A method of compensating for the excitability of spinal motoneurones when estimating the magnitude of potentials evoked in skeletal muscles

In recognition of the mediating influence of spinal motoneurone excitability on the amplitude of motor evoked potentials (MEPs) generated by transcranial magnetic stimulation (TMS), it is customary to reject trials/study participants if the level of electromyographic (EMG) activity recorded before the delivery of TMS exceeds some threshold. The thresholds employed in practice vary considerably (2.5-100 µV) and appear arbitrary. It is now known that a change in root mean squared (r.m.s.) EMG from 1 to 5 µV is associated with a 20% increase in the probability that the MEP amplitude will exceed the 50 µV criterion for resting motor threshold. Furthermore, trial-to-trial fluctuations in r.m.s. EMG over a range not extending beyond 2 µV are associated with systematic variations in the amplitude of MEPs. These outcomes suggest that most EMG rejection thresholds fail in their principal purpose - which is to obviate the influence of spinal motoneurone excitability on the amplitude of evoked potentials. A new method (implemented using both quantile and least squares linear regression techniques) is presented, that can be used to compensate for this influence. Using a very large sample it is demonstrated that when the compensation is adequate, it can alter the ostensible impact of an experimental factor on the magnitude of MEPs. An additional benefit of the method is that it permits the use of most if not all datapoints, and thus preserves the full power of the experimental design. KEY POINTS: Customarily, experimental trials are rejected if electromyographic (EMG) activity recorded before transcranial magnetic stimulation (TMS) exceeds some threshold. In practice, adopted thresholds vary considerably (2.5-100 µV) and appear arbitrary. Most thresholds fail to obviate the influence of spinal motoneurone excitability on the amplitude of motor evoked potentials (MEPs). A new method based on linear regression is described that compensates for the relationship between ('background') EMG and MEP amplitude. The compensation is shown to alter the ostensible impact of experimental factors on the magnitude of MEPs.