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J Dent Res 85(12):1112-1117, 2006
© 2006 International and American Associations for Dental Research

RESEARCH REPORT
Biological

Duty Time of Rabbit Jaw Muscles Varies with the Number of Activity Bursts

T. Grünheid1,*, G.E.J. Langenbach2, A. Zentner1, and T.M.G.J. Van Eijden2

1 Department of Orthodontics and
2 Department of Functional Anatomy, Academic Center for Dentistry Amsterdam (ACTA), Universiteit van Amsterdam and Vrije Universiteit, Louwesweg 1, 1066 EA Amsterdam, The Netherlands

* corresponding author, t.gruenheid{at}acta.nl


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS & METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The relative duration of muscle activity during a specified period (duty time) varies depending on activity level and time of the day. Since both the number and the length of activity bursts contribute to the duty time, it was hypothesized that these variables would show intra-day variations similar to those of the duty time. To test this, we determined duty times, burst numbers, and burst lengths per hour, in relation to multiple activity levels, in a 24-hour period of concurrent radio-telemetric long-term electromyograms of various rabbit jaw muscles. The marked intra-day variation of the burst number resembled that of the duty time in all muscles, and was in contrast to the relatively invariable mean burst length. Furthermore, the duty times were more highly correlated with the number than with the length of bursts at all activity levels. Thus, the variation of the duty time in rabbit jaw muscles is caused mainly by changes in burst numbers.

KEY WORDS: activity burst • duty time • electromyography • jaw muscle • rabbit


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS & METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The evaluation of long-term electromyograms (EMG), used for quantifying the functional use of muscles during normal daily activity, frequently includes the determination of the duty time as the relative duration of muscle activity during a specified period (Hensbergen and Kernell, 1997; Kern et al., 2001). The duty time is a valuable measure of neuromuscular activity and reflects the duration of mechanical loading of structures connected to the muscle. It is the summation of both postural and phasic muscle activities, and provides information on the force magnitude, which plays a crucial role in muscular (Kernell, 1992; Pette and Staron, 1997; Pette, 2002) and skeletal (Burr, 1997; Turner, 2000; Ferretti et al., 2003) tissue remodeling, only when related to various levels of muscle activity. The fiber-type composition of jaw muscles, for instance, has been shown to be related to their duty time only for activations exceeding 20% of the maximum activity (Van Wessel et al., 2005c). Differences in the duty time, between muscles or muscle groups, reflect differential activation by the central nervous system and differential loading, which influences mass, architecture, and mechanical properties of mechano-sensitive tissues. The duty time in itself cannot discriminate how muscle activity is generated, since it is the cumulative length of all individual activity bursts during a specified period. Therefore, it has been suggested to differentiate between the number and the lengths of the bursts (Mork and Westgaard, 2005; Van Wessel et al., 2005a,b). Both the number (Turner et al., 1994; Fritton et al., 2000; Robling et al., 2002) and the rate (Turner et al., 1995) of loading cycles influence bone adaptation, which is most efficient within a small range of loading frequencies (Warden and Turner, 2004). Muscle contractions contribute to bone loading, and additional information on the regularity and rhythmicity of the latter may be obtained by assessment of the number and lengths of intervals between muscle activations.

The duty time of a muscle varies, depending on activity level (Langenbach et al., 2004) and time of day (Hensbergen and Kernell, 1998; Grünheid et al., 2005). Since the duty time is related to both the number and the length of bursts, this intra-day variation might result from a change in the burst number, an alteration in the burst length, or a combination of both. Up to now, the influences of these distinct variables have not been elucidated, and it is unknown whether they differ between muscles and, like the duty time, depend on the level of neuromuscular activation.

The aims of this study were to compare the habitual activity of various jaw muscles by means of concurrent radio-telemetric long-term EMG recordings of rabbit masticatory muscles, as an example of a multi-muscle system. Its further aims were to assess the intra-day variation of multiple EMG variables, and to examine how variations in duty time are associated with burst numbers and burst lengths. Since both variables contribute to the duty time, it was hypothesized that they would show intraday variations similar to those of the duty time.


   MATERIALS & METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS & METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Animals
Six healthy adult male New Zealand White rabbits (Oryctolagus cuniculus, Harlan, Horst, The Netherlands), aged 5–12 mos, each weighing from 2800 to 5000 g, were housed individually, fed a pelleted laboratory diet and water ad libitum, kept in a room with a 12-hour light/dark cycle, beginning at 7 a.m., and were allowed an acclimatization period of 2 wks. Except for daily care, the animals were left undisturbed, to minimize external influence.

Experimental Procedure
Experiments were approved by the institutional Animal Ethics Committee, and were performed according to the experimental procedure and with the telemetric system previously described in detail elsewhere (Langenbach et al., 2002, 2004; Grünheid et al., 2005; Van Wessel et al., 2005a). In brief, a four-channel transmitter device for biopotential recording (F50-EEEE, Data Sciences International [DSI], St. Paul, MN, USA) was placed subcutaneously in the shoulder area of each animal. Bipolar fine-wire electrodes, each consisting of 2 silicone-insulated stainless steel wires (diameter, 0.45 mm) with bared ends (length, 5 mm), were used to record intramuscular EMGs. The electrodes were subcutaneously led to an incision in the right submandibular region, inserted, by means of a hypodermic needle (Nuijens et al., 1997) and parallel to the fiber direction, into pre-defined locations of the right anterior superficial and posterior deep masseter, the medial pterygoid, and the digastric muscles, and sutured at the muscle surfaces to prevent dislodging. Surgery was performed with the animals under general anesthesia.

Muscle potentials were simultaneously sampled at 250 Hz (21,600,000 samples/muscle/day), transmitted to a receiver (RMC-1, DSI), and stored for subsequent analysis in a data acquisition system (DataQuest A.R.T. 2.3, DSI). After continuous recording for 10 days, the animals were killed by an overdose of pentobarbital (Nembutal, Sanofi Sante, Maassluis, The Netherlands). We sampled the signals for another 5 min to determine the level of recorded noise for each muscle. Only signals with amplitudes 10x higher than the estimated noise level (0.08–0.24 µV) were processed further. Inaccurate electrode location at the time of dissection led to exclusion of the medial pterygoid muscle in 2 animals, and the posterior deep masseter muscle in another animal.

Data Processing and Analysis
For each animal, we analyzed EMGs of a full 24-hour period, recorded more than 7 days after the surgical procedure (Leon et al., 2004). EMG signals were filtered (5 Hz high-pass), rectified, and averaged over 20 ms (Spike2 5.06, Cambridge Electronic Design Ltd., Cambridge, UK). All EMG samples were indexed for their amplitudes (steps of 1 µV), and we excluded the 0.001% samples with the largest EMG amplitudes (i.e., 43 samples), to eliminate potential artifacts (Van Wessel et al., 2005a). The peak-EMG, defined as the largest amplitude of the remaining 99.999% of the samples, indicated the maximum activity for that day, and was used for EMG normalization (Knutson et al., 1994). Activity levels were expressed as percentages of this peak-EMG.

We analyzed data using automated custom-made codes within the Spike2 software, to quantify hourly burst numbers, burst lengths, burst interval numbers, burst interval lengths, and duty times. To locate all bursts exceeding activity levels of 2%, 5%, 10%, 20%, 50%, and 90% of the peak-EMG, we scanned the rectified and averaged EMG of each muscle (Fig. 1Go). A burst was defined as a series of consecutive samples with amplitudes exceeding a specified activity level; a burst interval was defined as the time interval between 2 bursts. ’Duty time’ was defined as the relative time per hour during which a muscle was active, and was determined as the cumulative length of the EMG samples having amplitudes larger than the pre-defined activity levels.


Figure 1
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  		Figure 1. Example of an EMG recording and details for quantification of individual bursts. (A) Segment of a processed and rectified EMG recorded from the posterior deep masseter of animal #4 during normal daily oral behavior. (B) Expanded view at the location of the arrow shown in (A). The broken lines indicate activity levels, expressed as percentages of the maximum activity (peak-EMG) of this muscle for that day. EMG activity was based on the number and lengths of bursts with amplitudes exceeding 2%, 5%, 10%, 20%, 50%, and 90% of the peak-EMG. We grouped bursts to determine the duty times at these activity levels. Note that the depicted period is not representative of the EMG recording for the entire day.

 
Statistical Analysis
The duty times were plotted against the corresponding burst numbers and mean burst lengths for the analyzed period, separately for each muscle, animal, and activity level. We calculated coefficients of determination from partial correlations to identify the proportions of variance in duty time attributable to burst number and burst length. Subsequent averaging provided mean values and standard deviations of the coefficients of determination for all animals.

Mean values and coefficients of variation (CV) of duty times, burst numbers, mean burst lengths, and burst interval lengths, obtained during the 24 consecutive hour-long periods, were calculated separately for each animal, muscle, and activity level. These values were subsequently averaged over all animals. Differences between muscles were tested for statistical significance, for each activity level separately, by analysis of variance for repeated measurements where data were normally distributed (Shapiro-Wilk test), and by the Friedman test with the Wilcoxon signed-ranks test as the post hoc pairwise comparison procedure where data were not normally distributed. Statistical analyses were performed with SPSS 12.0.1 (SPSS Inc., Chicago, IL, USA), with P-values of less than 0.05 considered statistically significant.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS & METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
The hourly duty times, burst numbers, and burst lengths are summarized in Table 1Go. At each activity level, the number of burst intervals was on par with the number of bursts. The mean burst rate at the lowest activity level—hence also including the bursts present at higher activity levels—was 1.899 bursts per sec, whereas, at the 90% activity level, it was 0.001 bursts per sec. In hours with high duty times, the burst interval lengths had lower standard deviations than in hours with low duty times. This finding was most pronounced at 5–10% of the peak-EMG.


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  		Table 1. Hourly Duty Time, Burst Number, and Burst Length of Rabbit Jaw Muscles at Various Activity Levels
 
Notwithstanding marked similarities, a few statistically significant differences between muscles were revealed: The duty time of the superficial masseter was higher than that of the medial pterygoid at the 50% activity level, and higher than that of the digastric at both the 50% and 90% activity levels. These differences were accompanied by larger numbers of bursts and burst intervals in the superficial masseter than in both medial pterygoid and digastric muscles at the 50% activity level. At the 10% activity level, the mean burst lengths differed only between the superficial masseter and the digastric muscles.

The CVs of the duty times and burst numbers document the considerable variation of these variables over the course of the day (Table 1Go). In contrast, the mean burst lengths were markedly less variable over the time-course. The variance of all examined EMG variables did not differ significantly between the muscles, suggesting similar variation in all muscles. The degree of these variations increased, however, with rising activity level.

Scatter plots of duty times against burst numbers and burst lengths (Fig. 2Go) revealed positive linear relationships between these variables in all examined muscles. The correlation between duty time and burst number was higher than that between duty time and burst length. The mean burst length of all examined muscles remained relatively constant over the time-course in each animal. However, it differed significantly among animals, indicating marked inter-individual variation.


Figure 2
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  		Figure 2. Correlated EMG activity of the examined jaw muscles. The scatter plots illustrate the relationships among the variables burst number, mean burst length, and duty time at the activity level exceeding 5% of the peak-EMG. Panels consist of data obtained during continuous EMG recording for 24 hrs, with each datapoint representing 1 hr. Data from all animals are presented in the same graph to facilitate comparison. r = Partial correlation of the variables displayed in the panel, adjusted for the remaining variable (averaged over all samples; number of samples is shown below muscle name).

 
The coefficients of determination (Table 2Go) of duty time and burst number increased with rising activity levels to values close to 1, indicating high amounts of variability in duty time that could be accounted for by burst number. In contrast, the coefficients of determination for duty time and burst length generally decreased with increasing levels of activity.


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  		Table 2. Coefficients of Determination Calculated from Partial Correlations to Identify the Proportions of Variance in Duty Time Attributable to Burst Number and Burst Length of Rabbit Jaw Muscles at Various Activity Levels
 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS & METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
The EMG analysis performed in the present study provides a detailed and comprehensive description of the activity characteristics of various rabbit jaw muscles. In accordance with investigations of developing rabbit jaw muscles (Van Wessel et al., 2005b), the duty times and the burst numbers differed significantly among the superficial masseter, medial pterygoid, and digastric muscles only at activity levels exceeding 50% of the peak-EMG. Differences in total activity duration reflected, to a great extent, differences in the postural role of muscles. Duty times have been reported to be typically higher in muscles contributing predominantly to postural activity than in those contributing predominantly to phasic activity (Hensbergen and Kernell, 1997, 1998; Hodgson et al., 2001). Activities exceeding 50% of the peak-EMG included only the most powerful tasks. This constituted infrequent activation of muscles, which, in the present study, added up to, on average, only 2.42 sec per hr. The vast majority of oral motor-tasks, however, was reflected by activity levels below 50% peak-EMG. The absence of significant intermuscular differences at these activity levels showed that, during concerted functional use, the activation patterns of various jaw muscles have marked similarities and supports previous suggestions that jaw muscles are responsible for both postural and motor activities (Grünheid et al., 2005).

Considering the scarceness of significant differences between the determined duty times, it can be assumed that the duration of mechanical loading by muscle forces was similar in the attachment areas of all examined muscles. The burst numbers obtained at the various activity levels suggest separation of the mechanical loading into thousands of short bouts at low activity levels, which are in contrast to the very few loading cycles at high activity levels. The high burst numbers and the low standard deviations of burst interval lengths in the hours with the highest duty times showed that the mechanical loading occurred at a relatively high frequency and regularity, possibly caused by the execution of predominantly rhythmic motor tasks, such as licking, drinking, or chewing.

A positive relationship between loading frequency and bone formation has been reported (Hsieh and Turner, 2001; Robling et al., 2002), with bone response to rhythmic loads of 0.5 Hz and above (Turner et al. 1994, 1995). The results of the present study suggest that only jaw muscle activities up to 20% of the peak-EMG satisfy the conditions required to influence bone formation during normal daily activity, since only these activities generated loading above 0.5 Hz. This muscle activity might be a determinant of the morphogenesis of the craniofacial skeleton (Kiliaridis, 1995), which is believed to be a secondary adaptation to the interaction of functional structures (Moss and Salentijn, 1969), because, in daily life, masticatory muscle function takes place all day long and stimulates bone and dentition continuously (Miyamoto et al., 1996; Saifuddin et al., 2001).

The degree of variation in duty times and burst numbers was similar in all examined muscles at each activity level. Plotting the duty times and the burst numbers against the time of day revealed similar circadian variations for both variables in all muscles of each animal. In contrast, the degree of variation in the mean burst length was markedly lower, and, in general, the mean burst lengths were relatively invariable over the course of the day. The relatively high CVs at the 50% activity level suggest increasing variation. However, this might also result from a decreasing precision of burst length estimation, which approached the measuring limit of 20 ms. The average burst lengths differed significantly between and among the animals. Hence, in some animals, the same duty time was generated by a higher number of, on average, shorter bursts, whereas in others it was generated by a lower number of longer bursts. These intra-individually consistent, but inter-individually different, burst lengths may be based on variations in muscle innervation patterns, or might point to differences in the habitual control of the motor system (Mork and Westgaard, 2005).

Although duty time is, by definition, related to both burst number and burst length, the present study revealed its stronger correlation with burst number. The high coefficients of determination indicated that the variability in burst numbers accounted for high percentages of the variance in duty times. In contrast to the considerable intra-day variations in duty times and burst numbers, the mean burst length was relatively invariable with various duty times. Together, these results provide evidence that the intra-day variation in duty time was associated mainly with a change in burst number. Alterations in the burst lengths seemed to influence the duty time only at low activity levels. The increase in the coefficients of determination calculated for the duty time and burst number with rising activation level suggests that the interdependence between these variables depends on the level of neuromuscular activation.


   ACKNOWLEDGMENTS
 
The authors are grateful to Leo Van Ruijven for technical support, Irene Aartman for statistical advice, and Jan Harm Koolstra for his suggestions on the manuscript. This study was institutionally supported by the Netherlands Institute for Dental Sciences (IOT).

Received December 21, 2005; Last revision August 2, 2006; Accepted September 25, 2006


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 DISCUSSION
 REFERENCES
 
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