Journal of Applied Physiology AJP: Gastrointestinal and Liver Physiology
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

J Appl Physiol 97: 2090-2097, 2004. First published July 30, 2004; doi:10.1152/japplphysiol.00560.2004
8750-7587/04 $5.00
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF) Free
Right arrow All Versions of this Article:
97/6/2090    most recent
00560.2004v1
Right arrow Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via ISI Web of Science (7)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Yoshitake, Y.
Right arrow Articles by Fukunaga, T.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Yoshitake, Y.
Right arrow Articles by Fukunaga, T.

Fluctuations in plantar flexion force are reduced after prolonged tendon vibration

Yasuhide Yoshitake,1,2,* Minoru Shinohara,3,* Motoki Kouzaki,1 and Tetsuo Fukunaga1,4

1Department of Life Sciences, The University of Tokyo, Tokyo 153; 2Department of Health Sciences, Oita University of Nursing and Health Sciences, Oita 870, Japan; 3Department of Integrative Physiology, University of Colorado, Boulder, Colorado 80309; and 4Department of Sport Sciences, Waseda University, Saitama 359, Japan

Submitted 28 May 2004 ; accepted in final form 14 July 2004


   ABSTRACT
TOP
 ABSTRACT
METHODS
 RESULTS
 DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 
The purpose of the study was to examine the effect of prolonged vibration on the force fluctuations during a force-matching task performed at low-force levels. Fourteen young healthy men performed a submaximal force-matching task of isometric plantar flexion before and after Achilles tendon vibration (n = 8, vibration subjects) or lying without vibration (n = 6, control subjects) for 30 min. The target forces were 2.5–10% of the previbration maximal voluntary contraction force. The standard deviation of force decreased by a mean of 29 ± 20% across target forces after vibration, whereas it did not decrease significantly in control subjects (–5 ± 12%). This change was significantly greater compared with control subjects (P < 0.01 for both). Power spectral density of the force was predominantly composed of signals of low-frequency bandwidth (≤5 Hz) with few higher frequency components. In vibration subjects, there was a significant decrease in power in the frequency range ≤2 Hz after vibration. The decrease in power at this frequency range was linearly related to the decrease in the force fluctuations (r = 0.96, P < 0.001). The results indicate that prolonged Achilles tendon vibration reduces the fluctuations in plantar flexion force in the frequency range ≤2 Hz during low-level contractions. It suggests that Ia afferent inputs contribute to the low-frequency force fluctuations in plantar flexion.

steadiness; motor control; Ia afferents

IN HUMAN MOVEMENT, MOTOR OUTPUT always involves variability about the intended movement. For example, when an individual tries to match one's output force to a submaximal target force as steadily as possible, the exerted force fluctuates about the target. It has been shown that the force fluctuations are influenced by a number of factors, including contraction type, muscle used for the task, age of the subjects, and activities of daily life (10). In particular, the force fluctuations are often greater in older adults compared with young adults (12, 30), and they are exacerbated by the reduced habitual activity during a prolonged bed rest in young adults (31).

The experimental and simulation studies on the final physiological cascades for the motor output of a single muscle, namely motor unit activation strategy, have revealed that the force fluctuations are influenced by multiple features of motor unit activity, including the strength of low-frequency (1 Hz) oscillation of motor unit discharge rate about a mean discharge rate and amount of variability of discharge rate (22, 34). Because motor unit activity is controlled by the neural inputs to the {alpha}-motoneuron pool in the spinal cord, the potential effect of afferent input to the force fluctuations has been postulated. Laidlaw et al. (22) speculated a possible involvement of altered stretch reflex function in the age-related increase in the fluctuations in motor output. The intrafusal muscle spindle senses small length changes in the muscle fiber. Information from the intrafusal muscle spindle is forwarded via Ia afferents to the spinal cord, which in turn gives excitatory inputs to the {alpha}-motoneuron pools of the homonymous muscle, thus facilitating the activation of motor units. Involvement of this pathway in fine motor control has been demonstrated by direct measurements of Ia afferent discharges (20, 39, 40), but its functional significance in fine motor control is controversial. Wessberg and Vallbo (37, 38), for example, cast their doubts on the basis of the lack of a close temporal relation between Ia afferent discharges and 8- to 10-Hz oscillations in the acceleration or muscle activity during slow finger movements. More recently, however, Cresswell and Löscher (4) found a reduction in the fatigue-induced increase in the force fluctuations in the frequency range of 5–30 Hz (tremor) for the plantar flexor muscles after prolonged vibration that is known to depress Ia circuit functions (9, 17, 28, 29).

The study by Cresswell and Löscher (4) demonstrated an effect of Ia circuit function on the force fluctuations only in the frequency range of 5–30 Hz that develops during fatiguing contractions. However, the major frequency range for the force fluctuations is <4–5 Hz during force-matching tasks performed at low force level in the nonfatigued state (3, 6–8, 33, 34, 36). Although the potential contribution of Ia circuit function to the higher frequency fluctuations in motor output (5–30 Hz) has been tested for a number of years (11, 14, 15, 23, 24, 26), there is no study that has examined the effect of Ia circuit function on the lower frequency fluctuations in force (<4–5 Hz).

The purpose of the study was to determine the effect of prolonged tendon vibration on force fluctuations during a force-matching task performed in the nonfatigued state. We expect to find that prolonged vibration reduces low-frequency fluctuations in force during a brief contraction because 1) prolonged vibration has been suggested to depress Ia afferent inputs, 2) a reduction in the Ia afferent inputs would increase the relative contribution of cortical projections to the motor units, and 3) low-frequency fluctuations in force (<4–5 Hz) are prominent during force-matching tasks at low force level.


   METHODS
TOP
 ABSTRACT
 METHODS
RESULTS
 DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 
Subjects.   Fourteen young healthy men volunteered to participate in this study. The subjects had no medical history or physical signs of neurological disorder. Only male subjects with relatively small subcutaneous fat thickness were recruited to ensure clear electrical recordings during low-force contractions. The age, height, and body mass of the subjects (means ± SD) were 27.1 ± 4.8 yr, 172.4 ± 6.0 cm, and 68.6 ± 10.9 kg, respectively. Eight subjects (vibration subjects) received vibration to the Achilles tendon, and the effects of vibration on maximal voluntary contraction (MVC) force and force fluctuations were examined. Six subjects (control subjects) performed the same tasks as the experimental subjects, however, without vibration. Reproducibility of MVC force and the force fluctuations were confirmed from the data in control subjects. There were no significant differences in physical characteristics between the groups. Subjects gave informed consent, and the experiments were approved by the Ethics committee of the Department of Life Sciences, The University of Tokyo, Japan.

Experimental protocol.   Subjects performed the MVC and submaximal force-matching tasks of isometric plantar flexion with the dominant (right) leg before and after prolonged Achilles tendon vibration (vibration subjects) or lying for the same time period without vibrations (control subjects). The MVC preceded the force-matching task before vibration or lying, whereas it followed the force-matching task after vibration or lying.

Vibration.   Prolonged vibration was applied to the Achilles tendon for 30 min by a specially designed mechanical stimulator (model DPS-285, Dia Medical System, Tokyo, Japan). The mechanical stimulator consisted of a direct-current motor with the shaft embedded in a plastic tube. The vibrator shaft was attached to the Achilles tendon at the ankle joint level with a force of 10–15 N. Vibration was applied with a frequency of 100 Hz and displacement of ±0.75 mm.

MVC.   The MVC task involved a gradual increase in plantar flexion force exerted by the triceps surae muscle from baseline to maximum in 3–4 s, which was then sustained at maximum for 2 s. The plantar flexion force was displayed in real time on the oscilloscope. The timing of the task was based on a verbal count given at 1-s intervals, with vigorous encouragement from the investigator when the force began to plateau. Each subject performed at least three MVC trials, with subsequent trials performed if the differences in the peak force of two MVCs were >5%. Subjects were allowed to reject any effort that they did not regard as "maximal." The trial with the highest peak force was chosen for analysis.

Force-matching task.   The procedure for the force-matching task was the same as previously employed by our group (31). Subjects were asked to contract their plantar flexor muscles and to maintain a plantar flexion force as steady as possible about the target displayed on an oscilloscope with visual feedback for 30 s. The gain of the display on the oscilloscope was adjusted so that displacement between lines representing the target and actual forces was constant across tasks. The target forces were 2.5, 5.0, 7.5, and 10% of the MVC that was measured before the 30 min of vibration in experimental subjects or before the 30 min of lying in control subjects (MVCpre). The force levels were chosen on the basis of previous studies that provide evidence that adaptations in force fluctuations are greater at lower forces (10, 12, 22, 31). Practice for the force-matching task was performed at each target force before the recording session started. In the recording session, the order of the target force was balanced across subjects, and rest periods of 30 s were allowed between trials. Each recording session was completed in 5 min.

Mechanical recordings.   Subjects lay in a prone position on a padded bed with the thigh secured to the bed by a strap. Force was measured with a strain gauge transducer positioned between a metal baseplate and a foot lever plate. The bottom end of the foot lever plate had a half-round-shaped attachment that surrounded and secured the heel. The heel was secured with a strap at the bottom end of the foot lever plate. The strain gauge transducer was aligned between the two plates near the distal part of the foot. The exact position of the entire device was carefully adjusted so the knee and hip was fully extended with the ankle joint angle at 90°. A low-sensitivity force transducer (model LTZ-200KA, Kyowa, Tokyo, Japan; 0.013 V/N) was used during the MVC task, and a more sensitive transducer (model LUR-A-100NSA1, Kyowa; 0.18 V/N) was used during the force-matching task. The force was amplified and low-pass filtered (<100 Hz) by a direct-current amplifier with a filter (model DPM 700, Kyowa).

Electrical recordings.   Surface electromyogram (EMG) was recorded from the medial gastrocnemius (MG), lateral gastrocnemius (LG), and soleus (Sol) with bipolar Ag-AgCl electrodes (diameter: 8 mm, interelectrode distance: 20 mm). The electrodes were connected to a preamplifier and a differential amplifier (x1,000) having a bandwidth of 5 Hz to 1 kHz (model 1253A, NEC Medical Systems, Tokyo, Japan).

Data analysis.   The force and EMG signals were collected at a sampling frequency of 2 kHz by a 16-bit analog-to-digital converter (Power-Lab/16sp, ADInstruments, Toyko, Japan) and stored on a personal computer. The middle 16 s of the contraction were used for further analysis in the force-matching task. The mean value and the SD of force, and root mean square amplitude of EMG (EMGrms) across 16 s were calculated (bin = 0.5 ms) by the standard methods. The relation between the SD and mean force (normalized to MVCpre or corresponding MVC) was evaluated with the slope and intercept obtained by a linear regression analysis with the least squares error method.

Power spectrum density of the force signal was obtained by the fast Fourier transformation method (16,384 points, Hamming window, 0.061 Hz/bin) after elimination of the direct-current component and resampling at 1 kHz. It is known that the force fluctuations during steady contractions are predominantly in the range of less than ~12 Hz when the level of force is <20% MVC (34, 36). We have confirmed in a pilot study that the frequency component above 12 Hz is very small (<0.3% of the total power) for plantar flexion forces ≤10% MVC. For the purpose of statistical comparison, the mean power across 1-Hz windows (16 or 17 bins) was further calculated up to 12 Hz. In addition, linear regression analyses were performed between the relative change in the SD and the relative change in the low- (≤5 Hz) or high-frequency power (>5 Hz). The frequency ranges that could explain the alterations in the SD of force after vibration were identified by these analyses. In MVC tasks, EMGrms was calculated over a 1-s window centered with the time at which peak force was attained.

Statistical analysis.   For the control subjects, the intraclass correlation coefficient (ICC) was calculated for MVC force and the SD of force before and after 30 min of lying. This was calculated under the assumption of a one-way random effects model (32), and linear correlation coefficient (Bravais-Pearson's r) between the data. Relative changes in MVC force and the slope and y-intercept of SD-force relation were compared between two subject groups with unpaired Student's t-test. Relative change in the SD of force between two subject groups was compared with two-way ANOVA (2 subject groups x 4 intensities) with repeated measures. In vibration subjects, the power spectral density of force in each 1-Hz frequency bin was compared with a three-factor ANOVA (4 intensities x 2 times x 15 frequencies) with repeated measures. Linear correlation coefficient (Bravais-Pearson's r) was obtained between the relative change in the SD of force and the relative change in the low- or high-frequency power of the force signal. EMGrms during MVC task was tested by using a two-way ANOVA (3 muscles x 2 times) with repeated measures. EMGrms during force matching-task was tested by using a three-way ANOVA (3 muscles x 2 times x 4 intensities) with repeated measures. An {alpha} level of 0.05 was chosen for all statistical analyses with post hoc comparisons (Newman-Keuls test) when appropriate. All values are expressed as means ± SE in the figures and means ± SD in the text and Table 1 unless stated otherwise.


View this table:
[in this window]
[in a new window]
  		Table 1. Force and EMG amplitude during MVC and force-matching tasks before and after vibration

 

   RESULTS
TOP
 ABSTRACT
 METHODS
 RESULTS
DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 
In control subjects, the ICCs for MVC force before and after 30 min of lying was 0.98, and the linear correlation coefficient (Bravais-Pearson's r) in MVC force before and after 30 min of lying was 0.99. Consequently, there was no significant change in MVC force (0.06 ± 14%). In contrast, MVC force in vibration subjects decreased by 19 ± 10% after vibration (Table 1). The relative change in MVC force in vibration subjects was significantly greater (P < 0.05) compared with control subjects (see Fig. 3). The reduction in MVC force accompanied decreases in EMGrms in vibration subjects (Table 1). The average decrease in EMGrms was 32 ± 25% (P < 0.01), 12 ± 19% (P < 0.05), and 12 ± 16% (P = 0.053) for MG, LG, and Sol, respectively.



View larger version (10K):
[in this window]
[in a new window]
  		Fig. 3. Relative change in MVC force, SD of force (collapsed across target forces), y-intercept, and slope of SD-force relation after 30 min of vibration (open bars, vibration subjects) and lying (filled bars, control subjects). The y-intercept and slope of SD-force relation are derived from forces normalized to corresponding MVC. *P < 0.05 and **P < 0.01 between groups.

 
When the subject matched the force to the target, the exerted force fluctuated about an average value (Fig. 1). The amount of force fluctuations (SD of force) was examined from the middle 16 s of data. In Fig. 2 (top), the SD of force was plotted against the mean force normalized to the MVCpre. The SD of force increased linearly as the level of target force increased. In control subjects, the SD of force did not change after 30 min of lying (Fig. 2, left). The ICC for the SD of force before and after 30 min of lying was 0.96. In addition, a high linear correlation coefficient (Bravais-Pearson's r = 0.98) was found between the SD of force before and after 30 min of lying. These analyses confirmed the test-to-retest reproducibility of the measurements in the present design. It was also confirmed that the SD of force before lying or vibration was not statistically different between the control and vibration groups (P > 0.05). In vibration subjects, the force fluctuations appeared to decrease after vibration (Fig. 1). On average, the SD of force decreased across target forces after vibration (Fig. 2, right), and the relative change in the SD was significantly greater in vibration subjects (–29 ± 20%) compared with control subjects (–5 ± 12%) across target forces (P < 0.01; Fig. 3).



View larger version (17K):
[in this window]
[in a new window]
  		Fig. 1. Representative data for force and electromyogram (EMG) during force-matching task before (Pre) and after (Post) vibration. Data are from 1 subject matching 10% maximal voluntary contraction (MVC). MG, medial gastrocnemius muscle; LG, lateral gastrocnemius muscle; SOL, soleus muscle. SD of force decreased from 0.79 to 0.49 N after vibration in this example.

 


View larger version (22K):
[in this window]
[in a new window]
  		Fig. 2. SD of force before and after 30 min of vibration (right, vibration subjects) and 30 min of lying (left, control subjects). Top: SD of force was plotted against the mean force normalized to MVC force before 30 min of vibration or lying (MVCpre). Bottom: SD of force was plotted against the mean force normalized to the corresponding MVC forces. Linear regression lines for the average data are superimposed.

 
It is of note that the target forces for the force-matching task were the same in absolute units within a subject before and after vibration (Table 1). Because of the reduction in MVC force in vibration subjects, one might argue that the decrease in the force fluctuations could be due to the difference in the levels of target relative to the corresponding MVC force. When the SD of force was plotted against the mean force normalized to the corresponding MVC force before and after vibration, the plots shifted to the right, but with very slight displacements (Fig. 2, bottom). To eliminate the effect of the decreased MVC force and to make a statistical comparison for the relation between the force fluctuations and the intensity normalized to the corresponding MVC force, the slope and y-intercept of the linear relation between the SD and mean force (normalized to the corresponding MVC force) before and after vibration were calculated for each subject. It was apparent that the y-intercept decreased in vibration subjects, and the statistical analysis confirmed that the relative change in vibration subjects (–23%) was significantly greater (P < 0.05) compared with control subjects (–7%) (Fig. 3). Relative change in the slope was small, and there was no difference between subject groups (–4% and –5%). These results indicate that the decrease in the force fluctuations in the vibration subjects was independent of the decrease in MVC force after vibration. There was no systematic change in EMGrms across muscles despite the slight difference in the level of target force relative to the corresponding MVC force in vibration subjects (Table 1).

Power spectral density of the force was calculated to examine how alterations in the frequency content of the force signal could be associated with reductions in force fluctuations after vibration. Most of the power was ≤5 Hz with a peak around 0.5 Hz before vibration, and the peak power was reduced after vibration (Fig. 4). In Fig. 5, the grouped data after vibration are overlaid with the data before vibration, indicating that the remaining filled portions are the amount of reductions in power after vibration. The greatest power in the force signal was observed ≤1 Hz across target forces, for which significant decline in power was found after vibration across all target forces (P < 0.01). The second greatest power was observed in 1–2 Hz, for which significant decline in power was found for the two of the four target forces (P < 0.01). On average, the power declined in other frequency ranges as well, but there was no significant change at any frequency band >2 Hz. Relative change in the power of the force signal for low-frequency (≤5 Hz) and high-frequency (>5 Hz) range was further plotted against the relative change in the force fluctuations after vibration (Fig. 6). A highly significant correlation was found between the relative change in low-frequency power of force and the SD of force (r = 0. 96, P < 0.001, Fig. 6A). There was no significant correlation for the high-frequency power (r = 0.25, P > 0.05; Fig. 6B). These results indicate that the decrease in the force fluctuations after vibration is associated with the reductions in the low-frequency band (≤5 Hz) of the force signal.



View larger version (16K):
[in this window]
[in a new window]
  		Fig. 4. Example of the power spectral analysis of the force signal during force-matching task before and after vibration. Note that the y-axis scales are different below (left, 5 N2/Hz) and above (right, 5 x 10–2 N2/Hz) 5 Hz for visual purposes. Force signals from Fig. 1 were used.

 


View larger version (28K):
[in this window]
[in a new window]
  		Fig. 5. Group data for power spectrum density of the force signals before and after vibration. Data after vibration are superimposed with the data before vibration. Note that the y-axis scales are different for below and above 5 Hz for visual purposes. **P < 0.01 before and after vibration.

 


View larger version (11K):
[in this window]
[in a new window]
  		Fig. 6. Correlation between the relative changes in the SD of force and power of force in the low-frequency range (≤5 Hz; A) and in the high-frequency range (>5 Hz; B). A significant linear regression line (r = 0.96, P < 0.001) is superimposed in A. Correlation coefficient in B was 0.25 (P > 0.05). NS, not significant.

 

   DISCUSSION
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 
The purpose of the study was to determine the effect of prolonged tendon vibration on force fluctuations during a force-matching task performed in the nonfatigued state and to examine the alterations in the frequency content of the force signals. The results demonstrated a reduction in the fluctuations in plantar flexion force after prolonged Achilles tendon vibration and identified the frequency range that was influenced by vibration.

Physiological mechanisms underlying the fluctuations in motor output are suggested to be dependent on the frequency range of the fluctuations (11, 27, 33, 34). According to McAuley and Marsden (27), the short-latency stretch reflex tends to create oscillations at 10 Hz, whereas the long-latency stretch reflex creates oscillations at 7 Hz, as well as central oscillations. Rhythmic oscillations in muscle activity around 20 Hz and 40–50 Hz observed in EMG may originate centrally. In particular, the force fluctuations during a fatiguing contraction (5–30 Hz, tremor) have long been suggested and demonstrated to be associated with the neural inputs from Ia afferents (e.g., Refs. 4, 14), whereas the association between the Ia circuit and the force fluctuations during brief low-force contractions in nonfatigued muscle is not known. In contrast to fatiguing contractions at moderate-force levels (4), there was little power in the higher frequency band (>5 Hz) during brief low-force contractions. In addition, significant alteration in power after vibration was limited to the lower frequency band (≤5 Hz), leading to the close association between the change in the force fluctuations and that of low-frequency power (r = 0.96; Fig. 6A). There was no association (P > 0.05; Fig. 6B) between the change in the force fluctuations and that of high-frequency power (>5 Hz), and the association remained weak (r = 0.39, P < 0.05) when those trials with an increase in high-frequency power were removed from the statistical analysis. Thus this study demonstrates the novel finding that neural input from Ia circuit strongly contributes to the force fluctuations at the frequency ≤5 Hz during a brief low-force contraction.

Reductions in Ia circuit function after muscle or tendon vibration have repeatedly been demonstrated in a variety of protocols as reductions in Ia afferent discharges (28), H reflex (4), and muscle stretch reflex (29). These decreases seem to involve presynaptic inhibition of Ia terminals, increased firing threshold of Ia fibers, and transmitter depletion (5, 17, 18). In a recent study that used a 30-min tendon vibration protocol with the same setup in our laboratory, a reduction in the H-reflex amplitude in triceps surae muscles has been confirmed. In addition, the reduction in H reflex accompanied a reduction in peak force and EMG during MVC, which would be due to a depression of Ia afferent input that led to a depressed {alpha}-motoneuron and {gamma}-motoneuron coactivation (2). A reduction in MVC force and EMG amplitude in the present study (Table 1) are consistent with this report on plantar flexion (35) and previous reports on knee extension MVC and EMG after 30 min of vibration (19, 21). It takes 10–20 min for the H reflex, MVC force and EMG to recover completely to the previbration level (Ushiyama J, Kouzaki M, Masani K, Kanehisa H, and Fukunaga T, unpublished observation), whereas the force-matching task in the present study was completed within 5 min after vibration. Furthermore, in the present study, a reduction in MVC force and EMG after vibration was observed after completion of the force-matching task, indicating that the effect of vibration was maintained during the force-matching task after vibration. These observations support the premise that neural input from the Ia afferents to the motoneuron pools was depressed during the force-matching task after vibration.

The frequency range in which significant reductions in power were observed after vibration was ≤2 Hz (Fig. 5), indicating the possibility of the close relation between Ia circuit function and low frequency of force. It has been suggested in a hand muscle that the force fluctuations in this frequency range could be attributable to the sensorimotor processing of the visual feedback information (33) and low-frequency modulation of motoneuron discharges (34). Slifkin et al. (33) provided evidence for reductions in power ≤2 Hz with a decrease in the time interval for the visual feedback. In the present study, visual feedback of the force signal was continuously provided, and it is unlikely that depression of the sensory feedback from muscle spindles affected the processing of the visual feedback information. Taylor et al. (34) showed in a simulation study that an addition of a low-frequency oscillation into the excitation of the motor unit population model was necessary to approximate the experimental finding of peak power at a frequency ≤2 Hz. Low-frequency modulation of motor unit discharges could be attributed to the rhythmicity in the spinal network or in the descending drive from supraspinal centers (1, 25). A recent study reported that elevated levels of physiological arousal with stress (electrical stimulation to the contralateral hand) increased the low-frequency power (1–2 Hz) of force during a pinch-grip task (3). In the present study, there was no obvious stressor that could be changed before and after vibration. Hence, it is less likely that rhythmicity in the descending drive was depressed, and is more likely that rhythmicity generated in the spinal network was altered, due to reduced afferent input to the spinal cord. It is of note that the altered frequency range in force is much lower than the frequency range of Ia afferent discharge (greater than ~10 Hz) (16). It indicates that the motor unit discharges are not directly modulated by the individual Ia discharges. This is also supported by the absence of a postspike positive peak in the Ia spike-triggered average in force during low-force isometric contractions (16). Hence, it is more likely that a reduction in Ia discharges modulated the rhythmicity in the spinal network, which is generated through multiple mechanisms, including the activation of neurotransmitters and ion channels. In humans, there is no study that demonstrates the relation between afferent input and the strength of rhythmicity in the spinal network. However, in the neonatal rat, Marchetti et al. (25) observed that constant-frequency (2–10 Hz) stimulation of the dorsal root evoked low-frequency oscillatory patterns (≤2 Hz) in the ventral root of the isolated spinal cord. Although it is not clear how this finding can be extrapolated to the humans at this point, reduced spinal rhythmicity due to the reduced afferent inputs could be a potential mechanism underlying the depression of the low-frequency oscillation in force. Other possible mechanism would include the potential influence of other afferents (e.g., cutaneous and pain), but there is not enough evidence to determine the potential effect of prolonged vibration on other afferents.

Changes in the distribution of muscle activity between the synergistic muscles have been suggested as one of the mechanisms that may influence the fluctuations in motor output in contractions of multiple muscles (13, 31) in addition to the motor unit activation strategy. Lack of changes in the distribution of EMG activity across triceps surae muscle implies that there was not a noticeable change in the global distribution of muscle activity, but it does not rule out the possible changes in the temporal muscle activity or motor unit activation strategy that could not be detected by surface EMG.

In conclusion, prolonged Achilles tendon vibration reduces the fluctuations in plantar flexion force during a low-level force-matching task. It seems that afferent input from Ia circuit contributes not only to the tremor component (8–12 Hz) during fatiguing contractions (4) but also to the force fluctuations of lower frequency range (<5 Hz) during a brief plantar flexion contraction performed in the nonfatigued state.


   GRANTS
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
 GRANTS
ACKNOWLEDGMENTS
 REFERENCES
 
This work was supported by a Uehara Memorial Foundation Research Grant (to Y. Yoshitake) and the Kozuki Foundation for Sports and Athletes (to T. Fukunaga).


   ACKNOWLEDGMENTS
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
REFERENCES
 
The authors are grateful to Masanobu Tachi and Junichi Ushiyama (University of Tokyo) for help with experiments. The authors appreciate comments from Roger Enoka, Kevin Keenan, Kurt Kornatz, Chet Moritz, and Carol Mottram (University of Colorado at Boulder).


   FOOTNOTES
 

Address for reprint requests and other correspondence: M. Shinohara, Dept. of Integrative Physiology, University of Colorado, Boulder, CO 80309-0354 (E-mail: shinohara{at}colorado.edu)

The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

* Y. Yoshitake and M. Shinohara contributed equally to this work. Back


   REFERENCES
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
 GRANTS
 ACKNOWLEDGMENTS
 REFERENCES
 

  1. Baker SN, Pinches EM, and Lemon RN. Synchronization in monkey motor cortex during a precision grip task. II. Effect of oscillatory activity on corticospinal output. J Neurophysiol 89: 1941–1953, 2003.[Abstract/Free Full Text]
  2. Bongiovanni LG, Hagbarth KE, and Stjernberg L. Prolonged muscle vibration reducing motor output in maximal voluntary contractions in man. J Physiol 423: 15–26, 1990.[Abstract/Free Full Text]
  3. Christou EA, Jakobi JM, Critchlow A, Fleshner M, and Enoka RM. The 1- to 2-Hz oscillations in muscle force are exacerbated by stress, especially in older adults. J Appl Physiol 97: 225–235, 2004.[Abstract/Free Full Text]
  4. Cresswell AG and Löscher WN. Significance of peripheral afferent input to the alpha-motoneurone pool for enhancement of tremor during an isometric fatiguing contraction. Eur J Appl Physiol 82: 129–136, 2000.[CrossRef][ISI][Medline]
  5. Curtis D and Eccles J. Synaptic action during and after repetitive stimulation. J Physiol 150: 374–398, 1960.[Free Full Text]
  6. De Luca CJ and Erim Z. Common drive in motor units of a synergistic muscle pair. J Neurophysiol 87: 2200–2204, 2002.[Abstract/Free Full Text]
  7. De Luca CJ, Foley PJ, and Erim Z. Motor unit control properties in constant-force isometric contractions. J Neurophysiol 76: 1503–1516, 1996.[Abstract/Free Full Text]
  8. De Luca CJ, LeFever RS, McCue MP, and Xenakis AP. Control scheme governing concurrently active human motor units during voluntary contractions. J Physiol 329: 129–142, 1982.[Abstract/Free Full Text]
  9. Desmedt JE and Godaux E. Mechanism of the vibration paradox: excitatory and inhibitory effects of tendon vibration on single soleus muscle motor units in man. J Physiol 285: 197–207, 1978.[Abstract/Free Full Text]
  10. Enoka RM, Christou EA, Hunter SK, Kornatz KW, Semmler JG, Taylor AM, and Tracy BL. Mechanisms that contribute to differences in motor performance between young and old adults. J Electromyogr Kinesiol 13: 1–12, 2003.[CrossRef][ISI][Medline]
  11. Freund HJ. Motor unit and muscle activity in voluntary motor control. Physiol Rev 63: 387–436, 1983.[Free Full Text]
  12. Galganski ME, Fuglevand AJ, and Enoka RM. Reduced control of motor output in a human hand muscle of elderly subjects during submaximal contractions. J Neurophysiol 69: 2108–2115, 1993.[Abstract/Free Full Text]
  13. Graves AE, Kornatz KW, and Enoka RM. Older adults use a unique strategy to lift inertial loads with the elbow flexor muscles. J Neurophysiol 83: 2030–2039, 2000.[Abstract/Free Full Text]
  14. Hagbarth KE and Young RR. Participation of the stretch reflex in human physiological tremor. Brain 102: 509–526, 1979.[Free Full Text]
  15. Halliday AM and Redfearn JW. An analysis of the frequencies of finger tremor in healthy subjects. J Physiol 134: 600–611, 1956.[Free Full Text]
  16. Halliday DM, Kakuda N, Wessberg J, Vallbo B, Conway BA, and Rosenberg JR. Correlation between Ia afferent discharges, EMG and torque during steady isometric contraction of human finger muscles. In: Alpha and Gamma Motor Systems, edited by Taylor A, Gladden MH, and Durbaba R. New York: Plenum, 1995, p. 547–549.
  17. Hayward LF, Nielsen RP, Heckman CJ, and Hutton RS. Tendon vibration-induced inhibition of human and cat triceps surae group I reflexes: evidence of selective Ib afferent fiber activation. Exp Neurol 94: 333–347, 1986.[CrossRef][ISI][Medline]
  18. Hultborn H, Meunier S, Pierrot-Deseilligny E, and Shindo M. Changes in presynaptic inhibition of Ia fibres at the onset of voluntary contraction in man. J Physiol 389: 757–772, 1987.[Abstract/Free Full Text]
  19. Jackson SW and Turner DL. Prolonged muscle vibration reduces maximal voluntary knee extension performance in both the ipsilateral and the contralateral limb in man. Eur J Appl Physiol 88: 380–386, 2003.[ISI][Medline]
  20. Kakuda N, Vallbo B, and Wessberg J. Fusimotor and skeletomotor activities are increased with precision finger movement in man. J Physiol 492: 921–929, 1996.[ISI]
  21. Kouzaki M, Shinohara M, and Fukunaga T. Decrease in maximal voluntary contraction by tonic vibration applied to a single synergist muscle in humans. J Appl Physiol 89: 1420–1424, 2000.[Abstract/Free Full Text]
  22. Laidlaw DH, Bilodeau M, and Enoka RM. Steadiness is reduced and motor unit discharge is more variable in old adults. Muscle Nerve 23: 600–612, 2000.[CrossRef][ISI][Medline]
  23. Lippold OC. Oscillation in the stretch reflex arc and the origin of the rhythmical, 8–12 C-S component of physiological tremor. J Physiol 206: 359–382, 1970.[Abstract/Free Full Text]
  24. Lippold OC, Redfearn JW, and Vuco J. The rhythmical activity of groups of motor units in the voluntary contraction of muscle. J Physiol 137: 473–487, 1957.[Free Full Text]
  25. Marchetti C, Beato M, and Nistri A. Alternating rhythmic activity induced by dorsal root stimulation in the neonatal rat spinal cord in vitro. J Physiol 530: 105–112, 2001.[Abstract/Free Full Text]
  26. Matthews PB and Muir RB. Comparison of electromyogram spectra with force spectra during human elbow tremor. J Physiol 302: 427–441, 1980.[Abstract/Free Full Text]
  27. McAuley JH and Marsden CD. Physiological and pathological tremors and rhythmic central motor control. Brain 123: 1545–1567, 2000.[Abstract/Free Full Text]
  28. Ribot-Ciscar E, Rossi-Durand C, and Roll JP. Muscle spindle activity following muscle tendon vibration in man. Neurosci Lett 258: 147–150, 1998.[CrossRef][ISI][Medline]
  29. Rymer WZ and Hasan Z. Prolonged time course for vibratory suppression of stretch reflex in the decerebrate cat. Exp Brain Res 44: 101–112, 1981.[ISI][Medline]
  30. Shinohara M, Li S, Kang N, Zatsiorsky VM, and Latash ML. Effects of age and gender on finger coordination in MVC and submaximal force-matching tasks. J Appl Physiol 94: 259–270, 2003.[Abstract/Free Full Text]
  31. Shinohara M, Yoshitake Y, Kouzaki M, Fukuoka H, and Fukunaga T. Strength training counteracts motor performance losses during bed rest. J Appl Physiol 95: 1485–1492, 2003.[Abstract/Free Full Text]
  32. Shrout PE and Fleiss JL. Intraclass correlations: uses in assessing rater reliability. Psychol Bull 86: 420–428, 1979.[CrossRef][ISI]
  33. Slifkin AB, Vaillancourt DE, and Newell KM. Intermittency in the control of continuous force production. J Neurophysiol 84: 1708–1718, 2000.[Abstract/Free Full Text]
  34. Taylor AM, Christou EA, and Enoka RM. Multiple features of motor-unit activity influence force fluctuations during isometric contractions. J Neurophysiol 90: 1350–1361, 2003.[Abstract/Free Full Text]
  35. Ushiyama J, Kouzaki M, Masani K, Kanehisa H, and Fukunaga T. Effect of prolonged vibration applied to the achilles tendon on muscle activity of ankle plantar flexor synergists during maximal voluntary contraction in humans. Abstracts of 33rd Annual Meeting of Society for Neuroscience 392.9, 2003.
  36. Vaillancourt DE and Newell KM. Aging and the time and frequency structure of force output variability. J Appl Physiol 94: 903–912, 2003.[Abstract/Free Full Text]
  37. Wessberg J and Vallbo B. Human muscle spindle afferent activity in relation to visual control in precision finger movements. J Physiol 482: 225–233, 1995.[ISI]
  38. Wessberg J and Vallbo B. Pulsatile motor output in human finger movements is not dependent on the stretch reflex. J Physiol 493: 895–908, 1996.[ISI][Medline]
  39. Wise AK, Gregory JE, and Proske U. Detection of movements of the human forearm during and after co-contractions of muscles acting at the elbow joint. J Physiol 508: 325–330, 1998.[Abstract/Free Full Text]
  40. Wise AK, Gregory JE, and Proske U. The responses of muscle spindles to small, slow movements in passive muscle and during fusimotor activity. Brain Res 821: 87–94, 1999.[CrossRef][ISI][Medline]



This article has been cited by other articles:


Home page
 J. Neurophysiol.Home page
C. J. Mottram, K. S. Maluf, J. L. Stephenson, M. K. Anderson, and R. M. Enoka
Prolonged Vibration of the Biceps Brachii Tendon Reduces Time to Failure When Maintaining Arm Position With a Submaximal Load
J Neurophysiol, February 1, 2006; 95(2): 1185 - 1193.
[Abstract] [Full Text] [PDF]

Home page
 J. Appl. Physiol.Home page
M. Shinohara, C. T. Moritz, M. A. Pascoe, and R. M. Enoka
Prolonged muscle vibration increases stretch reflex amplitude, motor unit discharge rate, and force fluctuations in a hand muscle
J Appl Physiol, November 1, 2005; 99(5): 1835 - 1842.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF) Free
Right arrow All Versions of this Article:
97/6/2090    most recent
00560.2004v1
Right arrow Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via ISI Web of Science (7)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Yoshitake, Y.
Right arrow Articles by Fukunaga, T.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Yoshitake, Y.
Right arrow Articles by Fukunaga, T.

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Visit Other APS Journals Online
Copyright © 2004 by the American Physiological Society.