Effect of Mechanical Loading and Bone Loss on Motor Neuron Activity-H-Reflex Relationship

The Effect of Mechanical Loading and Bone Loss on the Relationship Between Motor Neuron Pool Activity and H-Reflex Amplitude

Weight-bearing exercises (e.g., running, jumping, whole-body vibration) are widely practiced due to their beneficial effects on bone development and their role in the prevention and treatment of osteoporosis. However, the underlying neuroregulatory mechanisms responsible for these positive effects have not yet been fully understood. Two main neuromodulatory mechanisms have been proposed in the literature: (i) spinal reflexes originating from muscle spindles (stretch reflex, tonic vibration reflex), and (ii) the bone myoregulation reflex (BMR) based on load-sensitive osteocytes.

It is well established that increased voluntary contraction and the associated rise in background EMG activity, that is, motor neuron pool activity, enhance muscle spindle-based reflex responses (such as the H-reflex and tendon reflex). In contrast, it has been demonstrated that the H-reflex is suppressed during bone-loading activities such as single-leg stance, jumping, or whole-body vibration.

This study is based on two hypotheses:

• As mechanical loading increases, Ia inhibitory effects intensify, leading to greater H-reflex suppression.
• During whole-body vibration, the H-reflex is suppressed due to Ia inhibition.

If this inhibition originates from load-sensitive receptors-osteocytes-and thus from the BMR, then in osteoporosis, where osteocyte number and function are reduced, H-reflex suppression will be diminished.

The aim of this research is to test these hypotheses. Confirmation of these assumptions would suggest that reflex control during weight-bearing exercise occurs predominantly through osteocyte-mediated BMR mechanisms rather than muscle spindle-based mechanisms such as the stretch or tonic vibration reflex.

EMG and Force Data Acquisition

Surface EMG signals from the soleus muscle, accelerometer data from the whole-body vibration platform, and force sensor data will be collected at a 2 kHz sampling rate using a data acquisition system (CED 3601 Power 1401 MKII digital-to-analogue converter and CED 1902 Quad System MKIII amplifier). Data analysis will be performed using Spike2 version 7.20 software.

Subjects will be tested while standing on both feet. A force load cell (FC2231-0000-0100-L Compression Load Sensor, France) will be placed under the right heel of the subjects to obtain real-time readings of the weight applied to the right heel.

Before attaching the electrodes, any hair on the skin will be shaved, and the skin will be cleaned with alcohol wipes to remove surface oils. An ECG gel will be applied to increase skin conductivity.

A PowerPlate Pro5 (London, UK) device will be used to apply whole-body vibration.

________________________________________ H-reflex Measurement

A cathode electrode (1 cm diameter round electrode) will be positioned over the tibial nerve in the right popliteal fossa, and an anode electrode (10 × 10 cm) will be placed over the suprapatellar area. Stimulation will be delivered using a constant-current stimulator [model DS7A, Digitimer Ltd, Hertfordshire, UK] with monophasic rectangular current pulses of 1 ms duration. The current intensity will start at 5 mA and will be incrementally increased. The intensity required to obtain the recruitment curve of the H-reflex and the maximum M-response (Mmax) will be determined. A current intensity that elicits an M-response of 10-30% of Mmax will be used to minimize variations in H-reflex amplitude depending on stimulus intensity.

H-reflex will be measured in six different conditions. First, subjects will be asked to place 10%, 30%, 50%, 70%, and 100% of their body weight on their right leg in a random order. A monitor displaying real-time feedback of the weight applied to the right leg will be placed in front of the subjects to help stabilize the target load. The target weight percentage will be indicated on the monitor. For each load condition, 10 H-reflex measurements will be obtained at 10-second intervals.

Afterward, a 1-minute-long 30 Hz low-amplitude (1.2 mm) whole-body vibration will be applied to the subjects, and the H-reflex will be measured every 5 seconds.

To assess motor neuron activity, the EMG activity in the 100 ms preceding the electrical stimulation will be quantified as RMS amplitude.

________________________________________ Bone Myoregulation Reflex

10-second long low-amplitude (1.2 mm) whole-body vibrations of 30 Hz, 32 Hz, 34 Hz, and 36 Hz will be applied to the subjects. Cumulative averaging method will be used to measure latency of bone myoregulation reflex.

________________________________________ Sample Size Calculation

In this study, the H-reflex amplitude will be measured under five different loading conditions and during whole-body vibration in two groups. Assuming an effect size (partial eta squared) of 0.06, an alpha error level of 0.05, and a statistical power of 0.9, the minimum required sample size will be calculated as 12 subjects per group, for a total of 24 subjects. The sample size calculation will be performed using G*Power version 3.1.9.4 (Franz Faul, Universität Kiel, Germany).

________________________________________ Statistical Analysis

The normality of data distribution will be assessed using the Shapiro-Wilk test. Variables showing a normal distribution will be presented as mean ± standard deviation, whereas non-normally distributed variables will be summarized as median (interquartile range).

H-reflex amplitude and background EMG activity measured under five different loading conditions and during whole-body vibration will be compared using repeated-measures analysis of variance (ANOVA) when the assumption of normality is met. Tukey or Bonferroni post-hoc tests will be applied when appropriate. When the normality assumption is violated, the Friedman test will be used, and pairwise comparisons will be performed using the Wilcoxon test. Bonferroni correction will be applied for post-hoc analyses.

All statistical analyses will be conducted using SPSS software (version 18.0; SPSS Inc., Chicago, IL, USA).

Inclusion Criteria:

• Being in the postmenopausal period
• For the osteoporosis group: having femoral osteoporosis (femoral neck or total femur T-score ≤ -2.5)
• For the control group: having no osteoporosis or osteopenia (femoral neck and total femur T-scores > -1, and L1-L4 and L2-L4 T-scores > -1)
• Being a volunteer

Exclusion Criteria:

• Receiving osteoporosis treatment
• Having a peripheral or central nervous system disorder (e.g., stroke, polyneuropathy, radiculopathy, entrapment neuropathy, etc.)
• Having acquired or hereditary muscle diseases (myopathies)
• Having active painful lower extremity pathologies (e.g., osteoarthritis, inflammatory joint diseases, etc.)
• Having cardiac arrhythmias
• Having a history of other metabolic bone diseases
• Having skin lesions at the electrode placement sites on the lower extremities
• Being older than 65 years