Method to assess the mismatch between the measured and nominal parameters of transcranial magnetic stimulation devices.

BACKGROUND: Small variations in TMS parameters, such as pulse frequency and amplitude may elicit distinct neurophysiological responses. Assessing the mismatch between nominal and experimental parameters of TMS stimulators is essential for safe application and comparisons of results across studies. NEW METHOD: A search coil was used to assess exactness and precision errors of amplitude and timing parameters such as interstimulus interval, the period of pulse repetition, and intertrain interval of TMS devices. The method was validated using simulated pulses and applied to six commercial stimulators in single-pulse (spTMS), paired-pulse (ppTMS), and repetitive (rTMS) protocols, working at several combinations of intensities and frequencies. RESULTS: In a simulated signal, the maximum exactness error was 1.7% for spTMS and the maximum precision error 1.9% for ppTMS. Three out of six TMS commercial devices showed exactness and precision errors in spTMS amplitude higher than 5%. Moreover, two devices showed amplitude exactness errors higher than 5% in rTMS with parameters suggested by the manufactures. COMPARISON WITH EXISTING METHODS: Currently available tools allow characterization of induced electric field intensity and focality, and pulse waveforms of a single TMS pulse. Our method assesses the mismatch between nominal and experimental values in spTMS, ppTMS and rTMS protocols through the exactness and precision errors of amplitude and timing parameters. CONCLUSION: This study highlights the importance of evaluating the physical characteristics of TMS devices and protocols, and provides a method for on-site quality assessment of multiple stimulation protocols in clinical and research environments.

Effect of TMS coil orientation on the spatial distribution of motor evoked potentials in an intrinsic hand muscle.

Previous reports on the relationship between coil orientation and amplitude of motor evoked potential (MEP) in transcranial magnetic stimulation (TMS) did not consider the effect of electrode arrangement. Here we explore this open issue by investigating whether TMS coil orientation affects the amplitude distribution of MEPs recorded from the abductor pollicis brevis (APB) muscle with a bi-dimensional grid of 61 electrodes. Moreover, we test whether conventional mono- and bipolar montages provide representative MEPs compared to those from the grid of electrodes. Our results show that MEPs with the greatest amplitudes were elicited for 45° and 90° coil orientations, i.e. perpendicular to the central sulcus, for all electrode montages. Stimulation with the coil oriented at 135° and 315°, i.e. parallel to the central sulcus, elicited the smallest MEP amplitudes. Additionally, changes in coil orientation did not affect the spatial distribution of MEPs over the muscle extent. It has been shown that conventional electrodes with detection volume encompassing the APB belly may detect representative MEPs for optimal coil orientations. In turn, non-optimal orientations were identified only with the grid of electrodes. High-density electromyography may therefore provide new insights into the effect of coil orientation on MEPs from the APB muscle.

Can somatosensory electrical stimulation relieve spasticity in post-stroke patients? A TMS pilot study.

Evidence suggests that somatosensory electrical stimulation (SES) may decrease the degree of spasticity from neural drives, although there is no agreement between corticospinal modulation and the level of spasticity. Thus, stroke patients and healthy subjects were submitted to SES (3 Hz) for 30' on the impaired and dominant forearms, respectively. Motor evoked potentials induced by single-pulse transcranial magnetic stimulation were collected from two forearm muscles before and after SES. The passive resistance of the wrist joint was measured with an isokinetic system. We found no evidence of an acute carry-over effect of SES on the degree of spasticity.

Performance quantification of clustering algorithms for false positive removal in fMRI by ROC curves

Abstract Introduction Functional magnetic resonance imaging (fMRI) is a non-invasive technique that allows the detection of specific cerebral functions in humans based on hemodynamic changes. The contrast changes are about 5%, making visual inspection impossible. Thus, statistic strategies are applied to infer which brain region is engaged in a task. However, the traditional methods like general linear model and cross-correlation utilize voxel-wise calculation, introducing a lot of false-positive data. So, in this work we tested post-processing cluster algorithms to diminish the false-positives. Methods In this study, three clustering algorithms (the hierarchical cluster, k-means and self-organizing maps) were tested and compared for false-positive removal in the post-processing of cross-correlation analyses. Results Our results showed that the hierarchical cluster presented the best performance to remove the false positives in fMRI, being 2.3 times more accurate than k-means, and 1.9 times more accurate than self-organizing maps. Conclusion The hierarchical cluster presented the best performance in false-positive removal because it uses the inconsistency coefficient threshold, while k-means and self-organizing maps utilize a priori cluster number (centroids and neurons number); thus, the hierarchical cluster avoids clustering scattered voxels, as the inconsistency coefficient threshold allows only the voxels to be clustered that are at a minimum distance to some cluster.