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Abstract-In this paper, we provide a broad overview of models and technologies pertaining to transcranial current brain stimulation (tCS), a family of related noninvasive techniques including direct current (tDCS), alternating current (tACS), and random noise current stimulation (tRNS). These techniques are based on the delivery of weak currents through the scalp (with electrode current intensity to area ratios of about 0.3-5 A/m ) at low frequencies (typically 1kHz) resulting in weak electric fields in the brain (with amplitudes of about 0.2-2 V/m). Here we review the biophysics and simulation of noninvasive, current-controlled generation of electric fields in the human brain and the models for the interaction of these electric fields with neurons, including a survey of in vitro and in vivo related studies. Finally, we outline directions for future fundamental and technological research.Index Terms-Brain stimulation, electrical stimulation, transcranial alternating current (tACS), transcranial current stimulation (tCS), transcranial direct current (tDCS), transcranial random noise current stimulation (tRNS).

The use of alternating electric fields has been recently proposed for the treatment of recurrent glioblastoma. In order to predict the electric field distribution in the brain during the application of such tumor treating fields (TTF), we constructed a realistic head model from MRI data and placed transducer arrays on the scalp to mimic an FDA-approved medical device. Values for the tissue dielectric properties were taken from the literature; values for the device parameters were obtained from the manufacturer. The finite element method was used to calculate the electric field distribution in the brain. We also included a “virtual lesion” in the model to simulate the presence of an idealized tumor. The calculated electric field in the brain varied mostly between 0.5 and 2.0 V/cm and exceeded 1.0 V/cm in 60% of the total brain volume. Regions of local field enhancement occurred near interfaces between tissues with different conductivities wherever the electric field was perpendicular to those interfaces. These increases were strongest near the ventricles but were also present outside the tumor’s necrotic core and in some parts of the gray matter-white matter interface. The electric field values predicted in this model brain are in reasonably good agreement with those that have been shown to reduce cancer cell proliferation in vitro. The electric field distribution is highly non-uniform and depends on tissue geometry and dielectric properties. This could explain some of the variability in treatment outcomes. The proposed modeling framework could be used to better understand the physical basis of TTF efficacy through retrospective analysis and to improve TTF treatment planning.

Both biophysical and neurophysiological aspects need to be considered to assess the impact of electric fields induced by transcranial current stimulation (tCS) on the cerebral cortex and the subsequent effects occurring on scalp EEG. The objective of this work was to elaborate a global model allowing for the simulation of scalp EEG signals under tCS. In our integrated modeling approach, realistic meshes of the head tissues and of the stimulation electrodes were first built to map the generated electric field distribution on the cortical surface. Secondly, source activities at various cortical macro-regions were generated by means of a computational model of neuronal populations. The model parameters were adjusted so that populations generated an oscillating activity around 10 Hz resembling typical EEG alpha activity. In order to account for tCS effects and following current biophysical models, the calculated component of the electric field normal to the cortex was used to locally influence the activity of neuronal populations. Lastly, EEG under both spontaneous and tACS-stimulated (transcranial sinunoidal tCS from 4 to 16 Hz) brain activity was simulated at the level of scalp electrodes by solving the forward problem in the aforementioned realistic head model. Under the 10 Hz-tACS condition, a significant increase in alpha power occurred in simulated scalp EEG signals as compared to the no-stimulation condition. This increase involved most channels bilaterally, was more pronounced on posterior electrodes and was only significant for tACS frequencies from 8 to 12 Hz. The immediate effects of tACS in the model agreed with the post-tACS results previously reported in real subjects. Moreover, additional information was also brought by the model at other electrode positions or stimulation frequency. This suggests that our modeling approach can be used to compare, interpret and predict changes occurring on EEG with respect to parameters used in specific stimulation configurations.

Much of our knowledge about the electric field distribution in transcranial current stimulation (tCS) still relies on results obtained from layered spherical head models. In this work we created a high resolution finite element model of a human head by segmentation of MRI images, and paid particular attention to the representation of the cortical sheet. This model was then used to calculate the electric field induced by two electrodes: an anode placed above the left motor cortex, and a cathode placed over the right eyebrow. The results showed that the maxima of the current density appear located on localized hotspots in the bottom of sulci and not on the cortical surface as would be expected from spherical models. This also applies to the components of the current density normal and tangential to the cortical surface. These results show that such highly detailed head models are needed to correctly predict the effects of tCS on cortical neurons.