For several decades, studies throughout the motor control literature have claimed synchronization of motor unit firings result from common presynaptic branches, or “common inputs” shared by the motoneurons. However, the methods that support this notion have lacked necessary statistical rigor to establish their validity.

Recognizing this discrepancy, Drs. Carlo J. De Luca and Joshua Kline have created a statistically sound approach for measuring synchronization of motor unit firings.

The innovative method, known as SigMax, is a statistically-based analysis that is independent of the distribution of each motor unit’s firing instances, and does not assume that synchronization is inherent between motoneurons.

To test the SigMax method against other common synchronization detection methods, the Delsys dEMG System for signal decomposition was used to obtain over 17,000 motor unit pairs and more than 1,000,000 firings from the first dorsal interosseous and vastus lateralis muscles.

Relative to the SigMax method, they observed other approaches were subject to false detections, missed observations, and incorrect estimations of synchronization. Most notably, it was shown through the SigMax method that only 50% of motor unit pairs achieved synchronization, corroborating evidence against the notion that common inputs are responsible for synchronization amongst all motor units of a muscle.

Ideally, this study will seek to encourage motor unit investigators to pursue statistically-based techniques when measuring synchronization. It is, in effect, a far more reliable way to understand the true physiological mechanisms behind motor unit control.


      De Luca CJ and Kline JC. Statistically rigorous calculations do not support Common Input and Long-Term synchronization of motor unit firings.

Journal of Neurophysiology

    112: 2729-2744, 2014.