Focality of the Induced E-Field Is a Contributing Factor in the Choice of TMS Parameters: Evidence from a 3D Computational Model of the Human Brain.

Transcranial magnetic stimulation (TMS) is a promising, non-invasive approach in the diagnosis and treatment of several neurological conditions. However, the specific results in the cortex of the magnitude and spatial distribution of the secondary electrical field (E-field) resulting from TMS at different stimulation sites/orientations and varied TMS parameters are not clearly understood. The objective of this study is to identify the impact of TMS stimulation site and coil orientation on the induced E-field, including spatial distribution and the volume of activation in the cortex across brain areas, and hence demonstrate the need for customized optimization, using a three-dimensional finite element model (FEM). A considerable difference was noted in E-field values and distribution at different brain areas. We observed that the volume of activated cortex varied from 3000 to 7000 mm3 between the selected nine clinically relevant coil locations. Coil orientation also changed the induced E-field by a maximum of 10%, and we noted the least optimal values at the standard coil orientation pointing to the nose. The volume of gray matter activated varied by 10% on average between stimulation sites in homologous brain areas in the two hemispheres of the brain. This FEM simulation model clearly demonstrates the importance of TMS parameters for optimal results in clinically relevant brain areas. The results show that TMS parameters cannot be interchangeably used between individuals, hemispheres, and brain areas. The focality of the TMS induced E-field along with its optimal magnitude should be considered as critical TMS parameters that should be individually optimized.

Effects of macroscopic heterogeneity on propagation in a computationally inexpensive 2D model of the heart.

We have developed a computationally inexpensive, two-dimensional, bidomain model of the heart to demonstrate the effect of tissue heterogeneity on propagation of cardiac impulses generated by the sino-atrial node (SAN). The geometry consists of a thin sheet of cardiac tissue with designated areas that represent the SAN and atria. The SAN auto-generates continuous impulses that result in waves of normal propagation throughout the tissue. On the introduction of heterogeneous patches with low tissue conductivities, the rhythm of the waveform becomes irregular. The study suggests that simplified and computationally inexpensive models can be insightful tools to better understand the mechanisms that cause atrial fibrillation (AF) and hence more effective treatment methods.