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From oscillatory transcranial current stimulation to scalp EEG changes: a biophysical and physiological modeling study.

Merlet I, Birot G, Salvador R, Molaee-Ardekani B, Mekonnen A, Soria-Frish A, Ruffini G, Miranda PC, Wendling F - PLoS ONE (2013)

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: INSERM, Université de Rennes 1, LTSI, Rennes, France. isabelle.merlet@univ-rennes1.fr

ABSTRACT
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.

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Related in: MedlinePlus

Physical model for current propagation. A:Finite element mesh of the scalp and of the stimulation electrodes B: Finite element mesh of the interface between GM and WM. C: Spatial distribution of the magnitude of the electric field, in V/m, induced by the injection of a current through the anode. In this stimulation configuration, the anode and cathode virtual electrodes are centered over both occipital cortices, and the amplitude of the injected current is set to 1.12 mA.
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pone-0057330-g002: Physical model for current propagation. A:Finite element mesh of the scalp and of the stimulation electrodes B: Finite element mesh of the interface between GM and WM. C: Spatial distribution of the magnitude of the electric field, in V/m, induced by the injection of a current through the anode. In this stimulation configuration, the anode and cathode virtual electrodes are centered over both occipital cortices, and the amplitude of the injected current is set to 1.12 mA.

Mentions: First MR images were segmented. For this purpose we used T1 and Proton Density (PD) phantom images based on the Colin27 template (http://www.bic.mni.mcgill.ca/brainweb). Segmentation was performed using the BrainSuite software (http://www.loni.ucla.edu/Software/BrainSuite, [22]–[25]). White matter (WM), gray matter (GM) and cerebrospinal fluid (CSF) were segmented from the T1 images whereas the skull and scalp were obtained from the PD images. The resulting masks were used to generate surface meshes representing the boundaries between the different tissues. The mesh of WM-GM interface had 189494 triangles and 94743 vertices (average area of triangles 1.036 mm2, maximum 3.832 mm2, minimum 0.008 mm2) and is shown in figure 2B. Secondly, a volume mesh representing the whole head was generated from the surface meshes using MIMICS (http://www.materialise.com/). At this stage, virtual tDCS electrodes were also incorporated into the model. The anode and the cathode could be placed at any of the positions defined in the 10–10 International System. The resultant mesh comprised more than 1.9×106 tetrahedral second order Lagrange elements (Figure 2A). Thirdly, the volume mesh was imported into a finite element program to calculate the electric field (Comsol 3.5a, www.comsol.com). The upper surface of each electrode was set to uniform electrical potential and the potential difference between them was adjusted to reach the desired custom amplitude of injected current through the anode. All the remaining outer boundaries of the model were considered to be insulating, (), and continuity of the normal component of the current density was imposed on all the inner boundaries. The electric field induced in the brain was obtained by solving Laplace’s equation(where denotes the electrostatic scalar potential and the electrical conductivity) and taking the gradient of the scalar potential. This procedure assumes that the quasi-static approximation [26] is valid for the low stimulation frequencies used in tCS. In this approximation the tissues are considered to be purely resistive with no capacitive components. The different tissues in the head model were modeled as having electrical conductivities with values close to the average ones reported in the literature for the DC/low frequency range [27]–[29]: 0.33 S/m, 0.008 S/m, 1.79 S/m, 0.33 S/m and 0.15 S/m for the scalp, skull, CSF, GM and WM, respectively. The electrodes were modeled as having a conductivity value arbitrarily taken to be equal to that of the scalp. All media were modeled as having isotropic conductivities and, as such, the current density could be found simply by multiplying the scalar electrical conductivity by the electric field.


From oscillatory transcranial current stimulation to scalp EEG changes: a biophysical and physiological modeling study.

Merlet I, Birot G, Salvador R, Molaee-Ardekani B, Mekonnen A, Soria-Frish A, Ruffini G, Miranda PC, Wendling F - PLoS ONE (2013)

Physical model for current propagation. A:Finite element mesh of the scalp and of the stimulation electrodes B: Finite element mesh of the interface between GM and WM. C: Spatial distribution of the magnitude of the electric field, in V/m, induced by the injection of a current through the anode. In this stimulation configuration, the anode and cathode virtual electrodes are centered over both occipital cortices, and the amplitude of the injected current is set to 1.12 mA.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3585369&req=5

pone-0057330-g002: Physical model for current propagation. A:Finite element mesh of the scalp and of the stimulation electrodes B: Finite element mesh of the interface between GM and WM. C: Spatial distribution of the magnitude of the electric field, in V/m, induced by the injection of a current through the anode. In this stimulation configuration, the anode and cathode virtual electrodes are centered over both occipital cortices, and the amplitude of the injected current is set to 1.12 mA.
Mentions: First MR images were segmented. For this purpose we used T1 and Proton Density (PD) phantom images based on the Colin27 template (http://www.bic.mni.mcgill.ca/brainweb). Segmentation was performed using the BrainSuite software (http://www.loni.ucla.edu/Software/BrainSuite, [22]–[25]). White matter (WM), gray matter (GM) and cerebrospinal fluid (CSF) were segmented from the T1 images whereas the skull and scalp were obtained from the PD images. The resulting masks were used to generate surface meshes representing the boundaries between the different tissues. The mesh of WM-GM interface had 189494 triangles and 94743 vertices (average area of triangles 1.036 mm2, maximum 3.832 mm2, minimum 0.008 mm2) and is shown in figure 2B. Secondly, a volume mesh representing the whole head was generated from the surface meshes using MIMICS (http://www.materialise.com/). At this stage, virtual tDCS electrodes were also incorporated into the model. The anode and the cathode could be placed at any of the positions defined in the 10–10 International System. The resultant mesh comprised more than 1.9×106 tetrahedral second order Lagrange elements (Figure 2A). Thirdly, the volume mesh was imported into a finite element program to calculate the electric field (Comsol 3.5a, www.comsol.com). The upper surface of each electrode was set to uniform electrical potential and the potential difference between them was adjusted to reach the desired custom amplitude of injected current through the anode. All the remaining outer boundaries of the model were considered to be insulating, (), and continuity of the normal component of the current density was imposed on all the inner boundaries. The electric field induced in the brain was obtained by solving Laplace’s equation(where denotes the electrostatic scalar potential and the electrical conductivity) and taking the gradient of the scalar potential. This procedure assumes that the quasi-static approximation [26] is valid for the low stimulation frequencies used in tCS. In this approximation the tissues are considered to be purely resistive with no capacitive components. The different tissues in the head model were modeled as having electrical conductivities with values close to the average ones reported in the literature for the DC/low frequency range [27]–[29]: 0.33 S/m, 0.008 S/m, 1.79 S/m, 0.33 S/m and 0.15 S/m for the scalp, skull, CSF, GM and WM, respectively. The electrodes were modeled as having a conductivity value arbitrarily taken to be equal to that of the scalp. All media were modeled as having isotropic conductivities and, as such, the current density could be found simply by multiplying the scalar electrical conductivity by the electric field.

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: INSERM, Université de Rennes 1, LTSI, Rennes, France. isabelle.merlet@univ-rennes1.fr

ABSTRACT
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.

Show MeSH
Related in: MedlinePlus