Coherence between electromyographic signals of anterior tibialis, soleus, and gastrocnemius during standing balance tasks

IntroductionKnowledge about the mechanics and physiological features of balance for healthy individuals enhances understanding of impairments of balance related to neuropathology secondary to aging, diseases of the central nervous system (CNS), and traumatic brain injury, such as concussion. MethodsWe examined the neural correlations during muscle activation related to quiet standing from the intermuscular coherence in different neural frequency bands. Electromyography (EMG) signals were recorded from six healthy participants (fs = 1,200 Hz for 30 s) from three different muscles bilaterally: anterior tibialis, medial gastrocnemius, and soleus. Data were collected for four different postural stability conditions. In decreasing order of stability these were feet together eyes open, feet together eyes closed, tandem eyes open, and tandem eyes closed. Wavelet decomposition was used to extract the neural frequency bands: gamma, beta, alpha, theta, and delta. Magnitude-squared-coherence (MSC) was computed between different muscle pairs for each of the stability conditions. Results and discussionThere was greater coherence between muscle pairs in the same leg. Coherence was greater in lower frequency bands. For all frequency bands, the standard deviation of coherence between different muscle pairs was always higher in the less stable positions. Time-frequency coherence spectrograms also showed higher intermuscular coherence for muscle pairs in the same leg and in less stable positions. Our data suggest that coherence between EMG signals may be used as an independent indicator of the neural correlates for stability.

Automated summary

This study examined the neural correlations during muscle activation related to balance. The results showed greater coherence between muscle pairs in the same leg and in lower frequency bands. The coherence between different muscle pairs was higher in less stable positions. The findings suggest that coherence between EMG signals can be used as an independent indicator of the neural correlates for stability.