Electric fields of motor and frontal tDCS in a standard brain space: A computer simulation study

Abstract

The electric field produced in the brain is the main physical agent of transcranial direct current stimulation (tDCS). Inter-subject variations in the electric fields may help to explain the variability in the effects of tDCS. Here, we use multiple-subject analysis to study the strength and variability of the group-level electric fields in the standard brain space. Personalized anatomically-accurate models of 62 subjects were constructed from T1- and T2-weighted MRI. The finite-element method was used to computationally estimate the individual electric fields, which were registered to the standard space using surface based registration. Motor cortical and frontal tDCS were modelled for 16 electrode montages. For each electrode montage, the group-level electric fields had a consistent strength and direction in several brain regions, which could also be located at some distance from the electrodes. In other regions, the electric fields were more variable, and thus more likely to produce variable effects in each individual. Both the anode and cathode locations affected the group-level electric fields, both directly under the electrodes and elsewhere. For motor cortical tDCS, the electric fields could be controlled at the group level by moving the electrodes. However, for frontal tDCS, the group-level electric fields were more variable, and the electrode locations had only minor effects on the group average fields. Our results reveal the electric fields and their variability at the group level in the standard brain space, providing insights into the mechanisms of tDCS for plasticity induction. The data are useful for planning, analysing and interpreting tDCS studies.

Transcranial Direct Current Stimulation Does Not Affect Lower Extremity Muscle Strength Training in Healthy Individuals: A Triple-Blind, Sham-Controlled Study

“…However, the acute effects are inconsistent across studies (Tanaka et al, 2009, 2011; Montenegro et al, 2015, 2016; Angius et al, 2016; Washabaugh et al, 2016) and seem dependent on tDCS protocols, training tasks, muscle groups, and subject populations. In this context, computational modeling would be useful to understand the different spatial distributions of the electric field induced by different tDCS protocols (electrode configuration, size, or current intensity; Laakso et al, 2015, 2016). …”

“…Twelve subjects per group seem underpowered, although 12 is close to the sample size (15 subjects per group) of Hendy and Kidgell's (2013) study. There is a large inter-individual variation in the outcome of tDCS over the hand motor cortex (Wiethoff et al, 2014; Laakso et al, 2015, 2016), with approximately one-half of subjects failing to respond to the stimulation in the expected manner (Wiethoff et al, 2014). Recently, such a large inter-individual variation was also observed in tDCS over the leg motor cortex (Madhavan et al, 2016; van Asseldonk and Boonstra, 2016).…”

Scalp‐to‐cortex distance of left primary motor cortex and its computational head model: Implications for personalized neuromodulation

“…Except for the same scale (ie, mm) SCD and CT had, the vector‐like properties of SCD, including: (a) direction: SCD is a line starting from the point on the scalp and ending at the point on cerebral cortex and (b) magnitude: the measure of SCD representing the length of the line, also have profound impact on the modeling of tDCS. For instance, recent evidence confirmed that the directionality (or orientation) of the current injection can critically influence the field potential of the targeted region during transcranial electrical stimulation . Therefore, region‐specific SCD not only reflects the individual morphometric features, but also provides a useful and dynamic parameter to optimize the therapeutic protocol.…”

Impact of non-brain anatomy and coil orientation on inter- and intra-subject variability in TMS at midline

“…The main anatomical component of interest for simulations over midline would be the falx cerebri, a layer of dura roughly 2 mm thick that separates the two hemispheres of the brain (Miga et al, 1999). This area is difficult to segment and thus is not even included in the high resolution MIDA head model (Iacono et al, 2015), although it has been modeled as a discontinuous medium in some studies (Laakso et al, 2016b). …”

“…These simulations allowed researchers to look at how both coils and anatomy influence stimulation within individuals, but were limited in their ability to show how stimulation varies between individuals. Recent developments in modeling tools have improved the generation of heterogeneous head models (Windhoff et al, 2013; Thielscher et al, 2015), facilitating the use of several models in studies (Krieg et al, 2015; Lee et al, 2016; Opitz et al, 2013; Laakso et al, 2016a, 2016b; Opitz et al, 2016; Bungert et al, 2016). This is important because the induced E-Field in a single head cannot be representative of the induced E-Field for a population, given the significant differences in head anatomy.…”