to "jump up and down" is equivalent to an instruction to "bounce" or "hop."
 We predict that mass and height will negatively correlate with bouncing rate (in bounces per minute). That is, we predict that larger body size (in weight and height) will be associated with slower preferred dance-like movement.
 Twenty-one subjects were recruited for the experiment, 9 females and 11 males. The participants, drawn from a convenience population of children who attended day care, ranged in age from 2 to 7 years.
 Participants were tested individually in an isolated area on a flat solid-surface linoleum floor covering a concrete base. Each child was asked to jump up and down until he/she became too tired to continue. The experimenter did not demonstrate the activity for the children. Activity was videotaped with the camera positioned so as to capture an image of the full body including head and feet.
 After recording the jumping/bouncing, two anthropometric measurements were taken: height and weight. For the weight measurement, the child was asked to stand on a domestic electronic scale. For the height measurement, the child stood against a wall marked with a measurement grid. By placing a ruler on the child's head the experimenter read the height off of the wall grid. Originally we had planned to measure leg length. In Dahl and Huron leg length was estimated by asking the participant to point to the lower part of the hip bone protuberance (anterior inferior iliac spine) on their left and right sides; after locating these points the experimenter measured the length between the hip bone and the ankle (malleolus lateralis) using a wall grid behind the participant. However, in the current experiment this instruction was deemed too complicated for children. The experimenter might have palpated the bone protuberance, but this was deemed intrusive.
 The video recordings of the jumping children were analyzed using the Toshiba DVD Movie Factory software. In general the video segments were rather chaotic. Children started and stopped frequently, sometimes jumping just once or twice. In general the video sequences were highly variable. Some children moved in a manner best described as jumping, whereas other children moved in a more bouncing-like manner. In the case of jumping, some children would jump into the air once and then pause before jumping again. A variety of other motions—including spinning, head swinging, arm flapping and even touching of toes—occurred in the videotaped movement. At least three children engaged in obvious dance movements (even though dancing was not mentioned in the instructions). Consistent jumping or bouncing sequences tended to be very short.
 The video for each child was scanned for possible sequences for analysis. Typically one or two passages were identified for each child. For two participants, no consistent bouncing or jumping sequence was evident in the video and so these children were excluded from further consideration. In total 29 segments from 19 participants were analyzed. Segments used for analysis were either 5 or 10 seconds in duration. For 10 participants, two segments were available. The rate of movement was measured by counting the number of foot-floor contacts over the duration of the segment. The tempo of movement was expressed in foot-floor contacts per minute. With the exception of one participant, left and right feet were synchronized in making floor contact. One female participant alternated between left and right feet in one of two recorded video segments. The segment in which feet alternated was not used for analysis. For those participants for which repeated measures were available, the measured movement rates for the repeated measures were found to be the same when measured in foot to floor contacts per minute. A child jumping at 125 foot-floor contacts per minute in one segment also jumped/bounced at 125 foot-floor contacts per minute in the second segment. This suggests a high level of consistency in the movement rate for individual participants.
 Table 1 shows the height, weight, sex, age and jumping rate for all 19 participants.
Table 1. Measurements.
As noted, the ages of the participants ranged from 2 to 7 with an average of 4.7 years. Heights ranged from 0.95 to 1.32 meters (mean of 1.13m), while weights ranged from 11.6 to 26.3 kilograms (mean of 19.9kg). Movement rates ranged from 132 to 192 foot-floor contacts per minute (mean of 150). In order to determine the possible effect of height and weight on movement rate, a multiple regression analysis was carried in which the foot-to-floor contact rate was the predicted variable.
 Table 2 shows the pertinent correlation matrix for the 19 cases.
Table 2. Correlation Matrix Using Height and Weight to Predict Rate.
Using weight and height as predictor variables, and foot-to-floor rate as the predicted variable, a multiple regression analysis produced no significant results (Multiple R=0.38; R^2=0.15; F (2,16) =1.37; p=0.28 N.S.).
 In general the videos exhibited a surprising range of movement types. In initiating our experiment we had assumed that participants would engage primarily in "bouncing" motions. However, a wide range of gaits were evident in the videos. In the first instance the amount of vertical movement varied considerably. Some participants' feet barely left the floor, whereas other participants' feet traversed a large distance above the floor. In addition, large differences were observed in the amount of knee bending. Some participants' knees bent little, whereas other participants bent their legs at 90 degrees or more. In preparing to move some children squatted as if preparing to "launch". When moving, some children remained close to the same floor location while other children made significant forward/backward or left/right excursions.
 Apart from leg movements, torso, head and arm movements also varied widely. Some participants swung their arms in a very stylized, intentional way while some participants hung their arms limp at their sides. A few participants used their arms to help propel them upward while others used their arms primarily to maintain balance. The direction in which the participant was looking created variability in head movement. Some participants watched the camera lens while others focused on their own feet.
 In reviewing the videos, the experimenters concluded many of the movements would be better characterized as "jumping" rather than "bouncing." Jumping is a very energy intensive movement and sustainability of this movement would prove difficult.
 In order to assess the bouncing or jumping character of the movement, four raters were recruited (including the two authors) to judge the degree of "bounciness." The four raters viewed the pertinent video segments and judged the degree of bouncing on a scale from 0-10. Table 3 shows a correlation matrix indicating the inter-rater agreement for the gait judgments.
Table 3. Inter-rater Agreement for Gait Judgment.
The mean inter-rater correlation was +0.68, suggesting a shared variance of 0.46. While not good, the relatively high shared variance suggests that these values may provide an adequate index of "bouncing" versus "jumping" gait for the participants. Accordingly, these values provide another co-variate in a multiple regression analysis predicting the foot-to-floor contact rate. In this case, the gait ratings proved to be a significant predictor of movement rate (Multiple R^2=0.81; R^=0.66; F (3, 15) =9.85; p=0.0008).
 Table 4 reproduces the correlation matrix including gait.
Table 4. Correlation Matrix Including Gait.
 The purpose of this study was to test the notion that there is a relationship between body morphology and preferred dance tempo. While skewed in the predicted direction, the results do not support the original hypothesis that height and weight influence preferred movement rates in children. At face value, these results appear inconsistent with the findings of Dahl and Huron and Todd et. al (2006) which suggested a significant correlation between preferred tempos and leg length/mass, respectively.
 However, further examination of the videos warranted a post hoc analysis which took into account movement type or gait. When assessed these gait judgments proved to be a significant predictor of the movement rates found in the children. It was determined that further research, in which gait is controlled, is necessary to definitively show the relationship between body size and preferred tempo.
 Further study is needed to determine the relationship between preferred dance tempo and its relationship to body morphology. A future experiment would control the gait of movement. One suggestion for carrying out this task would be to do a longer study in which participants are trained, in several sessions, how to bounce rather than jump. A longitudinal study in which children's morphological changes and changes in dance movement is observed may also provide more evidence for a link between body morphology and preferred dance tempo. While the age range of the Huron and Utley experiment provided a wide range of body sizes, there is a significant developmental difference across the span of the children used. A suggestion for future study would be to use 5th and 6th grade children. At this stage, procession development is more uniform but there still exists a variety of body sizes.
 Despite inconclusive evidence in the Huron/Utley study, a case can still be made that children have difficulty synchronizing movement to an external beat because that external beat is often too slow relative to their spontaneous motor tempo and size.
 The Huron/Utley study found an average rate of 150 foot-to-floor contacts per minute. This is consistent with results from tapping studies done in preschool age children (Provasi and Bobin-Bègue, 2003) which measured spontaneous motor tempo of 150 beats per minute. Combined with the research of Fraisse on accuracy of synchronization in relationship to SMT, one can conclude that children would have difficulty synchronizing dance movements to any music significantly faster or slower than 150 beats per minute.
 Phillips-Silver and Trainor suggest that vestibular activation is important for rhythmic tasks, including rhythmic perception. This indicates that the vestibular system plays a role in synchronizing movement to an external source. The vestibular system can activate passively (bouncing and infant, riding a horse) or actively (walking, dancing, bouncing). In the case of children and dance, the interest lies primarily with active use of the vestibular system. It seems reasonable that the intentional activation of the vestibular system through movement—like dancing or walking—would be shaped by body morphology. For example, people with long legs will have a slower natural walking rate, and therefore entrain the vestibular system to a slower tempo (consistent with McDougall and Moore). The connection between body morphology, movement and rhythm perception naturally lends itself to studies on dance and preferred dance tempos.
 Development appears to be the crucial factor in the ability of children to synchronize movement to an external beat. This article has examined two important aspects of development including, physical development and changes in biological rhythms, specifically spontaneous motor tempo. Many developmental mile-stones occur in preschool age children and have an impact on rhythm perception: the advancement of motor skills, increased memory, faster processing speed, etc. At this age it is common for children to begin formal training in sensori-motor skills such as music lessons, dance lessons or gymnastics. The relationship of developmental changes to rhythmic perception and production awaits further research.