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Brain Stimul. 2017 Jul - Aug;10(4):764-772. doi: 10.1016/j.brs.2017.04.125. Epub 2017 Apr 20.

Imaging of current flow in the human head during transcranial electrical therapy.

Author information

1
J. Crayton Pruitt Department of Biomedical Engineering, University of Florida, Gainesville FL, USA.
2
School of Biological and Health Systems Engineering, Arizona State University, Tempe AZ, USA.
3
Department of Radiology, Johns Hopkins University, Baltimore MD, USA.
4
Department of Biochemistry and Molecular Biology, University of Florida, Gainesville FL, USA.
5
Department of Radiology, Johns Hopkins University, Baltimore MD, USA; School of Biological and Health Systems Engineering, Arizona State University, Tempe AZ, USA. Electronic address: rsadleir@asu.edu.

Abstract

BACKGROUND:

It has been assumed that effects caused by tDCS or tACS neuromodulation are due to electric current flow within brain structures. However, to date, direct current density distributions in the brains of human subjects have not been measured. Instead computational models of tDCS or tACS have been used to predict electric current and field distributions for dosimetry and mechanism analysis purposes.

OBJECTIVE/HYPOTHESIS:

We present the first in vivo images of electric current density distributions within the brain in four subjects undergoing transcranial electrical stimulation.

METHODS:

Magnetic resonance electrical impedance tomography (MREIT) techniques encode current flow in phase images. In four human subjects, we used MREIT to measure magnetic flux density distributions caused by tACS currents, and then calculated current density distributions from these data. Computational models of magnetic flux and current distribution, constructed using contemporaneously collected T1-weighted structural MRI images, were co-registered to compare predicted and experimental results.

RESULTS:

We found consistency between experimental and simulated magnetic flux and current density distributions using transtemporal (T7-T8) and anterior-posterior (Fpz-Oz) electrode montages, and also differences that may indicate a need to improve models to better interpret experimental results. While human subject data agreed with computational model predictions in overall scale, differences may result from factors such as effective electrode surface area and conductivities assumed in models.

CONCLUSIONS:

We believe this method may be useful in improving reproducibility, assessing safety, and ultimately aiding understanding of mechanisms of action in electrical and magnetic neuromodulation modalities.

KEYWORDS:

Current density; Finite element modeling; MREIT; MRI; tACS; tDCS

PMID:
28457836
PMCID:
PMC5513732
DOI:
10.1016/j.brs.2017.04.125
[Indexed for MEDLINE]
Free PMC Article

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