Regional recruitment and differential behavior of motor units during postural control in older adults.

Aging is associated with neuromuscular system changes that may have implications for the recruitment and firing behaviors of motor units (MUs). In previous studies, we observed that young adults recruit subpopulations of triceps surae MUs during tasks that involved leaning in five directions: common units that were active during different leaning directions and unique units that were active in only one leaning direction. Furthermore, the MU subpopulation firing behaviors [average firing rate (AFR), coefficient of variation (CoVISI), and intermittent firing] modulated with leaning direction. The purpose of this study was to examine whether older adults exhibited this regional recruitment of MUs and firing behaviors. Seventeen older adults (aged 74.8 ± 5.3 yr) stood on a force platform and maintained their center of pressure leaning in five directions. High-density surface electromyography recordings from the triceps surae were decomposed into single MU action potentials. A MU tracking analysis identified groups of MUs as being common or unique across the leaning directions. Although leaning in different directions did not affect the AFR and CoVISI of common units (P > 0.05), the unique units responded to the leaning directions by increasing AFR and CoVISI, albeit modestly (F = 18.51, P < 0.001). The unique units increased their intermittency with forward leaning (F = 9.22, P = 0.003). The mediolateral barycenter positions of MU activity in both subpopulations were found in similar locations for all leaning directions (P > 0.05). These neuromuscular changes may contribute to the reduced balance performance seen in older adults.NEW & NOTEWORTHY In this study, we observed differences in motor unit recruitment and firing behaviors of distinct subpopulations of motor units in the older adult triceps surae muscle from those observed in the young adult. Our results suggest that the older adult central nervous system may partially lose the ability to regionally recruit and differentially control motor units. This finding may be an underlying cause of balance difficulties in older adults during directionally challenging leaning tasks.

Differential behavior of distinct motoneuron pools that innervate the triceps surae.

It has been shown that when humans lean in various directions, the central nervous system (CNS) recruits different motoneuron pools for task completion; common units that are active during different leaning directions, and unique units that are active in only one leaning direction. We used high-density surface electromyography (HD-sEMG) to examine if motor unit (MU) firing behavior was dependent on leaning direction, muscle (medial and lateral gastrocnemius; soleus), limits of stability, or whether a MU is considered common or unique. Fourteen healthy participants stood on a force platform and maintained their center of pressure in five different leaning directions. HD-sEMG recordings were decomposed into MU action potentials and the average firing rate (AFR), coefficient of variation (CoVISI), and firing intermittency were calculated on the MU spike trains. During the 30°-90° leaning directions both unique units and common units had higher firing rates (F = 31.31, P < 0.0001). However, the unique units achieved higher firing rates compared with the common units (mean estimate difference = 3.48 Hz, P < 0.0001). The CoVISI increased across directions for the unique units but not for the common units (F = 23.65, P < 0.0001). Finally, intermittent activation of MUs was dependent on the leaning direction (F = 11.15, P < 0.0001), with less intermittent activity occurring during diagonal and forward-leaning directions. These results provide evidence that the CNS can preferentially control separate motoneuron pools within the ankle plantarflexors during voluntary leaning tasks for the maintenance of standing balance.NEW & NOTEWORTHY In this study, we demonstrate that the different subpopulations of motor units within the three muscles comprising the ankle plantarflexors behave differently during multidirectional leaning. Our results suggest that the central nervous system has the capability to control distinct subpopulations of motor units to meet the force requirements necessary for leaning. This may allow for a precise, efficient, and flexible control strategy for the maintenance of standing balance.

Maintenance of standing posture during multi-directional leaning demands the recruitment of task-specific motor units in the ankle plantarflexors.

The purpose of this study is to investigate whether regional modulation of the ankle plantarflexors during standing was related to the recruitment of motor units associated with force direction. Fourteen participants performed a multi-directional leaning task in standing. Participants stood on a force platform and maintained their center of pressure in five different target directions. Motor unit firings were extracted by decomposition of high-density surface electromyograms recorded from the ankle plantarflexor muscles. The motor unit barycentre, defined as the weighted mean of the maximal average rectified values across columns and rows, was used to evaluate the medio-lateral and proximo-distal changes in the surface representation of single motor units across different leaning target directions. Using a motor unit tracking analysis, groups of motor units were identified as being common or unique across the target directions. The leaning directions had an effect on the spatial representations of motor units in the medial gastrocnemius and soleus (p < 0.05), but not in the lateral gastrocnemius (p > 0.05). Motor unit action potentials were represented in the medial and proximal aspects of the muscles during forward vs. lateral leans. Further analysis determined that the common motor units were found in similar spatial locations across the target directions, whereas newly recruited unique motor units were found in different spatial locations according to target direction (p < 0.05). The central nervous system may possess the ability to activate different groups of motor units according to task demands to meet the force-direction requirements of the leaning task.

Do Performance Measures of Strength, Balance, and Mobility Predict Quality of Life and Community Reintegration After Stroke?

OBJECTIVE: To investigate the extent to which physical performance measures of strength, balance, and mobility taken at discharge from inpatient stroke rehabilitation can predict health-related quality of life (HRQoL) and community reintegration after 6 months. DESIGN: Longitudinal study. SETTING: University laboratory. PARTICIPANTS: Adults (N=75) recruited within 1 month of discharge home from inpatient stroke rehabilitation. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: 36-Item Short Form Health Survey (SF-36) for HRQoL and Subjective Index of Physical and Social Outcome (SIPSO) for community reintegration. Physical performance measures were the 6-minute walk test, timed Up and Go (TUG) test, Berg Balance Scale, Community Balance and Mobility Scale, and isokinetic torque and power of hip, knee, and ankle on the paretic and nonparetic sides. Other prognostic variables included age, sex, stroke type and location, comorbidities, and motor FIM score. RESULTS: Separate stepwise linear regressions were performed using the SF-36 and SIPSO as dependent variables. The total paretic lower limb torque and 6-minute walk test predicted the SF-36 Physical Component Summary (adjusted R2=.30). The total paretic lower limb torque and TUG test predicted the SIPSO physical component (adjusted R2=.47). The total paretic lower limb torque significantly predicted the SF-36 Mental Component Summary, but the adjusted R2 was low (.06). Similarly, the TUG test significantly predicted the SIPSO social component, but again the adjusted R2 was low (.09). CONCLUSIONS: Measures of physical performance including muscle strength and mobility at discharge can partially predict HRQoL and community reintegration 6 months later. Further research is necessary for more accurate predictions.