Effect of standing posture on inhibitory postsynaptic potentials in gastrocnemius motoneurons

Normobaric hypoxia does not influence the sural nerve cutaneous reflex during standing

Hypoxia increases postural sway compared to normoxia, but the underlying sensorimotor factors remain unclear. An important contributor to balance control is cutaneous feedback arising from the feet, which can be partially characterized by electrically evoking a reflex from a purely cutaneous nerve (i.e., sural) and sampling the subsequent motor activity of a muscle. The purpose of the present study was to determine how normobaric hypoxia influences sural nerve reflex parameters during a standing posture. It was hypothesized that normobaric hypoxia would reduce cutaneous reflex area compared to normoxia. Participants (n = 16; 5 females, 11 males) stood with their feet together while receiving two trials of 50 sural nerve stimulations (200-Hz, 5-pulse train, presented randomly every 3-6 s) at baseline (BL; normoxia), and at 2 (H2) and 4 (H4) h of normobaric hypoxia (~ 0.11 fraction of inspired oxygen in a hypoxic chamber). The sural nerve reflex was recorded using surface electromyography from the left medial gastrocnemius, and characterized by area and duration of the initial positive and negative peaks of the response. When normalized to pre-stimulus electromyography, the area of the peak-to-peak cutaneous reflex was not different than BL (p ≥ 0.14) for up to 4 h of normobaric hypoxia (BL: 0.26 ± 0.22, H2: 0.19 ± 0.19, H4: 0.22 ± 0.20 A.U.). Furthermore, the duration of the response was not different during hypoxia (BL: 73.2 ± 42.4; H2: 75.2 ± 47.0; H4: 77.6 ± 54.6 ms; p ≥ 0.13) than BL. Thus, reflexes arising from cutaneous afferents of the lateral border of the foot are resilient to at least 4 h of normobaric hypoxia.

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 (CoV_ISI), 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 CoV_ISI 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.

Estimating Exercise-Induced Changes in Human Neuronal Networks

Although several methods have been used to estimate exercise-induced changes in human neuronal networks, there are growing doubts about the methodologies used. This review describes a single motor unit-based method that minimizes the errors inherent in classical methods. With this method, it is now possible to identify human neuronal networks' changes due to exercise.