Biology subjects

Tashli, M.

Publications and source records attributed to Tashli, M..

2 recordsLinked to original sources

bioRxiv2022

Investigation of Soft Magnetic Material Cores in Transcranial Magnetic Stimulation Coils and the Effect of Changing Core Shapes on the Induced Electric Field in Small Animals

Transcranial magnetic stimulation (TMS) is a safe, effective and non-invasive treatment for several psychiatric and neurological disorders. Lately, there has been a surge in research utilizing this novel technology in treating other neurological and psychiatric ailments. The application of TMS on several neurological disorders requires the induced electric and magnetic fields to be focused and targeted to a small region in the brain. TMS of a focal cortical territory will ensure modulation of specific brain circuitry without affecting unwanted surrounding regions. This can be achieved by altering the properties of the magnetic core material used for the TMS system. In this study, soft ferromagnetic materials having high permeability, high saturation magnetization and low coercivity have been investigated as TMS coil cores in finite element simulations. Also, magnetic field measurements have been carried out using different cores in the TMS coil. Finite element analysis of the rat head model is carried out using Sim4life software while investigating variations associated with changing the ferromagnetic core material and shape in the coil. Materials proposed for the analysis in this study include Iron Cobalt Vanadium alloy (Fe-Co-V) also known as Permendur, Carbon Steel (AISI 1010) and Manganese Zinc ferrites (MnZn ferrites). Simulation results indicated significant magnetic field distribution variation when introducing a ferromagnetic core in TMS coil, concentrating the magnetic field to the targeted region in the rat head model without stimulating adjacent regions. It was observed that the v-tip sharpened core attained the highest magnetic field and best focality among other cores in simulations and experimentally.

bioengineering↗

bioRxiv2022

Prediction of Electric Fields Induced by Transcranial Magnetic Stimulation in the Brain using a Deep Encoder-Decoder Convolutional Neural Network

Transcranial magnetic stimulation (TMS) is a non-invasive, effective, and safe neuromodulation technique to diagnose and treat neurological and psychiatric disorders. However, the complexity and heterogeneity of the brain composition and structure pose a challenge in accurately determining whether critical brain regions have received the right level of induced electric field. Numerical computation methods, like finite element analysis (FEA), can be used to estimate electric field distribution. However, these methods need exceedingly high computational resources and are time-consuming. In this work, we developed a deep convolutional neural network (DCNN) encoder-decoder model to predict induced electric fields, in real-time, from T1-weighted and T2-weighted magnetic resonance imaging (MRI) based anatomical slices. We recruited 11 healthy subjects and applied TMS to the primary motor cortex to measure resting motor thresholds. Head models were developed from MRIs of the subjects using the SimNIBS pipeline. Head model overall size was scaled to 20 new size scales for each subject to form a total of 231 head models. Scaling was done to increase the number of input data representing different head model sizes. Sim4Life, a FEA software, was used to compute the induced electric fields, which served as the DCNN training data. For the trained network, the peak signal to noise ratios of the training and testing data were 32.83dB and 28.01dB, respectively. The key contribution of our model is the ability to predict the induced electric fields in real-time and thereby accurately and efficiently predict the TMS strength needed in targeted brain regions.

bioengineering↗