Electric Field Estimation in Deep TMS

Electric field estimation in deep transcranial magnetic stimulation

Journal: Brain Stimulation 8:326-342 (2015)

Authors: V. Guadagnin, M. Parazzini, S. Fiocchi, I. Liorni, Y.Roth, A. Zangen, P. Ravazzani


Literature studies [Bersani et al., 2013] showed the ability to treat different neuropsychiatric disorders using the H1 coil. One of the coils belongs to the Hesed (H) coils, which have been developed specifically for the Deep Transcranial Magnetic Stimulation (Deep TMS™). Despite the fact that clinical trials have obtained positive results, the electric field distributions inside different cerebral structures induced by these coils are not yet completely clear.


This study aims to explore the electric field characteristics induced by the H1 coils in two realistic head models.


The authors used two human models of the Virtual Family [Christet al., 2010] based on high resolution MRI of healthy volunteers (a 26-year-old female and a 34-year-old male). The H1 coil was modeled as current paths according to its real complex winding patterns and placed 5.5 cm anteriorly on the left hemisphere motor cortex of the right-hand abductor pollicis brevis. Moreover, the figure-8 coil was placed alternatively on the right and the left dorsolateral prefrontal cortex to compare the effect of the stimulation with the H1 coil on both hemispheres. For all simulations, we used a current pulse with a frequency content of 5 kHz and a current intensity adjusted to obtain 120% of the hand motor threshold. Simulations were conducted using the magneto quasi-static low-frequency solver of the simulation platform SEMCAD X.


The H1 coil induced an electric field with higher amplitude and a more widespread distribution in both the dorsolateral and medial prefrontal cortex than the figure-8 coil. Moreover, the penetration depth of the H1 coil was much higher than the figure-8 coil, particularly in the amygdala and nucleus accumbens, even if the induced fields were below the neural threshold.


This work highlights the importance of knowing the field distribution in order to evaluate the experimental results and to optimize therapeutic treatment.

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