What has transcranial magnetic stimulation taught us about neural adaptations to strength training? A brief review

The evidence for neural mechanisms underpinning rapid strength increases has been investigated and discussed for over 30 years using indirect methods, such as surface electromyography, with inferences made toward the nervous system. Alternatively, electrical stimulation techniques such as the Hoffman reflex, volitional wave, and maximal wave have provided evidence of central nervous system changes at the spinal level. For 25 years, the technique of transcranial magnetic stimulation (TMS) has allowed for noninvasive supraspinal measurement of the human nervous system in a number of areas such as fatigue, skill acquisition, clinical neurophysiology, and neurology. However, it has only been within the last decade that this technique has been used to assess neural changes after strength training. The aim of this brief review is to provide an overview of TMS, discuss specific strength training studies that have investigated changes, after short-term strength training in healthy populations in upper and lower limbs, and conclude with further research suggestions and the application of this knowledge for the strength and conditioning coach.

A comparison of two methods in acquiring stimulus-response curves with transcranial magnetic stimulation

Background
The stimulus–response (S–R) curve is a well accepted constituent in transcranial magnetic stimulation (TMS) studies. However, it has been suggested that parameters of the S–R curve differ when stimuli are provided in a “ramped” (measured steps from low to high intensity), or “random” fashion.

Hypothesis
We hypothesized that there would be no difference in the parameters of the S–R curve between either methodologies.

Methods
Using a randomised cross-over design, 10 healthy participants (29.6 ± 6.4 yrs, 3 f) completed “ramped” or “random” curves in biceps brachii (BB) and first dorsal interosseous (FDI) muscles of both limbs. Curves were compared using mixed-factor ANOVA and correlated between limbs and methodologies.

Results
No differences (P > 0.05) and high correlations (range 0.71–0.97; P < 0.001) were observed in BB and FDI data between curves.

Conclusions
This study demonstrated that either methodology provides similar parameters of the S–R curve in healthy participants.