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Proprioceptive coordination of movement sequences in humans
Clinical Neurophysiology 116 (2005) 87–92 www.elsevier.com/locate/clinph
Proprioceptive coordination of movement sequences in humans Richard K. Shields*, Sangeetha Madhavan, Keith R. Cole, Jared D. Brostad, Jeanne L. DeMeulenaere, Christopher D. Eggers, Patrick H. Otten Graduate Program in Physical Therapy and Rehabilitation Science, Carver College of Medicine, The University of Iowa, 1-252 Medical Education Building, Iowa City, IA 52242-1190, USA Accepted 18 July 2004 Available online 25 August 2004
Abstract Objective: To estimate the processing time and neuromuscular delay required to extract and process sensory information from the ankle in order to coordinate an upper extremity movement sequence. Methods: Nineteen able-bodied subjects were tested on their ability to perform a motor task that involved extension of their left index finger when their left ankle was passively plantar flexed at random velocities through a predetermined target angle. Results: We found that the able-bodied subjects were able to adjust their finger responses up to ankle velocities of 708/s (300 ms). Reaction time, defined as the delay between onset of ankle rotation and how quickly the index finger could be extended, was 215 ms. The processing time and conduction delay was estimated to be w85 ms. Conclusions: These results indicate that the nervous system processes kinesthetic input related to joint rotation of the ankle with the central mechanisms to execute a planned coordinated task with the upper extremity. Significance: The time required to process proprioceptive information from the leg to perform a coordinated task with the upper extremity may vary throughout the lifespan. Understanding the effects of age, exercise, or injury on proprioceptive processing time may have important clinical implications. q 2004 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved. Keywords: Dynamic position sense; Proprioception; Ankle joint; Movement sequence; Processing time; Spinal cord injury
1. Introduction Some of the actions that we perform daily, like speaking, walking, typing, writing, reaching and grasping, and throwing, fall under the category of movement sequences. A movement sequence can be defined as a series of coordinated but asynchronous joint rotations (Cordo, 1988). These movements require not only central control but also require the integration of online sensory feedback from the moving segment to produce a coordinated response (Gandevia and Burke, 1992). The temporal and spatial location of one moving joint determines when a subsequent joint rotation should begin.
* Corresponding author. Tel.: C1-319-335-9791; fax: C1-319-3359707. E-mail address: [email protected] (R.K. Shields).
Research on motor control, especially movement sequences, has shifted its attention from the role of central control to the importance of sensory input in coordinating motor behavior. Studies on locomotion have shown that kinesthetic input from joints in the lower extremity can trigger a step cycle in that leg (Conway et al., 1987). Sanes et al. (1985) showed that proprioceptive afferent inputs are important for accurate postural control and for the fine control of movement. More specifically, the nervous system is capable of using kinesthetic input to control the kinematics and onset of different joint rotations (Cordo et al., 1994). Cordo (1990) demonstrated that proprioception is not just used as a servo-control for detecting and correcting errors in movement sequences, but is also used by the nervous system to trigger a joint rotation at the proper time. Proprioception, classically defined by Sherrington (1906) as the perception of joint and body movement as well as position of the body or body segments in space, is
1388-2457/$30.00 q 2004 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.clinph.2004.07.019
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involved in balance control, specification of movement direction and extent, and in the learning of new movements (Cordo, 1990; Cordo et al., 2002; Deiner et al, 1984; Rothwell et al., 1982). Studies support that the CNS can extract kinematic information related to angular position and velocity of one rotating joint to trigger subsequent rotations in other joints (Cordo et al., 1994; Verschueren et al., 1999). However, most of the existing research on multijoint movement sequences focuses on sequential movements within the upper extremity only. The purpose of this study was to examine if the motion at one extremity can trigger a movement in another extremity; thus examining the extent to which the normal CNS is capable of using dynamic position sense to trigger an upper extremity movement sequence. Dynamic position sense is defined as the knowledge of the kinematics (angular position and velocity) of the moving joint obtained through various sensory receptors and central processing. Dynamic position sense during postural instability plays an important role in preventing injury or fall by triggering an upper extremity reaching sequence to ankle movement. Thus, it is more relevant to assess the proprioceptive sensitivity of the ankle using a triggered movement sequence task. We examined whether individuals could extend the index finger accurately when the left ankle was taken through a predetermined target angle at various speeds of rotation. We hypothesized that the normal CNS is capable of using dynamic position information from the ankle to trigger an upper extremity movement sequence. Some of these results have been presented previously in abstract form (Shields and Madhavan, 2002).
2. Methods Nineteen able-bodied human subjects (6 males, 13 females, 24–26 years) with no known neuromuscular deficits participated in this study. The exclusion criteria was any previous history of ankle joint trauma, any neurological deficits, significant degenerative joint diseases, rheumatoid arthritis, history of diabetes and restricted mobility. All subjects were chosen from an active and independent population. Subjects were provided with a brief description of the study and signed informed consents according to the institutions human subjects review board. 2.1. Experimental task Each subject sat at the experimental apparatus that generated passive ankle rotations at random velocities. One task was to extend the index finger when the ankle passed through a predetermined target angle (Target trials). Sufficient practice was provided to ensure that the subjects understood the task. In another set of trials the subjects were asked to indicate, by extending their finger, as soon as they
perceived their ankle motion (Reaction time trials). The ankle was rotated from 108 of dorsiflexion to 308 of plantar flexion (408 displacement). The target angle was set at 108 of plantar flexion, midway through the range. The subjects were asked to indicate the target angle when the ankle was rotating in the plantar flexion direction only. Recordings were made on the left hand and left ankle for all subjects. 2.2. Experimental apparatus A Kincom isokinetic dynamometer (Kin-Com 125 E Plus Chattecx Corporation) was used to rotate the ankle passively at 10 random velocities ranging from 10 to 908/s. Each subject sat comfortably at the Kincom with knee flexed and ankle strapped to the footplate. The other leg was comfortably supported. A potentiometer affixed to the index finger was used as the finger indicator to display and measure motion of the index finger. The subject’s pronated forearm rested on an adjustable table by the side with the palm on a wooden board, index finger inserted in an elastic loop connected to the lever of the potentiometer. The index finger was inserted into the elastic loop at the level of the second MCP joint. The Kincom was interfaced to a computer, which displayed the displacement information as feedback. The computer screen, placed in front of the subject, provided graphical display of the target angle, ankle displacement, and finger extension for visual feedback during practice trials. Once the subjects understood the task, vision was blocked and earplugs were worn to eliminate all auditory cues. 2.3. Experimental protocol The experiments were divided into 3 sessions—practice trials, target trials and reaction time trials. The velocities ranged from 10 to 908/s. The ankle was passively returned to the start position at a constant velocity of 108/s for all trials. Practice trials: Twenty practice trials at 20 and 708/s preceded the target trials of the randomized velocities. Visual feedback was in the form of real time continuous display of ankle displacement, target angle and index finger motion (Fig. 1). At the start of ankle rotation (plantar flexion), a line representing the target angle appeared. The subjects could see on the screen when their foot reached the target angle and thus learned to trigger their index finger at the appropriate time. In addition to this, verbal feedback was provided by the experimenters as to whether the subjects were ‘early’, ‘late’ or ‘right on target’. No practice was provided at any other velocity. During the first 10 trials, continuous online visual and verbal feedback was provided. For the next 5 trials, terminal visual and verbal feedback at the end of every trial was provided. For the last 5 trials, only verbal feedback was given so that the subjects could focus on the target using only ankle joint dynamic position sense. Target trials: In these 20 trials, subjects triggered for the predetermined target angle when the ankle was rotated at
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2.6. Data analysis
Fig. 1. Representative example of a single subject displaying ankle displacement of 408 with the target at the mid range and the finger extension indicator.
The digitized data were plotted using Sigmaplot 2002 (Windows version 8.0, SPSS Inc) and statistical analysis was done using SAS version 7 (1998 SAS Institute Inc., NC). Errors in performance were evaluated using constant error and absolute error measures. Repeated measures ANOVA on the constant error estimate was used to test for learning that occurred with practice. A one way ANOVA with repeated measures on Velocity was performed on absolute error measures during the target trials. Post hoc tests using Tukey’s Studentized range was performed on the effects which showed significance. Results of all analysis was considered significant at P!0.05. Unless otherwise stated all grouped data are presented as means and standard errors.
3. Results
random velocities in the absence of visual or verbal feedback. The subjects were blindfolded and earplugs were provided. The subjects had to rely on sensory information from the ankle to perform the task. Reaction time trials: Subjects performed 10 reaction time trials for each group of velocities randomized within the velocity groups. The subjects were instructed to trigger as soon as they felt ankle motion in the downward direction. No visual or verbal feedback was given and knowledge of results was withheld. No prior practice was given.
A representative example of the data acquired from a single subject is shown in Fig. 1. The angled line depicts the change in ankle displacement from 108 of dorsiflexion to 308 of plantar flexion imposed by the isokinetic dynamometer at a velocity of 208/s. The horizontal trace represents the target angle. The bottom trace represents the finger position. In this particular trial, the subject had triggered his index finger movement with reasonable accuracy as the foot reached the target angle.
2.4. Data recordings
3.1. Training accuracy
A 12 bit A–D converter was used to digitally sample all the signals. Datapac II Version 3.0 (Run technologies Inc, CA), a waveform oriented software was used to display all the integrated data from the A–D converter. All data was sampled at a rate of 500 samples/s.
Motor learning of all the subjects was evaluated by tracking their constant error across the practice trials of 208/s (Fig. 2). Repetitions 1, 11 and 15 were conversion zones for changing feedback modes and thereby progressing to a higher level of difficulty. Statistical analysis of the practice trials showed a significant effect of Trial number (F18, 358Z4.51, P!0.0001). As the subjects progressed through the practice trials, there was a consistent decrease in both mean constant and mean absolute errors showing that all the subjects learned the task accurately and therefore showed a minimal competency with the task. The mean constant and absolute error decreased to nearly half a degree and less than 28, respectively, for the last few practice trials in which no feedback was available.
2.5. Definition of measurements Time to target: Time from the start of ankle plantar flexion to the time when the target angle mid-way through the range was reached. Time of indication: Time from the start of ankle plantar flexion to the time that the finger was extended. The onset of finger extension was defined across all subjects at the point that the displacement curve reached 5 standard deviations above baseline. Constant error: Measure of bias of ankle angle at finger indication. In constant error estimates, overshoot and undershoot error may cancel out each other. Absolute error: Measure of overall accuracy of performance. In the case of the subjects with sensory loss, no response during the task was assigned a maximum error of 208.
3.2. Use of proprioceptive information to perform the task The absolute errors of performance of the subjects were calculated to assess if proprioceptive information regarding the ankle’s dynamic position is necessary for accurate performance of the task (Fig. 3). In these trials no visual or verbal feedback was given and no knowledge of results was provided. Hence the subjects had to rely on the afferent input from the rotating ankle to perform the triggered
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Fig. 2. Mean constant error values are plotted for the 20 practice trials of the 19 subjects. Data points are means of all subjects and error bars are standard errors. Note that repetitions 1, 11 and 15 are the conversion zones where the type of feedback was changed. The last 5 trials were in the absence of visual and verbal feedback.
movement sequence. The subjects had low errors (approximately 48) even when the ankle was rotated at random velocities suggesting that they could successfully utilize dynamic position information to trigger the sequential movement. A significant effect of velocity (F9.190Z2.51, P!.0001) suggested that there was greater error with increasing velocity. 3.3. Temporal accuracy of performance in able-bodied To further examine how sensory information from the ankle is used to coordinate the movement sequence, time taken by the ankle to reach the target angle (time to target) and the time of finger extension (time of indication) was plotted as a function of velocity of ankle rotation (Fig. 4). In these target trials, the time of indication of the subjects scaled accurately with velocity in the range from 10 to 608/s (Fig. 4A). A closer analysis of the responses of these data at the higher velocities, however, showed that at velocities 708/s and higher, the subjects were unable to trigger their finger quickly enough for the target angle (Fig. 4B). No significant difference was found among the times of finger extension at these 3 higher velocities (PZ0.23). On average the time of finger extension for 70, 80 and 908/s conditions stopped scaling at around 300 ms.
extended their index finger as soon as they perceived ankle movement in the downward direction. The reaction time, which we define here as the delay between the onset of ankle plantarflexion and extension of the index finger, was averaged to be around 215 ms. The reaction time, also varied across the velocities, slower velocities being significantly greater than the higher velocities. The reaction times were faster than the triggered responses across all velocities (F1417Z262.35, P!0.0001). This supports our assumption that the subjects were not just reacting to simple movement but were processing proprioceptive information even at the faster velocities of rotation.
3.4. Triggered responses vs. simple reaction time To examine if the inability to scale at the higher velocities could have been due to the subjects inability to react any faster to ankle movement, reaction time trials were included in the protocol. In these trials, the subjects
Fig. 3. Mean absolute error values are displayed versus velocity of ankle rotation in the target trial sessions for the 19 subjects. Error bars are standard errors.
R.K. Shields et al. / Clinical Neurophysiology 116 (2005) 87–92
Fig. 4. The time of indication (open circles),time to target (filled circles) and reaction time (filled triangles) is shown as a function of velocity in the target trial sessions. (A) shows all the 10 velocities while the (B) shows only the 5 faster velocities. Data points are means of 19 subjects and error bars are standard errors. Note that the triggered responses stop scaling at 708/s and higher. A significant difference between the triggered responses of the target and reaction time trials was found.
4. Discussion Many previous studies have shown that the CNS can use proprioceptive information to trigger joint rotations within movement sequences (Bevan et al., 1994; Cordo et al., 1994, 1995; Verschueren et al., 1999). Most of these studies, however, have been restricted to sequential movements in the upper extremity only. To our know ledge only one study by Verschueren and colleagues (1999) has examined dynamic position sense of the ankle to trigger an upper extremity task. In their study, however, the highest ankle velocity tested was 308/s so an estimate of processing time was not possible. The primary goal of this study was to examine if proprioceptive information from a rotating lower limb segment can be used to trigger an upper extremity movement sequence and estimate the processing time necessary for this movement
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sequence task. For this purpose, the ankle was passively rotated at random speeds from 10–908/s and the task was performed in the absence of feedback. The low absolute errors of performance during the random velocities of ankle rotation confirmed our hypothesis that dynamic position sense from the ankle can be used to trigger an upper extremity movement. Proprioceptive information is derived from a complex array of sources arriving at the brain from a variety of different inputs including the muscle spindle, joint capsule, joint ligaments, skin, fat pads and possibly joint cartilage and/or subchondral bones (Clark et al., 1979; Gandevia and McCloskey, 1976; Hutton and Nelson, 1986). However, muscle spindles have been shown to be the most potent of these sensory inputs. Group I and II afferents from the muscle spindles are most sensitive to the velocity of muscle lengthening and absolute changes in muscle length (Cordo et al., 2002; Gandevia and Burke, 1992). Tendon vibration during a movement sequence task leads to distorted perception of joint position and velocity (Cordo et al., 1995). Hence, we suggest that the muscle spindles are the main sources of the sensory afferent information utilized in triggering the upper extremity movement in this study. An important consideration the nervous system has to keep in mind when planning a movement sequence task would be the time that it takes to transmit and process the extracted sensory information. Hence, the CNS has to detect a triggering angle much earlier in space than where the actual target angle is located. Also, since the ankle is rotated at different velocities, this triggering angle would shift further before the target at the faster speeds of rotation. If the CNS relied only on angular position/ distance to perform the motor task, then the subjects would have to wait until the ankle reached the particular target position or rotates through a specific distance to trigger the finger, resulting in consistent overshooting of the target angle. Between ankle velocities of 10–608/s, the subjects were accurate with the task. Perhaps the accuracy at the slower speeds depended more on angular position/ distance information while the accuracy at the higher speeds depended more on the velocity information. Discrimination of angular distance was found to be more accurate than angular position in a similar upper extremity movement sequence task (Bevan et al., 1994). Further investigation is necessary to identify the amount of contribution of each of these variables-angular position, angular distance and angular velocity- in performing this movement sequence task. The subjects were not accurate with the task between 70 and 908/s. The time of indication stopped scaling at around 300 ms at the faster velocities (70, 80, 908/s) indicating that the nervous system did not have the time to predict the angle for an accurate triggered response. The minimal time necessary to extend the index finger (reaction time) in the able-bodied subjects was found to
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be 215 ms. Thus these data show that at least 85 ms (300–215 ms) was required by the CNS to process the kinesthetic information to coordinate the movement sequence. This was the minimum amount of time needed by the CNS to make an appropriate judgment about the rate of ankle rotation, set the triggering angle and send commands to extend the index finger. This processing time was slightly longer than what was calculated by Cordo et al. in a study which involved hand opening during elbow rotations (Cordo et al., 1994). We attribute this difference in processing time to the difference in distance that the somatosensory information from the ankle must travel compared to the shorter distances from the elbow in Cordo’s study. It should be noted, however, that the inability to process speeds faster than 708/s depended on where in the ankle range (208) the target was placed. For example, if the target was further in the range (308), it is conceivable that more time would be available to respond to the faster velocities. This has implications for the elderly who may have impaired ankle joint range of motion. The mechanism of motor coordination described in this paper can be applied to everyday movements, for active and passive movement sequences (Cordo et al., 1994, 2000; Verschueren et al., 1999). This kinesthetic triggering information forms the class of movements that includes much of our motor behavior. This study showed that the triggered upper extremity movement was based on the dynamic position of the lower extremity joint. There are two main findings of this study: (1) the CNS is unable to make accurate predictions using sensory input from the ankle joint at velocities greater than 708/s when the ankle is displaced through a range of 408 and, (2) a central processing time of at least 85 ms is necessary to coordinate an accurate movement sequence between the hand and the foot. These findings may have clinical implications for the elderly and those with unstable joints through musculoskeletal injury. A higher risk for falls in the elderly may be because they are not able to use the proprioceptive information from the ankle to coordinate a reaching movement to stabilize their balance quickly either due to decreased dynamic position sense (Verschueren et al., 2002) or due to a longer processing time. Also understanding the influence of exercise and fatigue on the proprioceptive systems involved with triggering movements based on kinematics of a distal joint would shed more light on the neuromuscular basis for movement and associated injuries.
Acknowledgements An award (R01-HD39445) from the National Center for Medical Rehabilitation Research (NIH) to RKS supported part of this research. References Bevan L, Cordo P, Carlton L, Carlton M. Proprioceptive coordination of movement sequences: discrimination of joint angle versus angular distance. J Neurophysiol 1994;71:1862–72. Clark FJ, Horch KW, Bach SM, Larson GF. Contributions of cutaneous and joint receptors to static knee-position sense in man. J Neurophysiol 1979;42:877–88. Conway BA, Hultborn H, Kiehn O. Proprioceptive input resets central locomotor rhythm in the spinal cat. Exp Brain Res 1987;68:643–56. Cordo PJ. Kinesthetic coordination of a movement sequence in humans. Neurosci Lett 1988;92:40–5. Cordo P. Kinesthetic control of a multijoint movement sequence. J Neurophysiol 1990;63:161–71. Cordo P, Carlton L, Bevan L, Carlton M, Kerr GK. Proprioceptive coordination of movement sequences: role of velocity and position information. J Neurophysiol 1994;71:1848–61. Cordo P, Bevan L, Gurfinkel V, Carlton L, Carlton M, Kerr G. Proprioceptive coordination of discrete movement sequences: mechanism and generality. Can J Physiol Pharmacol 1995;73:305–15. Cordo PJ, Gurfinkel VS, Levik Y. Position sense during imperceptibly slow movements. Exp Brain Res 2000;132:1–9. Cordo PJ, Flores-Vieira C, Verschueren SM, Inglis JT, Gurfinkel V. Position sensitivity of human muscle spindles: single afferent and population representations. J Neurophysiol 2002;87:1186–95. Deiner HC, Dichgans J, Guschlbauer B, Mau H. The significance of proprioception on postural stabilization as assessed by ischaemia. Brain Res 1984;296:103–9. Gandevia SC, Burke D. Does the nervous system depend on kinesthetic information to control natural limb movements? Behav Brain Sci 1992; 15:614–32. Gandevia SC, McCloskey DI. Joint sense, muscle sense, and their combination as position sense, measured at the distal interphalangeal joint of the middle finger. J Physiol 1976;260:387–407. Hutton RS, Nelson DL. Stretch sensitivity of Golgi tendon organs in fatigued gastrocnemius muscle. Med Sci Sports Exerc 1986;18:69–74. Rothwell JC, Traub MM, Day BL, Obeso JA, Thomas PK, Marsden CD. Manual motor performance in a deafferented man. Brain 1982;105: 515–42. Sanes JN, Mauritz KH, Dalakas MC, Evarts EV. Motor control in humans with large-fiber sensory neuropathy. Hum Neurobiol 1985;4:101–14. Sherrington C. The integrative action of the nervous system. New Haven: Yale University Press; 1906. Shields RK, Madhavan S. Proprioceptive coordination of movement sequences-Triggerred responses vs Simple Reaction Time Society for Neuroscience 32nd Annual Meeting, Orlando, Florida 2002. Verschueren SM, Swinnen SP, Cordo PJ, Dounskaia NV. Proprioceptive control of multijoint movement: bimanual circle drawing. Exp Brain Res 1999;127:182–92. Verschueren SM, Brumagne S, Swinnen SP, Cordo PJ. The effect of aging on dynamic position sense at the ankle. Behav Brain Res 2002;136:593–603.
Proprioceptive coordination of movement sequences in humans Richard K. Shields*, Sangeetha Madhavan, Keith R. Cole, Jared D. Brostad, Jeanne L. DeMeulenaere, Christopher D. Eggers, Patrick H. Otten Graduate Program in Physical Therapy and Rehabilitation Science, Carver College of Medicine, The University of Iowa, 1-252 Medical Education Building, Iowa City, IA 52242-1190, USA Accepted 18 July 2004 Available online 25 August 2004
Abstract Objective: To estimate the processing time and neuromuscular delay required to extract and process sensory information from the ankle in order to coordinate an upper extremity movement sequence. Methods: Nineteen able-bodied subjects were tested on their ability to perform a motor task that involved extension of their left index finger when their left ankle was passively plantar flexed at random velocities through a predetermined target angle. Results: We found that the able-bodied subjects were able to adjust their finger responses up to ankle velocities of 708/s (300 ms). Reaction time, defined as the delay between onset of ankle rotation and how quickly the index finger could be extended, was 215 ms. The processing time and conduction delay was estimated to be w85 ms. Conclusions: These results indicate that the nervous system processes kinesthetic input related to joint rotation of the ankle with the central mechanisms to execute a planned coordinated task with the upper extremity. Significance: The time required to process proprioceptive information from the leg to perform a coordinated task with the upper extremity may vary throughout the lifespan. Understanding the effects of age, exercise, or injury on proprioceptive processing time may have important clinical implications. q 2004 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved. Keywords: Dynamic position sense; Proprioception; Ankle joint; Movement sequence; Processing time; Spinal cord injury
1. Introduction Some of the actions that we perform daily, like speaking, walking, typing, writing, reaching and grasping, and throwing, fall under the category of movement sequences. A movement sequence can be defined as a series of coordinated but asynchronous joint rotations (Cordo, 1988). These movements require not only central control but also require the integration of online sensory feedback from the moving segment to produce a coordinated response (Gandevia and Burke, 1992). The temporal and spatial location of one moving joint determines when a subsequent joint rotation should begin.
* Corresponding author. Tel.: C1-319-335-9791; fax: C1-319-3359707. E-mail address: [email protected] (R.K. Shields).
Research on motor control, especially movement sequences, has shifted its attention from the role of central control to the importance of sensory input in coordinating motor behavior. Studies on locomotion have shown that kinesthetic input from joints in the lower extremity can trigger a step cycle in that leg (Conway et al., 1987). Sanes et al. (1985) showed that proprioceptive afferent inputs are important for accurate postural control and for the fine control of movement. More specifically, the nervous system is capable of using kinesthetic input to control the kinematics and onset of different joint rotations (Cordo et al., 1994). Cordo (1990) demonstrated that proprioception is not just used as a servo-control for detecting and correcting errors in movement sequences, but is also used by the nervous system to trigger a joint rotation at the proper time. Proprioception, classically defined by Sherrington (1906) as the perception of joint and body movement as well as position of the body or body segments in space, is
1388-2457/$30.00 q 2004 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.clinph.2004.07.019
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involved in balance control, specification of movement direction and extent, and in the learning of new movements (Cordo, 1990; Cordo et al., 2002; Deiner et al, 1984; Rothwell et al., 1982). Studies support that the CNS can extract kinematic information related to angular position and velocity of one rotating joint to trigger subsequent rotations in other joints (Cordo et al., 1994; Verschueren et al., 1999). However, most of the existing research on multijoint movement sequences focuses on sequential movements within the upper extremity only. The purpose of this study was to examine if the motion at one extremity can trigger a movement in another extremity; thus examining the extent to which the normal CNS is capable of using dynamic position sense to trigger an upper extremity movement sequence. Dynamic position sense is defined as the knowledge of the kinematics (angular position and velocity) of the moving joint obtained through various sensory receptors and central processing. Dynamic position sense during postural instability plays an important role in preventing injury or fall by triggering an upper extremity reaching sequence to ankle movement. Thus, it is more relevant to assess the proprioceptive sensitivity of the ankle using a triggered movement sequence task. We examined whether individuals could extend the index finger accurately when the left ankle was taken through a predetermined target angle at various speeds of rotation. We hypothesized that the normal CNS is capable of using dynamic position information from the ankle to trigger an upper extremity movement sequence. Some of these results have been presented previously in abstract form (Shields and Madhavan, 2002).
2. Methods Nineteen able-bodied human subjects (6 males, 13 females, 24–26 years) with no known neuromuscular deficits participated in this study. The exclusion criteria was any previous history of ankle joint trauma, any neurological deficits, significant degenerative joint diseases, rheumatoid arthritis, history of diabetes and restricted mobility. All subjects were chosen from an active and independent population. Subjects were provided with a brief description of the study and signed informed consents according to the institutions human subjects review board. 2.1. Experimental task Each subject sat at the experimental apparatus that generated passive ankle rotations at random velocities. One task was to extend the index finger when the ankle passed through a predetermined target angle (Target trials). Sufficient practice was provided to ensure that the subjects understood the task. In another set of trials the subjects were asked to indicate, by extending their finger, as soon as they
perceived their ankle motion (Reaction time trials). The ankle was rotated from 108 of dorsiflexion to 308 of plantar flexion (408 displacement). The target angle was set at 108 of plantar flexion, midway through the range. The subjects were asked to indicate the target angle when the ankle was rotating in the plantar flexion direction only. Recordings were made on the left hand and left ankle for all subjects. 2.2. Experimental apparatus A Kincom isokinetic dynamometer (Kin-Com 125 E Plus Chattecx Corporation) was used to rotate the ankle passively at 10 random velocities ranging from 10 to 908/s. Each subject sat comfortably at the Kincom with knee flexed and ankle strapped to the footplate. The other leg was comfortably supported. A potentiometer affixed to the index finger was used as the finger indicator to display and measure motion of the index finger. The subject’s pronated forearm rested on an adjustable table by the side with the palm on a wooden board, index finger inserted in an elastic loop connected to the lever of the potentiometer. The index finger was inserted into the elastic loop at the level of the second MCP joint. The Kincom was interfaced to a computer, which displayed the displacement information as feedback. The computer screen, placed in front of the subject, provided graphical display of the target angle, ankle displacement, and finger extension for visual feedback during practice trials. Once the subjects understood the task, vision was blocked and earplugs were worn to eliminate all auditory cues. 2.3. Experimental protocol The experiments were divided into 3 sessions—practice trials, target trials and reaction time trials. The velocities ranged from 10 to 908/s. The ankle was passively returned to the start position at a constant velocity of 108/s for all trials. Practice trials: Twenty practice trials at 20 and 708/s preceded the target trials of the randomized velocities. Visual feedback was in the form of real time continuous display of ankle displacement, target angle and index finger motion (Fig. 1). At the start of ankle rotation (plantar flexion), a line representing the target angle appeared. The subjects could see on the screen when their foot reached the target angle and thus learned to trigger their index finger at the appropriate time. In addition to this, verbal feedback was provided by the experimenters as to whether the subjects were ‘early’, ‘late’ or ‘right on target’. No practice was provided at any other velocity. During the first 10 trials, continuous online visual and verbal feedback was provided. For the next 5 trials, terminal visual and verbal feedback at the end of every trial was provided. For the last 5 trials, only verbal feedback was given so that the subjects could focus on the target using only ankle joint dynamic position sense. Target trials: In these 20 trials, subjects triggered for the predetermined target angle when the ankle was rotated at
R.K. Shields et al. / Clinical Neurophysiology 116 (2005) 87–92
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2.6. Data analysis
Fig. 1. Representative example of a single subject displaying ankle displacement of 408 with the target at the mid range and the finger extension indicator.
The digitized data were plotted using Sigmaplot 2002 (Windows version 8.0, SPSS Inc) and statistical analysis was done using SAS version 7 (1998 SAS Institute Inc., NC). Errors in performance were evaluated using constant error and absolute error measures. Repeated measures ANOVA on the constant error estimate was used to test for learning that occurred with practice. A one way ANOVA with repeated measures on Velocity was performed on absolute error measures during the target trials. Post hoc tests using Tukey’s Studentized range was performed on the effects which showed significance. Results of all analysis was considered significant at P!0.05. Unless otherwise stated all grouped data are presented as means and standard errors.
3. Results
random velocities in the absence of visual or verbal feedback. The subjects were blindfolded and earplugs were provided. The subjects had to rely on sensory information from the ankle to perform the task. Reaction time trials: Subjects performed 10 reaction time trials for each group of velocities randomized within the velocity groups. The subjects were instructed to trigger as soon as they felt ankle motion in the downward direction. No visual or verbal feedback was given and knowledge of results was withheld. No prior practice was given.
A representative example of the data acquired from a single subject is shown in Fig. 1. The angled line depicts the change in ankle displacement from 108 of dorsiflexion to 308 of plantar flexion imposed by the isokinetic dynamometer at a velocity of 208/s. The horizontal trace represents the target angle. The bottom trace represents the finger position. In this particular trial, the subject had triggered his index finger movement with reasonable accuracy as the foot reached the target angle.
2.4. Data recordings
3.1. Training accuracy
A 12 bit A–D converter was used to digitally sample all the signals. Datapac II Version 3.0 (Run technologies Inc, CA), a waveform oriented software was used to display all the integrated data from the A–D converter. All data was sampled at a rate of 500 samples/s.
Motor learning of all the subjects was evaluated by tracking their constant error across the practice trials of 208/s (Fig. 2). Repetitions 1, 11 and 15 were conversion zones for changing feedback modes and thereby progressing to a higher level of difficulty. Statistical analysis of the practice trials showed a significant effect of Trial number (F18, 358Z4.51, P!0.0001). As the subjects progressed through the practice trials, there was a consistent decrease in both mean constant and mean absolute errors showing that all the subjects learned the task accurately and therefore showed a minimal competency with the task. The mean constant and absolute error decreased to nearly half a degree and less than 28, respectively, for the last few practice trials in which no feedback was available.
2.5. Definition of measurements Time to target: Time from the start of ankle plantar flexion to the time when the target angle mid-way through the range was reached. Time of indication: Time from the start of ankle plantar flexion to the time that the finger was extended. The onset of finger extension was defined across all subjects at the point that the displacement curve reached 5 standard deviations above baseline. Constant error: Measure of bias of ankle angle at finger indication. In constant error estimates, overshoot and undershoot error may cancel out each other. Absolute error: Measure of overall accuracy of performance. In the case of the subjects with sensory loss, no response during the task was assigned a maximum error of 208.
3.2. Use of proprioceptive information to perform the task The absolute errors of performance of the subjects were calculated to assess if proprioceptive information regarding the ankle’s dynamic position is necessary for accurate performance of the task (Fig. 3). In these trials no visual or verbal feedback was given and no knowledge of results was provided. Hence the subjects had to rely on the afferent input from the rotating ankle to perform the triggered
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Fig. 2. Mean constant error values are plotted for the 20 practice trials of the 19 subjects. Data points are means of all subjects and error bars are standard errors. Note that repetitions 1, 11 and 15 are the conversion zones where the type of feedback was changed. The last 5 trials were in the absence of visual and verbal feedback.
movement sequence. The subjects had low errors (approximately 48) even when the ankle was rotated at random velocities suggesting that they could successfully utilize dynamic position information to trigger the sequential movement. A significant effect of velocity (F9.190Z2.51, P!.0001) suggested that there was greater error with increasing velocity. 3.3. Temporal accuracy of performance in able-bodied To further examine how sensory information from the ankle is used to coordinate the movement sequence, time taken by the ankle to reach the target angle (time to target) and the time of finger extension (time of indication) was plotted as a function of velocity of ankle rotation (Fig. 4). In these target trials, the time of indication of the subjects scaled accurately with velocity in the range from 10 to 608/s (Fig. 4A). A closer analysis of the responses of these data at the higher velocities, however, showed that at velocities 708/s and higher, the subjects were unable to trigger their finger quickly enough for the target angle (Fig. 4B). No significant difference was found among the times of finger extension at these 3 higher velocities (PZ0.23). On average the time of finger extension for 70, 80 and 908/s conditions stopped scaling at around 300 ms.
extended their index finger as soon as they perceived ankle movement in the downward direction. The reaction time, which we define here as the delay between the onset of ankle plantarflexion and extension of the index finger, was averaged to be around 215 ms. The reaction time, also varied across the velocities, slower velocities being significantly greater than the higher velocities. The reaction times were faster than the triggered responses across all velocities (F1417Z262.35, P!0.0001). This supports our assumption that the subjects were not just reacting to simple movement but were processing proprioceptive information even at the faster velocities of rotation.
3.4. Triggered responses vs. simple reaction time To examine if the inability to scale at the higher velocities could have been due to the subjects inability to react any faster to ankle movement, reaction time trials were included in the protocol. In these trials, the subjects
Fig. 3. Mean absolute error values are displayed versus velocity of ankle rotation in the target trial sessions for the 19 subjects. Error bars are standard errors.
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Fig. 4. The time of indication (open circles),time to target (filled circles) and reaction time (filled triangles) is shown as a function of velocity in the target trial sessions. (A) shows all the 10 velocities while the (B) shows only the 5 faster velocities. Data points are means of 19 subjects and error bars are standard errors. Note that the triggered responses stop scaling at 708/s and higher. A significant difference between the triggered responses of the target and reaction time trials was found.
4. Discussion Many previous studies have shown that the CNS can use proprioceptive information to trigger joint rotations within movement sequences (Bevan et al., 1994; Cordo et al., 1994, 1995; Verschueren et al., 1999). Most of these studies, however, have been restricted to sequential movements in the upper extremity only. To our know ledge only one study by Verschueren and colleagues (1999) has examined dynamic position sense of the ankle to trigger an upper extremity task. In their study, however, the highest ankle velocity tested was 308/s so an estimate of processing time was not possible. The primary goal of this study was to examine if proprioceptive information from a rotating lower limb segment can be used to trigger an upper extremity movement sequence and estimate the processing time necessary for this movement
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sequence task. For this purpose, the ankle was passively rotated at random speeds from 10–908/s and the task was performed in the absence of feedback. The low absolute errors of performance during the random velocities of ankle rotation confirmed our hypothesis that dynamic position sense from the ankle can be used to trigger an upper extremity movement. Proprioceptive information is derived from a complex array of sources arriving at the brain from a variety of different inputs including the muscle spindle, joint capsule, joint ligaments, skin, fat pads and possibly joint cartilage and/or subchondral bones (Clark et al., 1979; Gandevia and McCloskey, 1976; Hutton and Nelson, 1986). However, muscle spindles have been shown to be the most potent of these sensory inputs. Group I and II afferents from the muscle spindles are most sensitive to the velocity of muscle lengthening and absolute changes in muscle length (Cordo et al., 2002; Gandevia and Burke, 1992). Tendon vibration during a movement sequence task leads to distorted perception of joint position and velocity (Cordo et al., 1995). Hence, we suggest that the muscle spindles are the main sources of the sensory afferent information utilized in triggering the upper extremity movement in this study. An important consideration the nervous system has to keep in mind when planning a movement sequence task would be the time that it takes to transmit and process the extracted sensory information. Hence, the CNS has to detect a triggering angle much earlier in space than where the actual target angle is located. Also, since the ankle is rotated at different velocities, this triggering angle would shift further before the target at the faster speeds of rotation. If the CNS relied only on angular position/ distance to perform the motor task, then the subjects would have to wait until the ankle reached the particular target position or rotates through a specific distance to trigger the finger, resulting in consistent overshooting of the target angle. Between ankle velocities of 10–608/s, the subjects were accurate with the task. Perhaps the accuracy at the slower speeds depended more on angular position/ distance information while the accuracy at the higher speeds depended more on the velocity information. Discrimination of angular distance was found to be more accurate than angular position in a similar upper extremity movement sequence task (Bevan et al., 1994). Further investigation is necessary to identify the amount of contribution of each of these variables-angular position, angular distance and angular velocity- in performing this movement sequence task. The subjects were not accurate with the task between 70 and 908/s. The time of indication stopped scaling at around 300 ms at the faster velocities (70, 80, 908/s) indicating that the nervous system did not have the time to predict the angle for an accurate triggered response. The minimal time necessary to extend the index finger (reaction time) in the able-bodied subjects was found to
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be 215 ms. Thus these data show that at least 85 ms (300–215 ms) was required by the CNS to process the kinesthetic information to coordinate the movement sequence. This was the minimum amount of time needed by the CNS to make an appropriate judgment about the rate of ankle rotation, set the triggering angle and send commands to extend the index finger. This processing time was slightly longer than what was calculated by Cordo et al. in a study which involved hand opening during elbow rotations (Cordo et al., 1994). We attribute this difference in processing time to the difference in distance that the somatosensory information from the ankle must travel compared to the shorter distances from the elbow in Cordo’s study. It should be noted, however, that the inability to process speeds faster than 708/s depended on where in the ankle range (208) the target was placed. For example, if the target was further in the range (308), it is conceivable that more time would be available to respond to the faster velocities. This has implications for the elderly who may have impaired ankle joint range of motion. The mechanism of motor coordination described in this paper can be applied to everyday movements, for active and passive movement sequences (Cordo et al., 1994, 2000; Verschueren et al., 1999). This kinesthetic triggering information forms the class of movements that includes much of our motor behavior. This study showed that the triggered upper extremity movement was based on the dynamic position of the lower extremity joint. There are two main findings of this study: (1) the CNS is unable to make accurate predictions using sensory input from the ankle joint at velocities greater than 708/s when the ankle is displaced through a range of 408 and, (2) a central processing time of at least 85 ms is necessary to coordinate an accurate movement sequence between the hand and the foot. These findings may have clinical implications for the elderly and those with unstable joints through musculoskeletal injury. A higher risk for falls in the elderly may be because they are not able to use the proprioceptive information from the ankle to coordinate a reaching movement to stabilize their balance quickly either due to decreased dynamic position sense (Verschueren et al., 2002) or due to a longer processing time. Also understanding the influence of exercise and fatigue on the proprioceptive systems involved with triggering movements based on kinematics of a distal joint would shed more light on the neuromuscular basis for movement and associated injuries.
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