Σφακιανάκης Αλέξανδρος
ΩτοΡινοΛαρυγγολόγος
Αναπαύσεως 5 Άγιος Νικόλαος
Κρήτη 72100
00302841026182
00306932607174
alsfakia@gmail.com

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Παρασκευή 21 Απριλίου 2017

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

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Publication date: Available online 20 April 2017
Source:Brain Stimulation
Author(s): A.K. Kasinadhuni, A. Indahlastari, M. Chauhan, Michael Schär, T.H. Mareci, R.J. Sadleir
BackgroundIt 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/HypothesisWe present the first in vivo images of electric current density distributions within the brain in four subjects undergoing transcranial electrical stimulation.MethodsMagnetic 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.ResultsWe 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.ConclusionsWe 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.



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