OBJECTIVE: Transcranial direct current stimulation (tDCS) is a neuromodulatory technique for neuropsychiatric diseases and neurological disorders. In the tDCS treatment, dc current is injected into the head through a pair of electrodes attached on the scalp over a target region. A current density imaging method is needed to quantitatively visualize the internal current density distribution during the tDCS treatment. METHODS: We developed a novel current density image reconstruction algorithm using 1) a subject specific segmented 3-D head model, 2) diffusion tensor data, and 3) magnetic flux density data induced by the tDCS current. We acquired T1 weighted and diffusion tensor images of the head using the MRI scanner before the treatment. During the treatment, we can measure the induced magnetic flux density data using a magnetic resonance electrical impedance tomography (MREIT) pulse sequence. In this paper, the magnetic flux density data were numerically generated. RESULTS: Numerical simulation results show that the proposed method successfully recovers the current density distribution including the effects of the anisotropic, as well as isotropic conductivity values of different tissues in the head. CONCLUSION: The proposed current density imaging method using DT-MRI and MREIT can reliably recover cross-sectional images of the current density distribution during the tDCS treatment. SIGNIFICANCE: Success of the tDCS treatment depends on a precise determination of the induced current density distribution within different anatomical structures of the brain. Quantitative visualization of the current density distribution in the brain will play an important role in understanding the effects of the electrical stimulation.
OBJECTIVE: Transcranial direct current stimulation (tDCS) is a neuromodulatory technique for neuropsychiatric diseases and neurological disorders. In the tDCS treatment, dc current is injected into the head through a pair of electrodes attached on the scalp over a target region. A current density imaging method is needed to quantitatively visualize the internal current density distribution during the tDCS treatment. METHODS: We developed a novel current density image reconstruction algorithm using 1) a subject specific segmented 3-D head model, 2) diffusion tensor data, and 3) magnetic flux density data induced by the tDCS current. We acquired T1 weighted and diffusion tensor images of the head using the MRI scanner before the treatment. During the treatment, we can measure the induced magnetic flux density data using a magnetic resonance electrical impedance tomography (MREIT) pulse sequence. In this paper, the magnetic flux density data were numerically generated. RESULTS: Numerical simulation results show that the proposed method successfully recovers the current density distribution including the effects of the anisotropic, as well as isotropic conductivity values of different tissues in the head. CONCLUSION: The proposed current density imaging method using DT-MRI and MREIT can reliably recover cross-sectional images of the current density distribution during the tDCS treatment. SIGNIFICANCE: Success of the tDCS treatment depends on a precise determination of the induced current density distribution within different anatomical structures of the brain. Quantitative visualization of the current density distribution in the brain will play an important role in understanding the effects of the electrical stimulation.
Authors: A Antal; I Alekseichuk; M Bikson; J Brockmöller; A R Brunoni; R Chen; L G Cohen; G Dowthwaite; J Ellrich; A Flöel; F Fregni; M S George; R Hamilton; J Haueisen; C S Herrmann; F C Hummel; J P Lefaucheur; D Liebetanz; C K Loo; C D McCaig; C Miniussi; P C Miranda; V Moliadze; M A Nitsche; R Nowak; F Padberg; A Pascual-Leone; W Poppendieck; A Priori; S Rossi; P M Rossini; J Rothwell; M A Rueger; G Ruffini; K Schellhorn; H R Siebner; Y Ugawa; A Wexler; U Ziemann; M Hallett; W Paulus Journal: Clin Neurophysiol Date: 2017-06-19 Impact factor: 3.708
Authors: A K Kasinadhuni; A Indahlastari; M Chauhan; Michael Schär; T H Mareci; R J Sadleir Journal: Brain Stimul Date: 2017-04-20 Impact factor: 8.955
Authors: Munish Chauhan; Aprinda Indahlastari; Aditya K Kasinadhuni; Michael Schar; Thomas H Mareci; Rosalind J Sadleir Journal: IEEE Trans Med Imaging Date: 2018-04 Impact factor: 10.048