Nonphysiological factors in navigated TMS studies; confounding covariates and valid intracortical estimates.

ABSTRACT

UNLABELLED Brain stimulation is used to induce transient alterations of neural excitability to probe or modify brain function. For example, single-pulse transcranial magnetic stimulation (TMS) of the motor cortex can probe corticospinal excitability (CSE). Yet, CSE measurements are confounded by a high level of variability. This variability is due to physical and physiological factors. Navigated TMS (nTMS) systems can record physical parameters of the TMS coil (tilt, location, and orientation) and some also estimate intracortical electric fields (EFs) on a trial-by-trial basis. Thus, these parameters can be partitioned with stepwise regression. PURPOSE: The primary objective was to dissociate variance due to physical parameters from variance due to physiological factors for CSE estimates. The secondary objective was to establish the predictive validity of EF estimates from spherical head models. HYPOTHESIS: Variability of physical parameters of TMS predicts CSE variability. METHODS: Event-related measurements of physical parameters were analyzed in stepwise regression. Partitioned parameter variance and predictive validity were compared for a target-controlled and a nontarget-controlled experiment. A control experiment (preinnervation) confirmed the validity of linear data analysis. A bias-free model quantified the effect of divergence from optimum. RESULTS: Partitioning physical parameter variance reduces CSE variability. EF estimates from spherical models were valid. Post hoc analyses showed that even small physical fluctuations can confound the statistical comparison of CSE measurements. CONCLUSIONS: It is necessary to partition physical and physiological variance in TMS studies to make confounded data interpretable. The spatial resolution of nTMS is <5 mm and the EF-estimates are valid.