The conductivity of the human skull was measured both in vitro and in vivo. The in vitro measurement was performed on a sample of fresh skull placed within a saline environment. For the in vivo measurement a small current was passed through the head by means of two electrodes placed on the scalp. The potential distribution thus generated on the scalp was measured in two subjects for two locations of the current injecting electrodes. Both methods revealed a skull conductivity of about 0.015 [symbol: see text]/m. For the conductivities of the brain, the skull and the scalp a ratio of 1:1/15:1 was found. This is consistent with some of the reports on conductivities found in the literature, but differs considerably from the ratio 1:1/80:1 commonly used in neural source localization. An explanation is provided for this discrepancy, indicating that the correct ratio is 1:1/15:1.

BackgroundTo explore if stimulus–response (S-R) characteristics of the silent period (SP) after transcranial magnetic stimulation (TMS) are affected by changing the SP definition and by changing data presentation in healthy individuals. This information would be clinically relevant to predict motor recovery in patients with stroke using stimulus–response curves.MethodsDifferent landmarks to define the SP onset and offset were used to construct S-R curves from the biceps brachii (BB) and abductor digiti minimi (ADM) muscles in 15 healthy participants using rectified versus non-rectified surface electromyography (EMG). A non-linear mixed model fit to a sigmoid Boltzmann function described the S-R characteristics. Differences between S-R characteristics were compared using paired sample t-tests. The Bonferroni correction was used to adjust for multiple testing.ResultsFor the BB, no differences in S-R characteristics were observed between different SP onset and offset markers, while there was no influence of data presentation either. For the ADM, no differences were observed between different SP onset markers, whereas both the SP offset marker “the first return of any EMG-activity” and presenting non-rectified data showed lower active motor thresholds and less steep slopes.ConclusionsThe use of different landmarks to define the SP offset as well as data presentation affect SP S-R characteristics of the ADM in healthy individuals.

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Our results allow us to formulate a guideline for volume conductor modeling in tDCS. We recommend to accurately model the major tissues between the stimulating electrodes and the target areas, while for efficient yet accurate modeling, an exact representation of other tissues is less important. Because for the low-frequency regime in electrophysiology the quasi-static approach is justified, our results should also be valid for at least low-frequency (e.g., below 100 Hz) transcranial alternating current stimulation.

Transcranial direct current stimulation (tDCS) is a noninvasive brain stimulation technique able to induce long-lasting changes in cortical excitability that can benefit cognitive functioning and clinical treatment. In order to both better understand the mechanisms behind tDCS and possibly improve the technique, finite element models are used to simulate tDCS of the human brain. With the detailed anisotropic head model presented in this study, we provide accurate predictions of tDCS in the human brain for six of the practically most-used setups in clinical and cognitive research, targeting the primary motor cortex, dorsolateral prefrontal cortex, inferior frontal gyrus, occipital cortex, and cerebellum. We present the resulting electric field strengths in the complete brain and introduce new methods to evaluate the effectivity in the target area specifically, where we have analyzed both the strength and direction of the field. For all cerebral targets studied, the currently accepted configurations produced sub-optimal field strengths. The configuration for cerebellum stimulation produced relatively high field strengths in its target area, but it needs higher input currents than cerebral stimulation does. This study suggests that improvements in the effects of transcranial direct current stimulation are achievable.

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The generation of the surface electromyogram (sEMG) is described with regard to the properties of the single muscle fiber action potential as source, the physical aspects of volume conduction and recording configuration, and the properties and firing pattern of motor units (MUs). The spatial aspect of the motor unit action potential (MUP) is emphasized in relation to the results of high-density, multichannel sEMG measurements. The endplate zone, depth, size, and position of MUs can be estimated. The use of muscle fiber conduction velocity measurements in channelopathies and the changes in pathological fatigue are described. Using the unique patterns of spatial spread of MUPs over the skin (MU fingerprint), MU classification and the determination of firing moments is done noninvasively. Clinical applications of high-density sEMG measurements are reviewed. Emerging possibilities provided by MUP size and fingerprint measurements in neuromuscular disease and motor control are discussed. We conclude that multichannel sEMG adds unique, and sometimes indispensable, spatial information to our knowledge of the motor unit.

Abstract-The accuracy of predictions of muscle force based on electromyography (EMG) is an important issue in biomechanics and kinesiology. Since human skeletal muscles show a high diversity and heterogeneity in their fiber architecture, it is difficult to properly align electrodes to the muscle fiber direction. Against this background, we analyzed the effect of different bipolar configuration directions on EMG-based force estimation. In addition, we investigated whether principal component analysis (PCA) can improve this estimation. High-density surface-EMG from the triceps brachii muscle and the extension force of the elbow were measured in 11 subjects. The root mean square difference (RMSD) between predicted and measured force was determined. We found the best bipolar configuration direction to cause a 13% lower RMSD relative to the worst direction. Optimal results were obtained with electrodes aligned with the expected main muscle fiber direction. We found that PCA reduced RMSD by about 40% compared to conventional bipolar electrodes and by about 12% compared to optimally aligned multiple bipolar electrodes. Thus, PCA contributes to the accuracy of EMG-based estimation of muscle force when using a high-density EMG grid.Index Terms-Force estimation, heterogeneous muscle fiber architecture, human, principal component analysis, redundancy, surface electromyography.