Changes to online control and eye-hand coordination with healthy ageing

Effects of balance constraints during a double-step reaching task

BACKGROUND

In daily life tasks of the upper limb, we must make quick corrections with our hands in unstable postural situations. Postural and reaching control mechanisms are involved in the accurate execution of upper-limb tasks.

RESEARCH QUESTION

This research aimed to determine the effect of different postural stability conditions on the motor performance of the upper limb in a reaching task with non-static targets.

METHODOLOGY

19 young participants performed a reaching task toward targets that exhibited a change in position (at 200 or 600 ms) in different postural conditions (bipedal-firm, bipedal-foam, and unipedal-foam surface). Performance on the screen (motion time and spatial error), balance (center of pressure displacements, CoP), and index finger movements were recorded during the reaching task.

RESULTS

The instability affects the finger kinematic (displacements) and CoP kinematic (displacements, speed, and smoothness) without affecting the performance on the screen (precision and duration). The timing of target change affects the performance on the screen, finger kinematic (speed and smoothness), and CoP kinematic (displacements, speed, and smoothness).

SIGNIFICANCE

Postural and reaching control systems enable accurate hand motions in less stable situations, even in reaching tasks with non-static targets. The postural and reaching control systems can protect the end-effector performance during unstable conditions but not during trials with less time to correct the motion.

Age-related differences in functional tool-use are due to changes in movement quality and not simply motor slowing

Age-related declines in fine motor control may impact tool-use and thereby limit functional independence. Most previous research has, however, focused on the effect of aging on gross motor tasks. Few studies have investigated the effects of aging on the strategy or quality of fine motor skills, especially in tool-use, which may better reflect how age impacts complex movement capability. Twenty-two young (ages 19-35) and 18 older adults (ages 58-87) performed a timed upper extremity task using a tool to acquire and transport objects to different locations. Overall task performance was divided into two phases based on 3-D position of the tool: a gross motor phase (object transport) and a fine motor phase (object acquisition). Overall, older adults took longer to complete the task. A linear model indicated that this was due to the duration of the fine motor phase more so than the gross motor phase. To identify age-related differences in the quality of the fine motor phase, we fit three-dimensional ellipsoids to individual data and the calculated the ellipsoid volume. Results demonstrated a significant volume-by-age interaction, whereby increased ellipsoid volume (space the tool occupied) related to increased mean dwell time for the older adult group only; younger adults did not demonstrate this relationship. Additionally, older adults with longer movement times during the fine motor phase also had lower cognitive scores. No age-related differences were observed for the gross motor phase, suggesting that age-related declines in tool-use may be due to changes in fine motor control and cognitive status.

Saccade dynamics during an online updating task change with healthy aging

Goal-directed movements rely on the integration of both visual and motor information, especially during the online control of movement, to fluidly and flexibly control coordinated action. Eye-hand coordination typically plays an important role in goal-directed movements. As people age, various aspects of motor control and visual performance decline (Haegerstrom-Portnoy, Schneck, & Brabyn, 1999; Seidler et al., 2010), including an increase in saccade latencies (Munoz, Broughton, Goldring, & Armstrong, 1998). However, there is limited insight into how age-related changes in saccadic performance impact eye-hand coordination during online control. We investigated this question through the use of a target perturbation paradigm. Older and younger participants completed a perturbation task where target perturbations could occur either early (0 ms) or later (200 ms) after reach onset. We analyzed reach correction latencies and the frequency of the reach correction, coupled with analyses of saccades across all stages of movement. Older participants had slower correction latencies and initiated corrections less frequently compared to younger participants, with this trend being exacerbated in the later (200 ms) target perturbation condition. Older participants also produced slower saccade latencies toward both the initial target and the perturbed target. For trials in which a correction occurred to a late perturbation, touch responses were more accurate when there was more time between the saccade landing and the touch. Altogether, our results suggest that these age-related effects may be due to the delayed acquisition of visual and oculomotor information used to inform the reaching movement, stemming from the increase in saccade latencies before and after target perturbation.

The effect of age and perturbation time on online control during rapid pointing

Visual and proprioceptive information is used differently at different phases of a reach. The time at which a target perturbation occurs during a reach therefore has a significant impact on how an individual can compensate for this perturbation though online control. With healthy ageing, there are notable changes to both sensory and motor control that impact motor performance. However, how the online control process changes with age is not yet fully understood. We used a target perturbation paradigm and manipulated the time at which a target perturbation occurred during the reach to investigate how healthy ageing impacts sensorimotor control. We measured how the latency of the correction and the magnitude of the corrective response changed with perturbation time and quantified the difference across groups using a percentage difference measure. For both groups, online corrections to early perturbations were more easily accounted for than those to late perturbations, despite late perturbations eliciting faster correction latencies. While there was no group difference in accuracy, older participants were slower overall and produced a correction to a change in target location proportionally less often despite similar correction latencies. We speculate that the differences in the time during the reach that the correction is first identified may explain the differences in correction latencies observed between the perturbation time conditions.