Motor Control, 2015, 19, 60-74 http://dx.doi.org/10.1123/mc.2013-0083 © 2015 Human Kinetics, Inc.
The Relationships Between Muscle Force Steadiness and Visual Steadiness in Young and Old Adults Rebecca L. Krupenevich, Nick Murray, Patrick M. Rider, Zachary J. Domire, and Paul DeVita Since vision is used in studies of muscle force control, reduced muscle force control might be related to reduced visual ability. We investigated relationships between steadiness in eye movements and quadriceps muscle torque (a surrogate for force) during isometric contractions of constant and varying torques. Nineteen young adults with an average age of 20.7 years and 18 old adults with an average age of 71.6 years performed three vision tasks, three vision and torque tasks at 40% maximal voluntary contraction (MVC), and three vision and torque tasks at 54 nm. Age groups had identical torque steadiness (CV) in 40%-MVC and 54-nm conditions (p > .05). Old had similar vertical (p > .05) but decreased horizontal visual steadiness (SD) (p < .05) compared with young. Correlations between visual steadiness and muscle torque steadiness failed to show a significant relationship (p > .05). We were unable to identify a substantial relationship between muscle torque steadiness and eye movement, as a component of visual steadiness, and conclude that reduced visual steadiness does not contribute to reduced muscle torque steadiness. Keywords: aging, knee extensions, vision, eye tracking, variability
The use of appropriate and precise muscle forces is fundamental in performing basic life activities such as walking, driving automobiles, and manipulating handheld tools. A decrease in the ability to control muscle forces can reduce our ability to successfully perform these and other activities. Along with well-established decreases in muscular strength and power (Metter, Conwit, Tobin, & Fozard, 1997; Vandervoort, 2002), older adults experience decreases in muscle force accuracy, the ability to produce force at a particular magnitude, and steadiness, the ability to consistently maintain a particular force magnitude (Enoka et al., 2003; Hortobágyi, Tunnel, Moody, Beam, & DeVita, 2001), thereby affecting their capacity to execute tasks with control and precision (Tracy, Maluf, Stephenson, Hunter, & Enoka, 2005). Ultimately, inadequacies in neuromuscular function may pose safety risks to the older population. The age-related reductions in muscle force accuracy and steadiness can have an inhibiting effect on movement speed and coordination The authors are with the Dept. of Kinesiology, East Carolina University, Greenville, North Carolina. Address author correspondence to Paul DeVita at [email protected]. 60
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(Morgan et al., 1994), which in turn may affect many activities of daily living such as walking or driving. Specifically, decreased muscle force steadiness has been linked to increased fall risk in older adults (Carville, Perry, Rutherford, Smith, & Newham, 2007) and impaired performance in daily functional activities such as standing from a seated position or climbing stairs (Seynnes et al., 2005). Many factors contribute to the decrease in force steadiness with age, including motor unit remodeling and reduced firing rate frequency (Burnett, Laidlaw, & Enoka, 2000; Erim, Beg, Burke, & de Luca, 1999). Structural remodeling, partially brought about by the atrophy of fast-twitch muscle fibers, is seen with the onset of sarcopenia (Brown & Hasser, 1996). This structural remodeling is accompanied by a decline in the number of motor units and an increase in the number of fibers innervated per motor unit (Brown & Hasser, 1996; Erim et al., 1999). These adapted motor units increase the difficulty with which older adults modulate muscle force and generate the appropriate amount of muscle force during various activities of daily living (Galganski, Fuglevand, & Enoka, 1993; Larsson, Grimby, & Karlsson, 1979; Masakado et al., 1994). In addition to reductions in force steadiness with age, there is also a decrease in visual capability (Spear, 1993). Older adults, in particular, experience a decline in visual acuity (Owsley, 2011; Spear, 1993); however, visual acuity can be returned to normal with corrective optometry and therefore is not thought of as a major contributor to diminished overall visual function in relation to daily functional ability (Sosnoff & Newell, 2006; West et al., 2002). It is more likely that the decrease in visual function with age is due to a decrease in visual control (Abel, Troost, & Dell’Ossa, 1983; Knox, Davidson, & Anderson, 2005; Kosnik, Fikre, & Sekulert, 1986). Similar to other skeletal muscles, fast-twitch extraocular muscle fibers deteriorate with age (Kosnik et al., 1986), resulting in the reduced ability of older adults to control rapid eye movements, or saccades, with the same precision and accuracy as young adults (Kolarik, Margrain, & Freeman, 2010). Older adults also need more time to recognize and respond to visual targets compared with young adults (Owsley, 2011), causing a delay in the onset of eye movements when tracking a target as well as delays during tracking, further contributing to the reduction in eye movement accuracy (Kolarik et al., 2010; Moschner & Baloh, 1994; Spooner, Sakala, & Baloh, 1980). This functional decline results in an age-related increase in the number of visual tracking errors as the eyes try to reposition on the target using saccades (Sharpe & Sylvester, 1978; Sharpe & Zackon, 1987). The adverse effects of aging on vision seem to be exacerbated during balance and movement tasks, which is indicative of deficits within the visuomotor pathway (Paquette & Fung, 2011). Further, eye movement has been found to evoke responses in motor control, specifically postural sway (Glasauer, Schneider, Jahn, Strupp, & Brandt, 2005); this has large implications for the effect of vision, particularly declining vision with reduced occulomotor control, on force steadiness in large muscle groups. For example, a reduced ability to visually process a scene and respond accordingly may relate to an increased frequency of falls or injury (Chapman & Hollands, 2006; Glasauer et al., 2005). It is typical of studies investigating muscle force steadiness to use some form of visual target as the stimulus for modulating muscle force (Christou & Carlton, 2001; Hortobágyi et al., 2001; Tracy & Enoka, 2002, 2006). When visual feedback is provided during a task, older adults exhibit increased muscle force variability
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compared with tasks without visual feedback (Tracy, 2007; Tracy, Dinenno, Jorgensen, & Welsh, 2007; Welsh, Dinenno, & Tracy, 2007), indicating an age-related reduction in the ability to use visual feedback to maintain a steady force (Baweja, Kennedy, Vu, Vaillancourt, & Christou, 2010; Ofori, Samson, & Sosnoff, 2010; Svendsen, Samani, Mayntzhusen, & Pascal, 2011). Similarly, older adults have exhibited increased muscle force variability during tasks with complex visual feedback versus simple visual feedback (Christou & Carlton, 2001; Ofori et al., 2010). Thus, it is possible that the observed degradation in muscle force steadiness may in fact be a degradation in visual control or may reflect a degradation in visual control. Since visual capability declines with age and since vision is used in most investigations of muscle force control with age, reduced muscle force control in older adults might be at least partially related to or explained by altered visual capacity. We now hypothesize that there are direct relationships between visual steadiness and muscle force steadiness in both young and old adults with the implication that reduced muscle force steadiness in older adults can be at least partially explained by their reduced visual steadiness. The purpose of this study was to identify the relationships between steadiness in eye movement and muscle torque steadiness (a surrogate for muscle force steadiness) in young and old adults during isometric quadriceps contractions of constant and varying moments.
Methods Participants Nineteen young adults with an average age of 20.7 ± 1.82 years and 18 old adults with an average age of 71.6 ± 3.01 years volunteered for this study. Old and young adults had similar mean heights of 1.71 ± 0.09 and 1.73 ± 0.08 m and mean masses of 73.4 ± 10.39 and 74.2 ± 14.4 kg. A medical history questionnaire was given before participation in the study to ensure that all individuals were healthy and free of any neurological or pathological diseases and previous injuries to the lower extremities. Participants’ high functional ability was confirmed using the short physical performance battery (SPPB; Sayers et al., 2004) and short form-36 (SF-36; Ware et al., 1995) tests. On the SPPB test, both groups had an average score close to the maximum total score of 12 (young 11.8 ± 0.4; old 11.4 ± 0.9). Participants also displayed scores well above the population average of 45 on the SF-36 measures of physical capacity (young 55.9 ± 3.2; old 52.7 ± 5.56) and mental capacity (young 53.8 ± 4.6; old 56.4 ± 4.8). Testing protocols were approved by the institutional review board for human research, and each participant gave written informed consent.
Equipment Isometric quadriceps torque data were collected using an isokinetic dynamometer at a sampling frequency of 100 Hz (HUMAC NORM, CSMi, Stoughton, MA). We used isokinetic torque data as a direct surrogate of muscle force, which was reasonable because the lever arm for the isokinetic instrument remained unchanged through all tests. Horizontal and vertical eye movement data were collected using a mobile eye-tracking system at a sampling frequency of 30 Hz (Applied Science Laboratories, Bedford, MA). The mobile eye-tracking system included Mobile eye
Muscle Force and Visual Steadiness in Young and Old Adults 63
XG software, an LCD video recorder, and eye-tracking glasses consisting of a pair of eyeglass frames with two digital resolution cameras mounted above the right eye. One camera tracked the scene and the other camera tracked the eye movements. Visual targets were displayed on a 19-in. computer monitor (Dell, USA) using a custom-made software program.
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Procedures Participants visited the laboratory twice within 7 days with the two visits being separated by at least 48 hr. Maximal quadriceps strength and functional ability were assessed on the 1st day after appropriate acclimation to the dynamometer. Participants also practiced all muscle torque–visual steadiness tests on the 1st day to acclimate to the protocol and equipment. On the 2nd day, data were collected for all nine test conditions.
Maximal Quadriceps Muscle Torque Participants were seated on the isokinetic dynamometer seat with the back angle at approximately 90°. The axis of the right knee was aligned with the axis of the input shaft of the dynamometer. The shin pad was placed on the shank above the lateral malleolus at a comfortable position for the participant. A thigh strap was used to immobilize the right thigh. A seat belt and a shoulder stabilization belt were also used as an attempt to limit upper body movement during testing. The right knee was held at a 60° angle throughout all tasks. Anatomical zero was set when the knee was in full extension, and leg weight was measured in this position. The dynamometer’s software corrected the torque output to account for the effect of gravity on leg weight. Maximal isometric quadriceps strength was assessed over three 5-s trials, allowing for 60 s of rest in between consecutive trials. The 3-s window with the highest average, across all of the trials, was determined to be the maximal voluntary contraction (MVC) torque.
Eye Movements The eye-tracker glasses were placed on the participant’s face and calibrated using a nine-point calibration screen. Participants were allowed to wear corrective lenses, either glasses or contact lenses, during testing. The calibration process was repeated at the beginning of the testing session on Day 2 and in the event that the glasses were moved or shifted on the participant’s face at any point during either testing session. Participants were instructed to track the target using only their eyes and to avoid moving their head during the tracking tasks as much as possible. Table 1 Age Group Results for Muscle Torque Steadiness in Absolute and Relative Conditions Relative (Nm) Absolute (Nm)
Young (n = 19) 1.45 ± 0.63 1.26 ± 0.41
Values are coefficients of variation ± SD
Old (n = 18) 1.31 ± 0.33 1.43 ± 0.53
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Test Conditions Data were collected over nine tasks, and each task had three trials. The visual feedback for all tasks consisted of a cursor in the form of a green circle (11-mm diameter) moving in the vertical direction in response to quadriceps torque magnitude and horizontally at a set speed requiring 8 s to cross the 37.5-cm wide monitor. The monitor had 1,280 pixels horizontally and 1,024 pixels vertically; because screen resolution remained the same, visual gain varied by participant in the 40%-MVC conditions but was the same for all participants in the 54-nm conditions.
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Tasks The tasks consisted of the following: • Three vision tasks: (1) Viewing stationary cursor in center of screen, (2) visually tracking cursor moving horizontally across the middle of the blank screen, and (3) visually tracking cursor moving horizontally across the middle of the screen on a horizontal white line. • Three vision and torque tasks at a relative torque value of 40% MVC (relative torque conditions): Using isometric quadriceps contractions, participants controlled the cursor (1) with a constant torque to match a horizontal line, (2) with a constantly increasing then decreasing torque to match the cursor with a constant upward then downward sloped line, and (3) with a parabolically increasing then decreasing torque to match a parabolic target (Figure 1). • Three vision and torque tasks at an absolute torque value of 54 nm (absolute torque conditions) using the same conditions as in the relative conditions. The order of the vision and torque tasks was determined randomly for each participant. The 54-nm value was determined from a separate pilot study that obtained maximal strength measures on 12 young and 12 old adults and provided the average 40% MVC of all 24 participants. These individuals had similar anthropometric characteristics as the present participants but did not participate in the current study. In addition, the 40% MVC target torque level reasonably represents the functional values observed in activities of daily living in the lower extremity.
Figure 1 — Templates used with torque conditions; right to left: horizontal line, constant slope, parabola.
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Data Analysis The eye tracker provided a continuous recording of eye position for each trial, as well as an indication of any possible disruptions that caused a loss of signal. The recording for each trial was initiated 1 s before the participant started the trial, as determined by the 3-s countdown at the beginning of the trial, and terminated 1 s after the participant finished the trial. In the event that the infrared beam producing the three corneal reflections on the participant’s eye was disrupted, that section of the data was removed from the trial. Disruptions to the data recording could have been due to blinking, excessive squinting, or in some other way obstructing the path of the infrared light to the cornea. We note at this time that pursuit eye movements were observed in the vision-only condition and saccadic eye movements were observed in the vision and torque conditions. However, further analysis of these data was beyond the scope of this study; therefore, we do not present that analysis here. In addition, we analyzed each condition separately, ensuring that no condition contaminated data from another condition. Figure 2 illustrates representative torque-time curves from 1 young and 1 old participant performing the straight-line torque task at the 54-nm target. The middle 60% of each set of data was plotted on a line of best fit for all three trials.
Figure 2 — Representative trials from (a) one young and (b) one old adult. The horizontal line represents the 54-nm target torque. The fluctuation in torque signal represents muscle torque steadiness.
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The middle 60% was used in an attempt to analyze data collected when the participant was performing the intended task. We did not wish to analyze the portion of the trial during which participants were moving their eyes or the cursor to the target line. The mean value of the three trials in each condition was used in the statistical analysis. The horizontal and vertical vision data and the torque data were detrended before calculating measures of variance and central tendency for each trial other than those in the stationary vision condition (Tracy et al., 2007). Detrending was performed to remove any drift in the data so that all variance measures were affected only by variation in torque or visual data and not by the magnitude of the data. Namely, detrending produced a signal with a mean value of zero with noise being the positive and negative fluctuations of torque or vision around the mean. Without detrending, variance measures would be erroneously increased by the changing torque or visual signal. Detrending was accomplished by subtracting the line of best fit from each point with single lines of best fit calculated for the horizontal-line conditions, a positive and a negative sloped linear fit for the constant slope conditions, and a second order polynomial fit for the parabolic conditions.
Statistical Analysis We compared young and old adults on strength, visual steadiness, muscle torque steadiness, and selected visual parameters to determine any age-related differences using t tests. Coefficient of variation (CV) in the horizontal 40% MVC and horizontal 54-nm conditions was used to quantify muscle torque steadiness. A Pearson product–moment correlation analysis was also performed with each test condition individually to establish a relationship between visual steadiness and muscle torque steadiness across participants. The correlation analyses performed on the four relative and absolute constant and parabolic slope conditions were used to analyze the relationships between vision and torque data. The standard deviation of torque and the resultant standard-deviation values of the vertical and horizontal vision components were used in the correlations. We chose to use standard deviation in the correlations because, due to the detrending of the data, the means were nearly zero. The alpha level was set at p < .05 for all tests.
Results Maximum Strength Maximum voluntary muscle torque was 31% lower in old compared with young adults (145 ± 51.5 vs. 209 ± 68.4 nm, p < .05).
Age and Muscle Torque Steadiness There were no significant differences in muscle torque steadiness between young and old adults in either the relative condition (young = 1.45 ± 0.63; old = 1.31 ± 0.33; p = .20) or the absolute condition (young = 1.26 ± 0.41; old = 1.43 ± 0.53; p = .14; Table 1).
Muscle Force and Visual Steadiness in Young and Old Adults 67
Age and Visual Steadiness
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Young and old adults displayed similar visual capacity, as measured by the three vision-only conditions (Figure 3). The static vision condition did not show a significant difference between the two groups for the horizontal (p = .08) or vertical (p = .28) visual components. Similarly, the vision no-line condition and vision horizontal-line condition did not show significant differences between young and old adults for the vertical vision component (p = .34 and p = .47, respectively). A significant difference was observed in the horizontal component for these two conditions, with older adults showing ?40% decreased horizontal visual steadiness compared with young adults (p < .05).
Figure 3 — Top (static condition): No age-related difference in the horizontal or vertical visual component. Center (no-line condition): Old adults were less steady in the horizontal visual component than young; no age-related difference for the vertical visual component. Bottom (horizontal-line condition): Old adults were less steady in the horizontal visual component than young; no age-related difference for the vertical visual component.
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Relationships Between Visual Steadiness and Muscle Torque Steadiness
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Correlations performed between visual steadiness and muscle torque steadiness (using pooled data from both young and old adults) failed to show statistical significance for any of the relative or absolute constant slope and parabola conditions using the following critical value for a two-tailed test at p < .05: (df = 36) = 0.320. Table 2 shows the correlation coefficient (r) values for each vision and torque condition. Figures 4 and 5 illustrate correlations showing the line of best fit between resultant vision and torque along with the corresponding R2 value for the constant and parabolic slope conditions. Table 2 Correlation Coefficients (r) for Absolute and Relative Vision Torque Conditions Young and Old (n = 38) Constant slope Absolute Relative Parabola Absolute Relative
.067 .270 .045 .106
Figure 4 — Correlations between muscle torque steadiness and visual steadiness (resultant value of horizontal and vertical components for all participants) in the constant slope condition for (A) 40% MVC and (B) 54 nm. *r value 0, p < .05.
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Figure 5 — Correlations between muscle torque steadiness and visual steadiness (resultant value of horizontal and vertical components for all participants) in the parabola condition for (A) 40% MVC and (B) 54 nm.
Discussion Functional Capacity Young and old adults in the current study were healthy, mobile, and functionally capable individuals. The old adults, in particular, were high performing individuals based on SF-36 and SPPB scores. The difference in maximum isometric quadriceps strength between the young and old adult groups in the current study (?31% lower, old vs. young) was slightly smaller than the difference between groups in similar studies. Schiffman et al. (Schiffman, Luchies, Richards, & Zebas, 2002) reported a ?35% difference in MVC between young and old adults, and Hortbágyi et al. (Hortobágyi et al., 2001) reported a 43% difference in isometric quadriceps MVC between young and old adults.
Muscle Torque Steadiness Young and old adults did not display a significant age-related difference in isometric quadriceps torque steadiness at an absolute 54-nm or 40%-MVC torque level. The extensive practice we provided, which was more than usually has been done in muscle torque steadiness investigations (Tracy et al., 2007; Welsh et al., 2007), may have decreased muscle torque variability, accounting for the relatively low torque variability displayed by all present participants. Cirillo et al. (Cirillo, Todd, & Semmler, 2011) reported that young and old adults displayed similar task
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specific improvement after short-term training with a complex visuomotor task. Our participants performed the visual steadiness and muscle torque steadiness tasks on two separate occasions, which may have induced an unintended learning effect. Vaillancourt and Russell (2002) provided some evidence refuting this notion by showing that there were no changes in the amount of torque variability over the course of a 20-s constant-torque trial after one practice trial. However, we provided our participants with much more practice. Our participants visited the laboratory twice; on the first visit, the participants performed a “practice protocol,” executing an identical set of tasks and conditions that they would perform on their second visit to the laboratory. Although the order of the vision and torque tasks was selected randomly, the 54-nm absolute value at which our participants were tested corresponded to 29% and 43% of the young and old adult average MVC values, respectively. Thus, the difference between the 54-nm absolute and 40%-MVC relative target levels for the old adults was only about ?3% while the difference for the young adults was ?11%. This negligible change in target torque levels for older adults could have also contributed to the learning effect through repetition. The substantial amount of practice that our participants underwent before data collection (i.e., performing all nine tasks) may be a contributing factor to the relatively high muscle torque steadiness displayed by the present participants.
Visual Steadiness Although the young and old adult groups were similar in terms of visual steadiness, there was a statistically significant age-related difference in horizontal eye movement for the no-line and straight-line vision-only conditions. Visual steadiness was quantified as the standard deviation of eye movement in pixels as a response to a visual target. Old adults showed less horizontal eye movement steadiness than young adults whereas the vertical visual steadiness values between the two groups were quite similar. This discrepancy is consistent with literature suggesting that older adults show increased variability in the horizontal direction compared with the vertical direction (Kosnik et al., 1986). Interestingly, there was not a significant difference between the two groups for the static task during which the visual target did not move. Therefore, we postulate that the movement of the visual target in the no-line and straight-line tasks evoked a different visual response than the nonmoving target from older adults, resulting in decreased horizontal eye movement steadiness. These results are in agreement with observations that young and old adults exhibit similar variations in eye movements during a static fixation task, yet, during a tracking task, older participants display decreased eye movement control compared with young adults (O’Connor, Margrain, & Freeman, 2010). This phenomenon may also relate to the relationship between target speed and eye movement speed (Sharpe & Sylvester, 1978). When the visual target was no longer stationary, older adults may have had more trouble matching the speed of their eye movements with the target, causing increased variation in eye movement compared with young adults. This study was the first attempt to quantify visual steadiness using eye movement recordings from an eye-tracking instrument while assessing muscle torque steadiness. Previously, eye-tracking instruments similar to the present device have been used to relate eye movement to large-scale tasks—for example, quantifying gaze patterns when walking to a target at the end of a hallway (Turano, Geruschat,
Muscle Force and Visual Steadiness in Young and Old Adults 71
& Baker, 2001) or identifying focal points while driving (Land & Lee, 1994). In addition, there may be some concern over the amount of head movement from the participants during tracking tasks as we did not immobilize the participants’ heads during testing. However, we gave several verbal commands instructing participants to track the target by moving only their eyes and to keep their head as still as possible.
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Relationships Between Visual Steadiness and Muscle Torque Steadiness We were unable to substantially establish a relationship between visual steadiness and isometric knee extensor torque steadiness. We also investigated correlations between the young and old groups separately to ensure that combining the groups did not mask a significant relationship; however, we found fundamentally identical results as in the combined analysis. Our findings may indicate that visual steadiness, as a component of visual control, is not a contributing factor in the equilibrium point hypothesis of motor control, in that it does not appear to be related to the control of muscle force activation. Contrary to our findings, there appears to be a well-documented relationship between the presence or absence of visual feedback and muscle torque steadiness, showing that the presence of visual feedback provokes an increase in the amount of torque variability in older adults compared with young adults (Tracy, 2007; Tracy et al., 2007; Welsh et al., 2007). In fact, this observation was a foundational issue for our hypothesis. Welsh et al. (2007) demonstrated that age-related differences in motor unit firing rate variability are only observed in the presence of visual feedback. In addition, age-related deficits in muscle torque steadiness have been identified as a response to complex versus simple visual feedback (Ofori et al., 2010) and in response to increased amounts of visual feedback through manipulating visual gain, or pixels per unit torque (Sosnoff & Newell, 2006). With these factors in mind, one could presume that while we were unable to identify a relationship between visual steadiness and muscle torque steadiness, there may be some other age-related physiological deficits affecting the way older adults view and respond to visual information that is likely related to torque output variability. Several factors, other than the presence of visual feedback, have also been shown to influence force variability—for example, the presence of physiological stressors (Christou, Jakobi, Critchlow, Fleshner, & Enoka, 2004; Christou, 2005), emotional state (Naugle, Coombes, & Janelle, 2010), altered levels of respiration (Baweja, Patel, Neto, & Christou, 2011), and aging (Enoka et al., 2003). Further interpretation might suggest these factors are indicative of the notion that there may be physiological factors other than muscle control that influence muscle torque steadiness.
Conclusion We were not able to identify a physiological relationship between muscle torque steadiness and eye movement, as a component of visual steadiness. Therefore, there is no evidence to support our hypothesis that there would be direct relationships between visual steadiness and muscle force steadiness in both young and old adults, with the implication that reduced muscle force steadiness in older adults would
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be at least partially correlated with reduced visual steadiness. Thus, it is possible that the interactions between force steadiness and aging observed in the literature might in fact be due to reduced neuromuscular control and not due to reduced visual function with aging. In addition, the relationship between force steadiness and visual feedback identified in previous research may be due to decrements in visual processing capabilities and not due to a decline in visual steadiness. Regardless, in the current study, we were not able to detect the influence of visual capacity on muscle torque steadiness in young or old adults.
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References Abel, L.A., Troost, T.B., & Dell’Ossa, L.F. (1983). The effects of age on normal saccadic characteristics and their variability. Vision Research, 23, 33–37. PubMed doi:10.1016/0042-6989(83)90038-X Baweja, H.S., Kennedy, D.M., Vu, J., Vaillancourt, D.E., & Christou, E.A. (2010). Greater amount of visual feedback decreases force variability by reducing force oscillations from 0–1 and 3–7 Hz. European Journal of Applied Physiology, 108, 935–943. PubMed doi:10.1007/s00421-009-1301-5 Baweja, H.S., Patel, B.K., Neto, O.P., & Christou, E.A. (2011). The interaction of respiration and visual feedback on the control of force and neural activation of the agonist muscle. Human Movement Science, 30, 1022–1038. PubMed doi:10.1016/j.humov.2010.09.007 Brown, M., & Hasser, E. (1996). Complexity of age-related change in skeletal muscle. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 51(2), B117–B123. PubMed doi:10.1093/gerona/51A.2.B117 Burnett, R.A., Laidlaw, D.H., & Enoka, R.M. (2000). Coactivation of the antagonist muscle does not covary with steadiness in older adults. Journal of Applied Physiology, 89, 61–71. PubMed Carville, S.F., Perry, M.C., Rutherford, O.M., Smith, C.H., & Newham, D.J. (2007). Steadiness of quadriceps contractions in young and older adults with and without a history of falling. European Journal of Applied Physiology, 100, 527–533. PubMed doi:10.1007/ s00421-006-0245-2 Chapman, G.J., & Hollands, M.A. (2006). Evidence for a link between changes to gaze behaviour and risk of falling in older adults during adaptive locomotion. Gait & Posture, 24, 288–294. PubMed doi:10.1016/j.gaitpost.2005.10.002 Christou, E.A. (2005). Visual feedback attenuates force fluctuations induced by a stressor. Medicine and Science in Sports and Exercise, 37(12), 2126–2133. PubMed doi:10.1249/01. mss.0000178103.72988.cd Christou, E.A., & Carlton, L.G. (2001). Old adults exhibit greater motor output variability than young adults only during rapid discrete isometric contractions. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 56(12), B524–B532. PubMed doi:10.1093/gerona/56.12.B524 Christou, E.A., Jakobi, J.M., Critchlow, A., Fleshner, M., & Enoka, R.M. (2004). The 1- to 2-Hz oscillations in muscle force are exacerbated by stress, especially in older adults. Journal of Applied Physiology, 97, 225–235. PubMed doi:10.1152/japplphysiol.00066.2004 Cirillo, J., Todd, G., & Semmler, J.G. (2011). Corticomotor excitability and plasticity following complex visuomotor training in young and old adults. The European Journal of Neuroscience, 34, 1847–1856. PubMed doi:10.1111/j.1460-9568.2011.07870.x Enoka, R.M., Evangelos, C.A., Hunter, S.K., Kornatz, K.W., Semmler, J.G., Taylor, A.M., & Tracy, B.L. (2003). Mechanisms that contribute to differences in motor performance between young and old adults. Journal of Electromyography and Kinesiology, 13, 1–12. PubMed doi:10.1016/S1050-6411(02)00084-6
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Erim, Z., Beg, F., Burke, D.T., & de Luca, C.J. (1999). Effects of aging on motor-unit control properties. Journal of Neurophysiology, 82, 2081–2091. PubMed Galganski, M.E., Fuglevand, A.J., & Enoka, R.M. (1993). Reduced control of motor output in a human hand muscle of elderly subjects during submaximal contractions. Journal of Neurophysiology, 69(6), 2108–2115. PubMed Glasauer, S., Schneider, E., Jahn, K., Strupp, M., & Brandt, T. (2005). How the eyes move the body. Neurology, 65, 1291–1293. PubMed doi:10.1212/01.wnl.0000175132.01370.fc Hortobágyi, T., Tunnel, D., Moody, J., Beam, S., & DeVita, P. (2001). Low- or high-intensity strength training partially restores impaired quadriceps force accuracy and steadiness in aged adults. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 56(1), B38–B47. PubMed doi:10.1093/gerona/56.1.B38 Knox, P.C., Davidson, J.H., & Anderson, D. (2005). Age-related changes in smooth pursuit initiation. Experimental Brain Research, 165. PubMed Kolarik, A.J., Margrain, T.H., & Freeman, T.C.A. (2010). Precision and accuracy of ocular following: Influence of age and type of eye movement. Experimental Brain Research, 201, 271–282. PubMed doi:10.1007/s00221-009-2036-6 Kosnik, W., Fikre, J., & Sekulert, R. (1986). Visual fixation stability in older adults. Investigative Ophthalmology & Visual Science, 27, 1720–1725. PubMed Land, M.F., & Lee, D. (1994). Where we look when we steer. Nature, 369, 742–744. PubMed doi:10.1038/369742a0 Larsson, L., Grimby, G., & Karlsson, J. (1979). Muscle strength and speed of movement in relation to age and muscle morphology. Journal of Applied Physiology, 46(3), 451–456. PubMed Masakado, Y., Noda, Y., Nagata, M., Kimura, A., Chino, N., & Akaboshi, K. (1994). MacroEMG and motor unit recruitment threshold: Differences between the young and the aged. Neuroscience Letters, 179(1–2), 1–4. PubMed doi:10.1016/0304-3940(94)90920-2 Metter, E.J., Conwit, R., Tobin, J., & Fozard, J.L. (1997). Age-associated loss of power and strength in the upper extremities in women and men. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 52(5), B267–B276. PubMed doi:10.1093/ gerona/52A.5.B267 Morgan, M., Phillips, J.G., Bradshaw, J.L., Mattingley, J.B., Iansek, R., & Bradshaw, J.A. (1994). Age-related motor slowness: Simply strategic? The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 49(3), 133–139. Moschner, C., & Baloh, R.W. (1994). Age-related changes in visual tracking. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 49(5), M235–M238. PubMed Naugle, K.M., Coombes, S.A., & Janelle, C.M. (2010). Subclinical depression modulates the impact of emotion on force control. Motivation and Emotion, 34, 432–445. doi:10.1007/ s11031-010-9184-7 O’Connor, E., Margrain, T.H., & Freeman, T.C.A. (2010). Age, eye movement and motion discrimination. Vision Research, 50, 2588–2599. PubMed doi:10.1016/j.visres.2010.08 .015 Ofori, E., Samson, J.M., & Sosnoff, J.J. (2010). Age-related differences in force variability and visual display. Experimental Brain Research, 203, 299–306. PubMed Owsley, C. (2011). Aging and vision. Vision Research, 51, 1610–1622. Paquette, C., & Fung, J. (2011). Old age affects gaze and postural coordination. Gait & Posture, 33, 227–232. PubMed doi:10.1016/j.gaitpost.2010.11.010 Sayers, S.P., Jette, A.M., Haley, S.M., Heeren, T.C., Guralnik, J.M., & Fielding, R.A. (2004). Validation of the late-life function and disability instrument. Journal of the American Geriatrics Society, 52, 1554–1559. PubMed doi:10.1111/j.1532-5415.2004.52422.x Schiffman, J.M., Luchies, C.W., Richards, L.G., & Zebas, C.J. (2002). The effects of age and feedback on isometric knee extensor force control abilities. Clinical Biomechanics (Bristol, Avon), 17, 486–493. PubMed doi:10.1016/S0268-0033(02)00041-4
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Seynnes, O., Hue, O.A., Garrandes, F., Colson, S.S., Bernard, P.L., Legros, P., & Singh, M.A. (2005). Force steadiness in the lower extremities as an independent predictor of functional performance in older women. Journal of Aging and Physical Activity, 13, 395–408. PubMed Sharpe, J.A., & Sylvester, T.O. (1978). Effect of aging on horizontal smooth pursuit. Investigative Ophthalmology and Visual Science, 17(5), 465–467. Sharpe, J.A., & Zackon, D.H. (1987). Senescent saccades: Effects of aging of their accuracy, latency and velocity. Acta Oto-Laryngologica, 104, 422–428. PubMed doi:10.3109/00016488709128270 Sosnoff, J.J., & Newell, K.M. (2006). Information processing limitations with aging in the visual scaling of isometric force. Experimental Brain Research, 170, 423–432. PubMed doi:10.1007/s00221-005-0225-5 Spear, P.D. (1993). Neural bases of visual deficits during aging. Vision Research, 33(18), 2589–2609. PubMed doi:10.1016/0042-6989(93)90218-L Spooner, J.W., Sakala, S.M., & Baloh, R.W. (1980). Effect of aging on eye tracking. Archives of Neurology, 37, 575–576. PubMed doi:10.1001/archneur.1980.00500580071012 Svendsen, J.H., Samani, A., Mayntzhusen, K., & Pascal, M. (2011). Muscle coordination and force variability during static and dynamic tracking tasks. Human Movement Science, 30, 1039–1051. PubMed Tracy, B.L. (2007). Visuomotor contribution to force variability in the plantarflexor and dorsiflexor muscles. Human Movement Science, 26, 796–807. PubMed doi:10.1016/j. humov.2007.07.001 Tracy, B.L., Dinenno, D.V., Jorgensen, B., & Welsh, S.J. (2007). Aging, visuomotor correction, and force fluctuations in large muscles. Medicine and Science in Sports and Exercise, 39, 469–479. PubMed doi:10.1249/mss.0b013e31802d3ad3 Tracy, B.L., & Enoka, R.M. (2002). Older adults are less steady during submaximal isometric contractions with the knee extensor muscles. Journal of Applied Physiology, 92, 1004–1012. PubMed Tracy, B.L., & Enoka, R.M. (2006). Steadiness training with light loads in the knee extensors of elderly adults. Medicine and Science in Sports and Exercise, 38, 735–745. PubMed doi:10.1249/01.mss.0000194082.85358.c4 Tracy, B.L., Maluf, K.S., Stephenson, J.L., Hunter, S.K., & Enoka, R.M. (2005). Variability of motor unit discharge and force fluctuations across a range of muscle forces in older adults. Muscle & Nerve, 32, 533–540. PubMed doi:10.1002/mus.20392 Turano, K.A., Geruschat, D.R., & Baker, F.H. (2003). Oculomotor strategies for the direction of gaze tested with a real-world activity. Vision Research, 43, 333–346. PubMed doi:10.1016/S0042-6989(02)00498-4 Vaillancourt, D.E., & Russell, D.M. (2002). Temporal capacity of short-term visuomotor memory in continuous force production. Experimental Brain Research, 145, 275–285. PubMed doi:10.1007/s00221-002-1081-1 Vandervoort, A.A. (2002). Aging of the human neuromuscular system. Muscle & Nerve, 25, 17–25. PubMed doi:10.1002/mus.1215 Ware, J.E., Kosinski, M., Bayliss, M.S., McHorney, C.A., Rogers, W.H., & Raczek, A. (1995). Comparison of methods for the scoring and statistical analysis of the SF-36 health profile and summary measures: Summary of results from the medical outcomes study. Medical Care, 33(4), AS264–AS279. PubMed Welsh, S.J., Dinenno, D.V., & Tracy, B.L. (2007). Variability of quadriceps femoris motor neuron discharge and muscle force in human aging. Experimental Brain Research, 179, 219–233. PubMed doi:10.1007/s00221-006-0785-z West, C.G., Gildengorin, G., Haegerstrom-Portnoy, G., Schneck, M.E., Lott, L., & Brabyn, J.A. (2002). Is vision function related to physical functional ability in older adults? Journal of the American Geriatrics Society, 50, 136–145. PubMed doi:10.1046/j.15325415.2002.50019.x
The Relationships Between Muscle Force Steadiness and Visual Steadiness in Young and Old Adults Rebecca L. Krupenevich, Nick Murray, Patrick M. Rider, Zachary J. Domire, and Paul DeVita Since vision is used in studies of muscle force control, reduced muscle force control might be related to reduced visual ability. We investigated relationships between steadiness in eye movements and quadriceps muscle torque (a surrogate for force) during isometric contractions of constant and varying torques. Nineteen young adults with an average age of 20.7 years and 18 old adults with an average age of 71.6 years performed three vision tasks, three vision and torque tasks at 40% maximal voluntary contraction (MVC), and three vision and torque tasks at 54 nm. Age groups had identical torque steadiness (CV) in 40%-MVC and 54-nm conditions (p > .05). Old had similar vertical (p > .05) but decreased horizontal visual steadiness (SD) (p < .05) compared with young. Correlations between visual steadiness and muscle torque steadiness failed to show a significant relationship (p > .05). We were unable to identify a substantial relationship between muscle torque steadiness and eye movement, as a component of visual steadiness, and conclude that reduced visual steadiness does not contribute to reduced muscle torque steadiness. Keywords: aging, knee extensions, vision, eye tracking, variability
The use of appropriate and precise muscle forces is fundamental in performing basic life activities such as walking, driving automobiles, and manipulating handheld tools. A decrease in the ability to control muscle forces can reduce our ability to successfully perform these and other activities. Along with well-established decreases in muscular strength and power (Metter, Conwit, Tobin, & Fozard, 1997; Vandervoort, 2002), older adults experience decreases in muscle force accuracy, the ability to produce force at a particular magnitude, and steadiness, the ability to consistently maintain a particular force magnitude (Enoka et al., 2003; Hortobágyi, Tunnel, Moody, Beam, & DeVita, 2001), thereby affecting their capacity to execute tasks with control and precision (Tracy, Maluf, Stephenson, Hunter, & Enoka, 2005). Ultimately, inadequacies in neuromuscular function may pose safety risks to the older population. The age-related reductions in muscle force accuracy and steadiness can have an inhibiting effect on movement speed and coordination The authors are with the Dept. of Kinesiology, East Carolina University, Greenville, North Carolina. Address author correspondence to Paul DeVita at [email protected]. 60
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(Morgan et al., 1994), which in turn may affect many activities of daily living such as walking or driving. Specifically, decreased muscle force steadiness has been linked to increased fall risk in older adults (Carville, Perry, Rutherford, Smith, & Newham, 2007) and impaired performance in daily functional activities such as standing from a seated position or climbing stairs (Seynnes et al., 2005). Many factors contribute to the decrease in force steadiness with age, including motor unit remodeling and reduced firing rate frequency (Burnett, Laidlaw, & Enoka, 2000; Erim, Beg, Burke, & de Luca, 1999). Structural remodeling, partially brought about by the atrophy of fast-twitch muscle fibers, is seen with the onset of sarcopenia (Brown & Hasser, 1996). This structural remodeling is accompanied by a decline in the number of motor units and an increase in the number of fibers innervated per motor unit (Brown & Hasser, 1996; Erim et al., 1999). These adapted motor units increase the difficulty with which older adults modulate muscle force and generate the appropriate amount of muscle force during various activities of daily living (Galganski, Fuglevand, & Enoka, 1993; Larsson, Grimby, & Karlsson, 1979; Masakado et al., 1994). In addition to reductions in force steadiness with age, there is also a decrease in visual capability (Spear, 1993). Older adults, in particular, experience a decline in visual acuity (Owsley, 2011; Spear, 1993); however, visual acuity can be returned to normal with corrective optometry and therefore is not thought of as a major contributor to diminished overall visual function in relation to daily functional ability (Sosnoff & Newell, 2006; West et al., 2002). It is more likely that the decrease in visual function with age is due to a decrease in visual control (Abel, Troost, & Dell’Ossa, 1983; Knox, Davidson, & Anderson, 2005; Kosnik, Fikre, & Sekulert, 1986). Similar to other skeletal muscles, fast-twitch extraocular muscle fibers deteriorate with age (Kosnik et al., 1986), resulting in the reduced ability of older adults to control rapid eye movements, or saccades, with the same precision and accuracy as young adults (Kolarik, Margrain, & Freeman, 2010). Older adults also need more time to recognize and respond to visual targets compared with young adults (Owsley, 2011), causing a delay in the onset of eye movements when tracking a target as well as delays during tracking, further contributing to the reduction in eye movement accuracy (Kolarik et al., 2010; Moschner & Baloh, 1994; Spooner, Sakala, & Baloh, 1980). This functional decline results in an age-related increase in the number of visual tracking errors as the eyes try to reposition on the target using saccades (Sharpe & Sylvester, 1978; Sharpe & Zackon, 1987). The adverse effects of aging on vision seem to be exacerbated during balance and movement tasks, which is indicative of deficits within the visuomotor pathway (Paquette & Fung, 2011). Further, eye movement has been found to evoke responses in motor control, specifically postural sway (Glasauer, Schneider, Jahn, Strupp, & Brandt, 2005); this has large implications for the effect of vision, particularly declining vision with reduced occulomotor control, on force steadiness in large muscle groups. For example, a reduced ability to visually process a scene and respond accordingly may relate to an increased frequency of falls or injury (Chapman & Hollands, 2006; Glasauer et al., 2005). It is typical of studies investigating muscle force steadiness to use some form of visual target as the stimulus for modulating muscle force (Christou & Carlton, 2001; Hortobágyi et al., 2001; Tracy & Enoka, 2002, 2006). When visual feedback is provided during a task, older adults exhibit increased muscle force variability
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compared with tasks without visual feedback (Tracy, 2007; Tracy, Dinenno, Jorgensen, & Welsh, 2007; Welsh, Dinenno, & Tracy, 2007), indicating an age-related reduction in the ability to use visual feedback to maintain a steady force (Baweja, Kennedy, Vu, Vaillancourt, & Christou, 2010; Ofori, Samson, & Sosnoff, 2010; Svendsen, Samani, Mayntzhusen, & Pascal, 2011). Similarly, older adults have exhibited increased muscle force variability during tasks with complex visual feedback versus simple visual feedback (Christou & Carlton, 2001; Ofori et al., 2010). Thus, it is possible that the observed degradation in muscle force steadiness may in fact be a degradation in visual control or may reflect a degradation in visual control. Since visual capability declines with age and since vision is used in most investigations of muscle force control with age, reduced muscle force control in older adults might be at least partially related to or explained by altered visual capacity. We now hypothesize that there are direct relationships between visual steadiness and muscle force steadiness in both young and old adults with the implication that reduced muscle force steadiness in older adults can be at least partially explained by their reduced visual steadiness. The purpose of this study was to identify the relationships between steadiness in eye movement and muscle torque steadiness (a surrogate for muscle force steadiness) in young and old adults during isometric quadriceps contractions of constant and varying moments.
Methods Participants Nineteen young adults with an average age of 20.7 ± 1.82 years and 18 old adults with an average age of 71.6 ± 3.01 years volunteered for this study. Old and young adults had similar mean heights of 1.71 ± 0.09 and 1.73 ± 0.08 m and mean masses of 73.4 ± 10.39 and 74.2 ± 14.4 kg. A medical history questionnaire was given before participation in the study to ensure that all individuals were healthy and free of any neurological or pathological diseases and previous injuries to the lower extremities. Participants’ high functional ability was confirmed using the short physical performance battery (SPPB; Sayers et al., 2004) and short form-36 (SF-36; Ware et al., 1995) tests. On the SPPB test, both groups had an average score close to the maximum total score of 12 (young 11.8 ± 0.4; old 11.4 ± 0.9). Participants also displayed scores well above the population average of 45 on the SF-36 measures of physical capacity (young 55.9 ± 3.2; old 52.7 ± 5.56) and mental capacity (young 53.8 ± 4.6; old 56.4 ± 4.8). Testing protocols were approved by the institutional review board for human research, and each participant gave written informed consent.
Equipment Isometric quadriceps torque data were collected using an isokinetic dynamometer at a sampling frequency of 100 Hz (HUMAC NORM, CSMi, Stoughton, MA). We used isokinetic torque data as a direct surrogate of muscle force, which was reasonable because the lever arm for the isokinetic instrument remained unchanged through all tests. Horizontal and vertical eye movement data were collected using a mobile eye-tracking system at a sampling frequency of 30 Hz (Applied Science Laboratories, Bedford, MA). The mobile eye-tracking system included Mobile eye
Muscle Force and Visual Steadiness in Young and Old Adults 63
XG software, an LCD video recorder, and eye-tracking glasses consisting of a pair of eyeglass frames with two digital resolution cameras mounted above the right eye. One camera tracked the scene and the other camera tracked the eye movements. Visual targets were displayed on a 19-in. computer monitor (Dell, USA) using a custom-made software program.
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Procedures Participants visited the laboratory twice within 7 days with the two visits being separated by at least 48 hr. Maximal quadriceps strength and functional ability were assessed on the 1st day after appropriate acclimation to the dynamometer. Participants also practiced all muscle torque–visual steadiness tests on the 1st day to acclimate to the protocol and equipment. On the 2nd day, data were collected for all nine test conditions.
Maximal Quadriceps Muscle Torque Participants were seated on the isokinetic dynamometer seat with the back angle at approximately 90°. The axis of the right knee was aligned with the axis of the input shaft of the dynamometer. The shin pad was placed on the shank above the lateral malleolus at a comfortable position for the participant. A thigh strap was used to immobilize the right thigh. A seat belt and a shoulder stabilization belt were also used as an attempt to limit upper body movement during testing. The right knee was held at a 60° angle throughout all tasks. Anatomical zero was set when the knee was in full extension, and leg weight was measured in this position. The dynamometer’s software corrected the torque output to account for the effect of gravity on leg weight. Maximal isometric quadriceps strength was assessed over three 5-s trials, allowing for 60 s of rest in between consecutive trials. The 3-s window with the highest average, across all of the trials, was determined to be the maximal voluntary contraction (MVC) torque.
Eye Movements The eye-tracker glasses were placed on the participant’s face and calibrated using a nine-point calibration screen. Participants were allowed to wear corrective lenses, either glasses or contact lenses, during testing. The calibration process was repeated at the beginning of the testing session on Day 2 and in the event that the glasses were moved or shifted on the participant’s face at any point during either testing session. Participants were instructed to track the target using only their eyes and to avoid moving their head during the tracking tasks as much as possible. Table 1 Age Group Results for Muscle Torque Steadiness in Absolute and Relative Conditions Relative (Nm) Absolute (Nm)
Young (n = 19) 1.45 ± 0.63 1.26 ± 0.41
Values are coefficients of variation ± SD
Old (n = 18) 1.31 ± 0.33 1.43 ± 0.53
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Test Conditions Data were collected over nine tasks, and each task had three trials. The visual feedback for all tasks consisted of a cursor in the form of a green circle (11-mm diameter) moving in the vertical direction in response to quadriceps torque magnitude and horizontally at a set speed requiring 8 s to cross the 37.5-cm wide monitor. The monitor had 1,280 pixels horizontally and 1,024 pixels vertically; because screen resolution remained the same, visual gain varied by participant in the 40%-MVC conditions but was the same for all participants in the 54-nm conditions.
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Tasks The tasks consisted of the following: • Three vision tasks: (1) Viewing stationary cursor in center of screen, (2) visually tracking cursor moving horizontally across the middle of the blank screen, and (3) visually tracking cursor moving horizontally across the middle of the screen on a horizontal white line. • Three vision and torque tasks at a relative torque value of 40% MVC (relative torque conditions): Using isometric quadriceps contractions, participants controlled the cursor (1) with a constant torque to match a horizontal line, (2) with a constantly increasing then decreasing torque to match the cursor with a constant upward then downward sloped line, and (3) with a parabolically increasing then decreasing torque to match a parabolic target (Figure 1). • Three vision and torque tasks at an absolute torque value of 54 nm (absolute torque conditions) using the same conditions as in the relative conditions. The order of the vision and torque tasks was determined randomly for each participant. The 54-nm value was determined from a separate pilot study that obtained maximal strength measures on 12 young and 12 old adults and provided the average 40% MVC of all 24 participants. These individuals had similar anthropometric characteristics as the present participants but did not participate in the current study. In addition, the 40% MVC target torque level reasonably represents the functional values observed in activities of daily living in the lower extremity.
Figure 1 — Templates used with torque conditions; right to left: horizontal line, constant slope, parabola.
Muscle Force and Visual Steadiness in Young and Old Adults 65
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Data Analysis The eye tracker provided a continuous recording of eye position for each trial, as well as an indication of any possible disruptions that caused a loss of signal. The recording for each trial was initiated 1 s before the participant started the trial, as determined by the 3-s countdown at the beginning of the trial, and terminated 1 s after the participant finished the trial. In the event that the infrared beam producing the three corneal reflections on the participant’s eye was disrupted, that section of the data was removed from the trial. Disruptions to the data recording could have been due to blinking, excessive squinting, or in some other way obstructing the path of the infrared light to the cornea. We note at this time that pursuit eye movements were observed in the vision-only condition and saccadic eye movements were observed in the vision and torque conditions. However, further analysis of these data was beyond the scope of this study; therefore, we do not present that analysis here. In addition, we analyzed each condition separately, ensuring that no condition contaminated data from another condition. Figure 2 illustrates representative torque-time curves from 1 young and 1 old participant performing the straight-line torque task at the 54-nm target. The middle 60% of each set of data was plotted on a line of best fit for all three trials.
Figure 2 — Representative trials from (a) one young and (b) one old adult. The horizontal line represents the 54-nm target torque. The fluctuation in torque signal represents muscle torque steadiness.
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The middle 60% was used in an attempt to analyze data collected when the participant was performing the intended task. We did not wish to analyze the portion of the trial during which participants were moving their eyes or the cursor to the target line. The mean value of the three trials in each condition was used in the statistical analysis. The horizontal and vertical vision data and the torque data were detrended before calculating measures of variance and central tendency for each trial other than those in the stationary vision condition (Tracy et al., 2007). Detrending was performed to remove any drift in the data so that all variance measures were affected only by variation in torque or visual data and not by the magnitude of the data. Namely, detrending produced a signal with a mean value of zero with noise being the positive and negative fluctuations of torque or vision around the mean. Without detrending, variance measures would be erroneously increased by the changing torque or visual signal. Detrending was accomplished by subtracting the line of best fit from each point with single lines of best fit calculated for the horizontal-line conditions, a positive and a negative sloped linear fit for the constant slope conditions, and a second order polynomial fit for the parabolic conditions.
Statistical Analysis We compared young and old adults on strength, visual steadiness, muscle torque steadiness, and selected visual parameters to determine any age-related differences using t tests. Coefficient of variation (CV) in the horizontal 40% MVC and horizontal 54-nm conditions was used to quantify muscle torque steadiness. A Pearson product–moment correlation analysis was also performed with each test condition individually to establish a relationship between visual steadiness and muscle torque steadiness across participants. The correlation analyses performed on the four relative and absolute constant and parabolic slope conditions were used to analyze the relationships between vision and torque data. The standard deviation of torque and the resultant standard-deviation values of the vertical and horizontal vision components were used in the correlations. We chose to use standard deviation in the correlations because, due to the detrending of the data, the means were nearly zero. The alpha level was set at p < .05 for all tests.
Results Maximum Strength Maximum voluntary muscle torque was 31% lower in old compared with young adults (145 ± 51.5 vs. 209 ± 68.4 nm, p < .05).
Age and Muscle Torque Steadiness There were no significant differences in muscle torque steadiness between young and old adults in either the relative condition (young = 1.45 ± 0.63; old = 1.31 ± 0.33; p = .20) or the absolute condition (young = 1.26 ± 0.41; old = 1.43 ± 0.53; p = .14; Table 1).
Muscle Force and Visual Steadiness in Young and Old Adults 67
Age and Visual Steadiness
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Young and old adults displayed similar visual capacity, as measured by the three vision-only conditions (Figure 3). The static vision condition did not show a significant difference between the two groups for the horizontal (p = .08) or vertical (p = .28) visual components. Similarly, the vision no-line condition and vision horizontal-line condition did not show significant differences between young and old adults for the vertical vision component (p = .34 and p = .47, respectively). A significant difference was observed in the horizontal component for these two conditions, with older adults showing ?40% decreased horizontal visual steadiness compared with young adults (p < .05).
Figure 3 — Top (static condition): No age-related difference in the horizontal or vertical visual component. Center (no-line condition): Old adults were less steady in the horizontal visual component than young; no age-related difference for the vertical visual component. Bottom (horizontal-line condition): Old adults were less steady in the horizontal visual component than young; no age-related difference for the vertical visual component.
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Relationships Between Visual Steadiness and Muscle Torque Steadiness
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Correlations performed between visual steadiness and muscle torque steadiness (using pooled data from both young and old adults) failed to show statistical significance for any of the relative or absolute constant slope and parabola conditions using the following critical value for a two-tailed test at p < .05: (df = 36) = 0.320. Table 2 shows the correlation coefficient (r) values for each vision and torque condition. Figures 4 and 5 illustrate correlations showing the line of best fit between resultant vision and torque along with the corresponding R2 value for the constant and parabolic slope conditions. Table 2 Correlation Coefficients (r) for Absolute and Relative Vision Torque Conditions Young and Old (n = 38) Constant slope Absolute Relative Parabola Absolute Relative
.067 .270 .045 .106
Figure 4 — Correlations between muscle torque steadiness and visual steadiness (resultant value of horizontal and vertical components for all participants) in the constant slope condition for (A) 40% MVC and (B) 54 nm. *r value 0, p < .05.
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Figure 5 — Correlations between muscle torque steadiness and visual steadiness (resultant value of horizontal and vertical components for all participants) in the parabola condition for (A) 40% MVC and (B) 54 nm.
Discussion Functional Capacity Young and old adults in the current study were healthy, mobile, and functionally capable individuals. The old adults, in particular, were high performing individuals based on SF-36 and SPPB scores. The difference in maximum isometric quadriceps strength between the young and old adult groups in the current study (?31% lower, old vs. young) was slightly smaller than the difference between groups in similar studies. Schiffman et al. (Schiffman, Luchies, Richards, & Zebas, 2002) reported a ?35% difference in MVC between young and old adults, and Hortbágyi et al. (Hortobágyi et al., 2001) reported a 43% difference in isometric quadriceps MVC between young and old adults.
Muscle Torque Steadiness Young and old adults did not display a significant age-related difference in isometric quadriceps torque steadiness at an absolute 54-nm or 40%-MVC torque level. The extensive practice we provided, which was more than usually has been done in muscle torque steadiness investigations (Tracy et al., 2007; Welsh et al., 2007), may have decreased muscle torque variability, accounting for the relatively low torque variability displayed by all present participants. Cirillo et al. (Cirillo, Todd, & Semmler, 2011) reported that young and old adults displayed similar task
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specific improvement after short-term training with a complex visuomotor task. Our participants performed the visual steadiness and muscle torque steadiness tasks on two separate occasions, which may have induced an unintended learning effect. Vaillancourt and Russell (2002) provided some evidence refuting this notion by showing that there were no changes in the amount of torque variability over the course of a 20-s constant-torque trial after one practice trial. However, we provided our participants with much more practice. Our participants visited the laboratory twice; on the first visit, the participants performed a “practice protocol,” executing an identical set of tasks and conditions that they would perform on their second visit to the laboratory. Although the order of the vision and torque tasks was selected randomly, the 54-nm absolute value at which our participants were tested corresponded to 29% and 43% of the young and old adult average MVC values, respectively. Thus, the difference between the 54-nm absolute and 40%-MVC relative target levels for the old adults was only about ?3% while the difference for the young adults was ?11%. This negligible change in target torque levels for older adults could have also contributed to the learning effect through repetition. The substantial amount of practice that our participants underwent before data collection (i.e., performing all nine tasks) may be a contributing factor to the relatively high muscle torque steadiness displayed by the present participants.
Visual Steadiness Although the young and old adult groups were similar in terms of visual steadiness, there was a statistically significant age-related difference in horizontal eye movement for the no-line and straight-line vision-only conditions. Visual steadiness was quantified as the standard deviation of eye movement in pixels as a response to a visual target. Old adults showed less horizontal eye movement steadiness than young adults whereas the vertical visual steadiness values between the two groups were quite similar. This discrepancy is consistent with literature suggesting that older adults show increased variability in the horizontal direction compared with the vertical direction (Kosnik et al., 1986). Interestingly, there was not a significant difference between the two groups for the static task during which the visual target did not move. Therefore, we postulate that the movement of the visual target in the no-line and straight-line tasks evoked a different visual response than the nonmoving target from older adults, resulting in decreased horizontal eye movement steadiness. These results are in agreement with observations that young and old adults exhibit similar variations in eye movements during a static fixation task, yet, during a tracking task, older participants display decreased eye movement control compared with young adults (O’Connor, Margrain, & Freeman, 2010). This phenomenon may also relate to the relationship between target speed and eye movement speed (Sharpe & Sylvester, 1978). When the visual target was no longer stationary, older adults may have had more trouble matching the speed of their eye movements with the target, causing increased variation in eye movement compared with young adults. This study was the first attempt to quantify visual steadiness using eye movement recordings from an eye-tracking instrument while assessing muscle torque steadiness. Previously, eye-tracking instruments similar to the present device have been used to relate eye movement to large-scale tasks—for example, quantifying gaze patterns when walking to a target at the end of a hallway (Turano, Geruschat,
Muscle Force and Visual Steadiness in Young and Old Adults 71
& Baker, 2001) or identifying focal points while driving (Land & Lee, 1994). In addition, there may be some concern over the amount of head movement from the participants during tracking tasks as we did not immobilize the participants’ heads during testing. However, we gave several verbal commands instructing participants to track the target by moving only their eyes and to keep their head as still as possible.
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Relationships Between Visual Steadiness and Muscle Torque Steadiness We were unable to substantially establish a relationship between visual steadiness and isometric knee extensor torque steadiness. We also investigated correlations between the young and old groups separately to ensure that combining the groups did not mask a significant relationship; however, we found fundamentally identical results as in the combined analysis. Our findings may indicate that visual steadiness, as a component of visual control, is not a contributing factor in the equilibrium point hypothesis of motor control, in that it does not appear to be related to the control of muscle force activation. Contrary to our findings, there appears to be a well-documented relationship between the presence or absence of visual feedback and muscle torque steadiness, showing that the presence of visual feedback provokes an increase in the amount of torque variability in older adults compared with young adults (Tracy, 2007; Tracy et al., 2007; Welsh et al., 2007). In fact, this observation was a foundational issue for our hypothesis. Welsh et al. (2007) demonstrated that age-related differences in motor unit firing rate variability are only observed in the presence of visual feedback. In addition, age-related deficits in muscle torque steadiness have been identified as a response to complex versus simple visual feedback (Ofori et al., 2010) and in response to increased amounts of visual feedback through manipulating visual gain, or pixels per unit torque (Sosnoff & Newell, 2006). With these factors in mind, one could presume that while we were unable to identify a relationship between visual steadiness and muscle torque steadiness, there may be some other age-related physiological deficits affecting the way older adults view and respond to visual information that is likely related to torque output variability. Several factors, other than the presence of visual feedback, have also been shown to influence force variability—for example, the presence of physiological stressors (Christou, Jakobi, Critchlow, Fleshner, & Enoka, 2004; Christou, 2005), emotional state (Naugle, Coombes, & Janelle, 2010), altered levels of respiration (Baweja, Patel, Neto, & Christou, 2011), and aging (Enoka et al., 2003). Further interpretation might suggest these factors are indicative of the notion that there may be physiological factors other than muscle control that influence muscle torque steadiness.
Conclusion We were not able to identify a physiological relationship between muscle torque steadiness and eye movement, as a component of visual steadiness. Therefore, there is no evidence to support our hypothesis that there would be direct relationships between visual steadiness and muscle force steadiness in both young and old adults, with the implication that reduced muscle force steadiness in older adults would
72 Krupenevich et al.
be at least partially correlated with reduced visual steadiness. Thus, it is possible that the interactions between force steadiness and aging observed in the literature might in fact be due to reduced neuromuscular control and not due to reduced visual function with aging. In addition, the relationship between force steadiness and visual feedback identified in previous research may be due to decrements in visual processing capabilities and not due to a decline in visual steadiness. Regardless, in the current study, we were not able to detect the influence of visual capacity on muscle torque steadiness in young or old adults.
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References Abel, L.A., Troost, T.B., & Dell’Ossa, L.F. (1983). The effects of age on normal saccadic characteristics and their variability. Vision Research, 23, 33–37. PubMed doi:10.1016/0042-6989(83)90038-X Baweja, H.S., Kennedy, D.M., Vu, J., Vaillancourt, D.E., & Christou, E.A. (2010). Greater amount of visual feedback decreases force variability by reducing force oscillations from 0–1 and 3–7 Hz. European Journal of Applied Physiology, 108, 935–943. PubMed doi:10.1007/s00421-009-1301-5 Baweja, H.S., Patel, B.K., Neto, O.P., & Christou, E.A. (2011). The interaction of respiration and visual feedback on the control of force and neural activation of the agonist muscle. Human Movement Science, 30, 1022–1038. PubMed doi:10.1016/j.humov.2010.09.007 Brown, M., & Hasser, E. (1996). Complexity of age-related change in skeletal muscle. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 51(2), B117–B123. PubMed doi:10.1093/gerona/51A.2.B117 Burnett, R.A., Laidlaw, D.H., & Enoka, R.M. (2000). Coactivation of the antagonist muscle does not covary with steadiness in older adults. Journal of Applied Physiology, 89, 61–71. PubMed Carville, S.F., Perry, M.C., Rutherford, O.M., Smith, C.H., & Newham, D.J. (2007). Steadiness of quadriceps contractions in young and older adults with and without a history of falling. European Journal of Applied Physiology, 100, 527–533. PubMed doi:10.1007/ s00421-006-0245-2 Chapman, G.J., & Hollands, M.A. (2006). Evidence for a link between changes to gaze behaviour and risk of falling in older adults during adaptive locomotion. Gait & Posture, 24, 288–294. PubMed doi:10.1016/j.gaitpost.2005.10.002 Christou, E.A. (2005). Visual feedback attenuates force fluctuations induced by a stressor. Medicine and Science in Sports and Exercise, 37(12), 2126–2133. PubMed doi:10.1249/01. mss.0000178103.72988.cd Christou, E.A., & Carlton, L.G. (2001). Old adults exhibit greater motor output variability than young adults only during rapid discrete isometric contractions. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 56(12), B524–B532. PubMed doi:10.1093/gerona/56.12.B524 Christou, E.A., Jakobi, J.M., Critchlow, A., Fleshner, M., & Enoka, R.M. (2004). The 1- to 2-Hz oscillations in muscle force are exacerbated by stress, especially in older adults. Journal of Applied Physiology, 97, 225–235. PubMed doi:10.1152/japplphysiol.00066.2004 Cirillo, J., Todd, G., & Semmler, J.G. (2011). Corticomotor excitability and plasticity following complex visuomotor training in young and old adults. The European Journal of Neuroscience, 34, 1847–1856. PubMed doi:10.1111/j.1460-9568.2011.07870.x Enoka, R.M., Evangelos, C.A., Hunter, S.K., Kornatz, K.W., Semmler, J.G., Taylor, A.M., & Tracy, B.L. (2003). Mechanisms that contribute to differences in motor performance between young and old adults. Journal of Electromyography and Kinesiology, 13, 1–12. PubMed doi:10.1016/S1050-6411(02)00084-6
Downloaded by Boston University on 09/19/16, Volume 19, Article Number 1
Muscle Force and Visual Steadiness in Young and Old Adults 73
Erim, Z., Beg, F., Burke, D.T., & de Luca, C.J. (1999). Effects of aging on motor-unit control properties. Journal of Neurophysiology, 82, 2081–2091. PubMed Galganski, M.E., Fuglevand, A.J., & Enoka, R.M. (1993). Reduced control of motor output in a human hand muscle of elderly subjects during submaximal contractions. Journal of Neurophysiology, 69(6), 2108–2115. PubMed Glasauer, S., Schneider, E., Jahn, K., Strupp, M., & Brandt, T. (2005). How the eyes move the body. Neurology, 65, 1291–1293. PubMed doi:10.1212/01.wnl.0000175132.01370.fc Hortobágyi, T., Tunnel, D., Moody, J., Beam, S., & DeVita, P. (2001). Low- or high-intensity strength training partially restores impaired quadriceps force accuracy and steadiness in aged adults. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 56(1), B38–B47. PubMed doi:10.1093/gerona/56.1.B38 Knox, P.C., Davidson, J.H., & Anderson, D. (2005). Age-related changes in smooth pursuit initiation. Experimental Brain Research, 165. PubMed Kolarik, A.J., Margrain, T.H., & Freeman, T.C.A. (2010). Precision and accuracy of ocular following: Influence of age and type of eye movement. Experimental Brain Research, 201, 271–282. PubMed doi:10.1007/s00221-009-2036-6 Kosnik, W., Fikre, J., & Sekulert, R. (1986). Visual fixation stability in older adults. Investigative Ophthalmology & Visual Science, 27, 1720–1725. PubMed Land, M.F., & Lee, D. (1994). Where we look when we steer. Nature, 369, 742–744. PubMed doi:10.1038/369742a0 Larsson, L., Grimby, G., & Karlsson, J. (1979). Muscle strength and speed of movement in relation to age and muscle morphology. Journal of Applied Physiology, 46(3), 451–456. PubMed Masakado, Y., Noda, Y., Nagata, M., Kimura, A., Chino, N., & Akaboshi, K. (1994). MacroEMG and motor unit recruitment threshold: Differences between the young and the aged. Neuroscience Letters, 179(1–2), 1–4. PubMed doi:10.1016/0304-3940(94)90920-2 Metter, E.J., Conwit, R., Tobin, J., & Fozard, J.L. (1997). Age-associated loss of power and strength in the upper extremities in women and men. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 52(5), B267–B276. PubMed doi:10.1093/ gerona/52A.5.B267 Morgan, M., Phillips, J.G., Bradshaw, J.L., Mattingley, J.B., Iansek, R., & Bradshaw, J.A. (1994). Age-related motor slowness: Simply strategic? The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 49(3), 133–139. Moschner, C., & Baloh, R.W. (1994). Age-related changes in visual tracking. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 49(5), M235–M238. PubMed Naugle, K.M., Coombes, S.A., & Janelle, C.M. (2010). Subclinical depression modulates the impact of emotion on force control. Motivation and Emotion, 34, 432–445. doi:10.1007/ s11031-010-9184-7 O’Connor, E., Margrain, T.H., & Freeman, T.C.A. (2010). Age, eye movement and motion discrimination. Vision Research, 50, 2588–2599. PubMed doi:10.1016/j.visres.2010.08 .015 Ofori, E., Samson, J.M., & Sosnoff, J.J. (2010). Age-related differences in force variability and visual display. Experimental Brain Research, 203, 299–306. PubMed Owsley, C. (2011). Aging and vision. Vision Research, 51, 1610–1622. Paquette, C., & Fung, J. (2011). Old age affects gaze and postural coordination. Gait & Posture, 33, 227–232. PubMed doi:10.1016/j.gaitpost.2010.11.010 Sayers, S.P., Jette, A.M., Haley, S.M., Heeren, T.C., Guralnik, J.M., & Fielding, R.A. (2004). Validation of the late-life function and disability instrument. Journal of the American Geriatrics Society, 52, 1554–1559. PubMed doi:10.1111/j.1532-5415.2004.52422.x Schiffman, J.M., Luchies, C.W., Richards, L.G., & Zebas, C.J. (2002). The effects of age and feedback on isometric knee extensor force control abilities. Clinical Biomechanics (Bristol, Avon), 17, 486–493. PubMed doi:10.1016/S0268-0033(02)00041-4
Downloaded by Boston University on 09/19/16, Volume 19, Article Number 1
74 Krupenevich et al.
Seynnes, O., Hue, O.A., Garrandes, F., Colson, S.S., Bernard, P.L., Legros, P., & Singh, M.A. (2005). Force steadiness in the lower extremities as an independent predictor of functional performance in older women. Journal of Aging and Physical Activity, 13, 395–408. PubMed Sharpe, J.A., & Sylvester, T.O. (1978). Effect of aging on horizontal smooth pursuit. Investigative Ophthalmology and Visual Science, 17(5), 465–467. Sharpe, J.A., & Zackon, D.H. (1987). Senescent saccades: Effects of aging of their accuracy, latency and velocity. Acta Oto-Laryngologica, 104, 422–428. PubMed doi:10.3109/00016488709128270 Sosnoff, J.J., & Newell, K.M. (2006). Information processing limitations with aging in the visual scaling of isometric force. Experimental Brain Research, 170, 423–432. PubMed doi:10.1007/s00221-005-0225-5 Spear, P.D. (1993). Neural bases of visual deficits during aging. Vision Research, 33(18), 2589–2609. PubMed doi:10.1016/0042-6989(93)90218-L Spooner, J.W., Sakala, S.M., & Baloh, R.W. (1980). Effect of aging on eye tracking. Archives of Neurology, 37, 575–576. PubMed doi:10.1001/archneur.1980.00500580071012 Svendsen, J.H., Samani, A., Mayntzhusen, K., & Pascal, M. (2011). Muscle coordination and force variability during static and dynamic tracking tasks. Human Movement Science, 30, 1039–1051. PubMed Tracy, B.L. (2007). Visuomotor contribution to force variability in the plantarflexor and dorsiflexor muscles. Human Movement Science, 26, 796–807. PubMed doi:10.1016/j. humov.2007.07.001 Tracy, B.L., Dinenno, D.V., Jorgensen, B., & Welsh, S.J. (2007). Aging, visuomotor correction, and force fluctuations in large muscles. Medicine and Science in Sports and Exercise, 39, 469–479. PubMed doi:10.1249/mss.0b013e31802d3ad3 Tracy, B.L., & Enoka, R.M. (2002). Older adults are less steady during submaximal isometric contractions with the knee extensor muscles. Journal of Applied Physiology, 92, 1004–1012. PubMed Tracy, B.L., & Enoka, R.M. (2006). Steadiness training with light loads in the knee extensors of elderly adults. Medicine and Science in Sports and Exercise, 38, 735–745. PubMed doi:10.1249/01.mss.0000194082.85358.c4 Tracy, B.L., Maluf, K.S., Stephenson, J.L., Hunter, S.K., & Enoka, R.M. (2005). Variability of motor unit discharge and force fluctuations across a range of muscle forces in older adults. Muscle & Nerve, 32, 533–540. PubMed doi:10.1002/mus.20392 Turano, K.A., Geruschat, D.R., & Baker, F.H. (2003). Oculomotor strategies for the direction of gaze tested with a real-world activity. Vision Research, 43, 333–346. PubMed doi:10.1016/S0042-6989(02)00498-4 Vaillancourt, D.E., & Russell, D.M. (2002). Temporal capacity of short-term visuomotor memory in continuous force production. Experimental Brain Research, 145, 275–285. PubMed doi:10.1007/s00221-002-1081-1 Vandervoort, A.A. (2002). Aging of the human neuromuscular system. Muscle & Nerve, 25, 17–25. PubMed doi:10.1002/mus.1215 Ware, J.E., Kosinski, M., Bayliss, M.S., McHorney, C.A., Rogers, W.H., & Raczek, A. (1995). Comparison of methods for the scoring and statistical analysis of the SF-36 health profile and summary measures: Summary of results from the medical outcomes study. Medical Care, 33(4), AS264–AS279. PubMed Welsh, S.J., Dinenno, D.V., & Tracy, B.L. (2007). Variability of quadriceps femoris motor neuron discharge and muscle force in human aging. Experimental Brain Research, 179, 219–233. PubMed doi:10.1007/s00221-006-0785-z West, C.G., Gildengorin, G., Haegerstrom-Portnoy, G., Schneck, M.E., Lott, L., & Brabyn, J.A. (2002). Is vision function related to physical functional ability in older adults? Journal of the American Geriatrics Society, 50, 136–145. PubMed doi:10.1046/j.15325415.2002.50019.x
