The Influence of Age on the Intermanual Transfer and Retention of Implicit Visuomotor Adaptation.

We examined age-related changes in intermanual transfer and retention of implicit visuomotor adaptation. We further asked if providing augmented somatosensory feedback regarding movement endpoint would enhance visuomotor adaptation. Twenty young adults and twenty older adults were recruited and randomly divided into an Augmented Feedback group and a Control group. All participants reached to five visual targets with visual feedback rotated 30° counter-clockwise relative to their actual hand motion. Augmented somatosensory feedback was provided at the end of the reach via the robotic handle that participants held. Implicit adaptation was assessed in the absence of visual feedback in the right trained hand and in the left untrained hand following rotated training trials to establish implicit adaptation and intermanual transfer of adaptation respectively. Participants then returned 24 hours later to assess retention in the trained and untrained hands. Results revealed that older adults demonstrated a comparable magnitude of implicit adaptation, transfer and retention of visuomotor adaptation as observed in younger adults, regardless of the presence of augmented somatosensory feedback. To conclude, when visuomotor adaptation is driven implicitly, intermanual transfer and retention do not differ significantly between young and older adults, even when the availability of augmented somatosensory feedback is manipulated.

Age-related changes in upper limb coordination in a complex reaching task.

When reaching to targets within arm's reach, intentional trunk motion must be neutralized by compensatory motion of the upper limb (UL). Advanced age has been associated with deterioration in the coordination of multi-joint UL movements. In the current study, we looked to determine if older adults also have difficulties modifying their UL movements (i.e., coordination between the shoulder and elbow joints), during a complex reaching task when trunk motion is manipulated. Two groups of healthy participants were recruited: 18 young (mean age = 24.28 ± 2.89 years old) and 18 older (mean age = 72.11 ± 2.39 years old) adults. Participants reached to a target with their eyes closed, while simultaneously moving the trunk forward. In 40% of trials, the trunk motion was unexpectedly blocked. Participants performed the task with both their dominant and non-dominant arms, and at a preferred and fast speed. All participants were able to coordinate motion at the elbow and shoulder joints in a similar manner and modify this coordination in accordance with motion at the trunk, regardless of the hand used or speed of movement. Specifically, in reaches that involved forward trunk motion (free-trunk trials), all participants demonstrated increased elbow flexion (i.e., less elbow extension) compared to blocked-trunk trials. In contrast, when trunk motion was blocked (blocked-trunk trials), all reaching movements were accompanied by increased shoulder horizontal adduction. While coordination of UL joints was similar across older and young adults, the extent of changes at the elbow and shoulder was smaller and less consistent in older adults compared to young participants, especially when trunk motion was involved. These results suggest that older adults can coordinate their UL movements based on task requirements, but that their performance is not as consistent as young adults.

Age differences in arm-trunk coordination during trunk-assisted reaching.

Reaching for an object is a basic motor skill that requires precise coordination between elbow, shoulder and trunk motion. The purpose of this research study was to examine age-related differences in compensatory arm-trunk coordination during trunk-assisted reaching. To engage the arm and trunk, an older and younger group of participants were asked to (1) maintain a fixed hand position while flexing forward at the trunk [stationary hand task (SHT)] and (2) reach to a within-arm's reach target while simultaneously flexing forward at the trunk [reaching hand task (RHT)] (Raptis et al. in J Neurophysiol 97:4069-4078, 2007; Sibindi et al. in J Vestib Res 23:237-247, 2013). Both tasks were completed with eyes closed. Participants completed the two tasks with their dominant and non-dominant arms, and at both a fast and a preferred speed. On average, young and older participants performed in a similar manner in the SHT, such that they maintained their hand position by compensating for trunk movement with modifications of the elbow and shoulder joints. In the RHT, young and older participants had similar endpoint accuracy. This similarity in performance between young and older participants in the SHT and RHT tasks was observed regardless of the arm used or movement speed. However, for both tasks, movements in older adults were significantly more variable compared to younger adults as shown by the larger variability in arm-trunk coordination performance (gain scores) in the SHT and higher movement time variability in the RHT. Thus, results imply that older adults maintain their ability to coordinate arm and trunk movements efficiently during reaching actions but are not as consistent as younger adults.

Sensory integration during reaching: the effects of manipulating visual target availability.

When using visual and proprioceptive information to plan a reach, it has been proposed that the brain combines these cues to estimate the object and/or limb's location. Specifically, according to the maximum-likelihood estimation (MLE) model, sensory inputs are combined such that more reliable inputs are assigned a greater weight (Ernst and Banks in Nature 415:429-433, 2002). In this paper, we examined if the brain is able to adjust which sensory cue it weights the most. Specifically, we asked if the brain changes how it weights sensory information when the availability of a visual cue is manipulated. Twelve healthy subjects reached to visual (V), proprioceptive (P), or visual + proprioceptive (VP) targets under different visual delay conditions (e.g., on V and VP trials, the visual target was available for the entire reach; it was removed with the go signal, or it was removed 1 s before the go signal). To establish which sensory cue subjects weighted the most, we compared endpoint positions achieved on V and P reaches to VP reaches. Results indicated that subjects combined visual and proprioceptive cues in accordance with the MLE model when reaching to VP targets. Moreover, subjects' reaching errors to visual targets increased with longer visual delays (particularly in the vertical direction). However, there was no change in reach variability with longer delays, and subjects did not reweight visual information as the availability of visual information was manipulated. Thus, a change in visual environment is not sufficient to cause the brain to reweight how it processes sensory information.