Research in motor control of aging humans has been centered around determining how motor performance is influenced by age, and around efforts to unravel the mechanisms that contribute to declines in motor performance. Changes are often characterized by slower and more variable movements, specifically slower initiation of movement, slower movement durations, declines in coordination of movement, reduced force production, coactivation of antagonist muscles during movement, and increased variability of movements (i.e., movements become inconsistent or varied from one use to the next). Specific examples of tasks that are linked to dimensions of motor control include goal-directed movements such as pointing, reaching and grasping, and aiming.
The slowing of movement in older adults can be seen in everyday tasks such as reaching and grasping, point-to-point movements (discrete goal-directed aiming movements with a defined beginning and end), and continuous movements (cyclical movements, such as circles, with no defined beginning and end). Movement time (MT) provides an assessment of the speed of task execution. Movement time is defined as the time from the initiation of a particular movement to the termination of the movement. Movement times in older adults are substantially slower than young adults, ranging from 20 to 70 percent slower, depending on the complexity of the task. A variety of tasks have been assessed, including movements of the finger, hand, arm, and trunk.
Fitts' Law (Fitts) describes increases in MT as a function of task complexity (see Figure 1). Movement accuracy is manipulated by increasing the distance traveled to a target or increasing the size of the target, and tasks can be analyzed through an Index of Difficulty (ID). For both young and older adults, MT increases linearly as ID increases. However, older adults are slower than young adults at the lowest levels of difficulty, and MT increases at a greater rate as difficulty increases.
Movement-time measures are important in assessing movement slowing, however they do not provide explicit insight on the underlying mechanisms of slowing or on specific changes in control. Research has therefore focused on movement decomposition in an effort to identify particular movement characteristics that contribute to movement slowing, allowing researchers to assess fundamental changes associated with movement slowing in older adults.
Kinematic analysis documents the specific features of a motion, specifically linear and angular displacement, velocity, and acceleration of goal-directed movements. Young controls portray bell-shaped velocity profiles in accurate point-to-point movements (see Figure 2B). Specifically, the ratio between the acceleration and deceleration phases of a movement is approximately 1.0. The acceleration phase coincides with the portion of a movement before peak velocity, and the deceleration phase, consequently, is the portion of a movement after peak velocity (see Figure 2B; 2E). Older adults demonstrate shorter acceleration phases and prolonged deceleration phases, thus portraying asymmetric or skewed velocity profiles. This suggests that it is the terminal, or deceleration, portion of movement that primarily contributes to slower movement outputs. Furthermore, older adults consistently produce lower peak velocity and acceleration amplitudes compared to young adults, which also contributes to slower movements.
Kinematic profiles may be examined to provide additional analyses of possible sources of slower movements. The movement optimization model (Meyer) divides the velocity and acceleration profiles into primary and secondary submovements. The primary submovement represents the ballistic, or prepared, portion of movement, whereas the secondary submovement represents the feedback, or corrective, portion of movement control (see Figure 2C; 2F). Adjustments to the microstructure of the movement indicate how movement control changes with task constraints. The primary submovement is shortened in older adults, requiring them to make more secondary, corrective submovements to reach a target (see Figure 2F). Older adults are known to decrease the distance traveled in the primary submovement and increase the number of corrective submovements in a variety of tasks. The shortening of the primary submovement may be a consequence of bodily changes and/or decrements in processing capacity and efficiency. Specific causes may include the inability to prepare and organize movement effectively, reduced proprioception, abnormal muscle activation patterns, increased reliance on vision, and the inability to produce or scale forces efficiently.
To produce movement, force must be generated by the muscles driving the body segment involved in a movement. These forces must be scaled to increase velocity; but, perhaps more importantly, the timing of muscle activation must synchronize with multiple other muscles and subsystems of the motor-control system. Research has shown that older adults have reductions in force production and regulation across a range of tasks, which limits their ability to make fast, accurate movements. Properties that may contribute to such changes are loss in muscle mass and a reorganization of motor units. However, it has further been shown in tasks in which accuracy constraints are relaxed that older adults are able to produce similar forces as young controls produce. This suggests that while muscle loss and motor unit reorganization may lead to decreases in force production, it is most likely not the limiting factor in tasks such as reaching and grasping and point-to-point movements, in which force output is submaximal. Therefore, there must be other mechanisms that contribute to force-control deficits in the presence of accuracy constraints in older adults. A possibility is that the fine ramping of force production is compromised in the reorganization of motor units, which are essential in fine motor tasks such as reaching and grasping and point-to-point movements.
In precision grip tasks, older adults produce excessive force in an effort to keep the grasped object from slipping. Again, older adults, while able to produce sufficient and even excessive force, are unable to effectively modulate and time force output. This is amplified when grip surfaces are slippery—in such instances older adults substantially increase grip forces beyond the necessary level to keep the object from falling. This suggests that it is peripheral feedback-mechanism decrements such as proprioception or tactile feedback, and/or processing capacity, that are compromised with advanced age and limit performance of older adults in these fine motor tasks.
Movement variability and coordination
Older adults also exhibit heightened movement variability in kinematic and endpoint measures. Variability has been documented in such measures as movement trajectory, peak velocity, movement duration, ratio of acceleration and deceleration phases, and force control. Compensation for movement variability may result in behavioral outputs that are a consequence of, rather than a mechanism of, movement variability and/or slowing. Seidler-Dobrin et al. (1998) found that older adults coactivate the agonist and antagonist muscles during movement, leading to altered muscle activation patterns, which consequently contributes to increased variability. Older adults also exhibited longer deceleration phases of movements. Coordination of multiple joint segments involves very complex control. Studies of handwriting, bimanual coordination, and multijoint coordination have found that older adults lose fine motor coordination and have increased normalized jerk, which is a measure of movement smoothness. This is manifested in decreased peak acceleration, deformations of desired movements at lower speeds, and bimanual coordination declines at lower speeds.
In the motor-control literature on older adults, many of the behavior decrements discussed thus far are linked to physical and cognitive declines. It has been suggested by several researchers that visual guidance of movement may partially, if not completely, compensate for many of the changes that occur with age when accuracy is required. Visual monitoring of a movement may compensate for sensorimotor information lost during the movement due to decrements in this information at the peripheral or central level. Since feedback information takes additional time to process and integrate, movements are typically slow and more variable. Furthermore, older adults in the absence of vision (when it is occluded) increase MTs and variability, suggesting that the visual monitoring of movements is important to the speed and accuracy of movement performance. In the absence of vision, older adults produce shorter primary submovements compared to young controls, even with ample practice. This suggests that older adults are reliant on visual feedback to control their movements. Researchers have suggested that this dependence is a consequence of one or more limitations in processing, planning, force production and regulation, and proprioception.
Motor-control declines that occur in older adults lead to slow and variable movement outputs. However, the underlying mechanisms that contribute to these outcomes are not well understood. These deficits do not add up linearly to give a complete picture of motor performance decrements plotted as a function of age. This complex problem leaves motor-control researchers with a variety of questions to ask. It is important, both while reading the literature and while conducting research, to keep in mind that the human motor system is quite complex. The individual components of the puzzle measured by researchers allow them to focus on determining what the primary contributors are to any deficit, since many of the sensorimotor processes are interdependent.
Figure 2 concerns the principles of kinematic and submovement parsing, illustrating young and older adult position, velocity, and acceleration profiles. Each of the six panels covers specific profiles: A) Young adults' positional data; B) Young adults' velocity profile, including acceleration and deceleration phases/times; C) Young adults' acceleration profiles, including primary and secondary submovement parsing; D) Older adults' positional data; E) Older adults' velocity profile, including acceleration and deceleration phases/times; F) Older adults' acceleration profiles, including primary and secondary submovement parsing. This illustration was adapted from: Ketcham, C. J.; Seidler, R. D.; Van Gemmert, A. W. A.; and Stelmach, G. E. (in Press) "Age Related Kinematic Differences as Influenced by Task Difficulty, Target-Size, and Movement Amplitude." Journal of Gerontology: Psychological Sciences.
Caroline J. Ketcham George E. Stelmach
See also Brain; Physiological Changes, Organ Systems: Skeletal Muscle; Reaction Time.
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