Bioelectrics
Zohre Mojiri; Amir Akhavan; Ehsan Rouhani
Volume 16, Issue 3 , December 2022, , Pages 257-269
Abstract
Deep brain stimulation (DBS) is a technique to stimulate the deep areas of the brain which can be used in both invasive and non-invasive methods. In invasive DBS, the electrodes are surgically implanted inside the brain to achieve the desired depth of the stimulation. The invasive DBS approach suffers ...
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Deep brain stimulation (DBS) is a technique to stimulate the deep areas of the brain which can be used in both invasive and non-invasive methods. In invasive DBS, the electrodes are surgically implanted inside the brain to achieve the desired depth of the stimulation. The invasive DBS approach suffers from intracranial bleeding. One solution is using non-invasive DBS by temporal interference (TI) method. In TI stimulation, the constructive interference of two electric fields generated by two high-frequency sinusoidal currents increases the stimulation intensity at a certain depth. The objective of this paper is to investigate quantitatively as well as qualitative analysis of TI stimulation effect on the activation of primary motor cortex area of the rat. To this end, a 4-channel stimulator is used. The experiment is conducted on one anesthetized rat. The transcranial stimulation is applied by the electrode fixed on the skull with screw and the results are evaluated qualitatively and the quantitatively in the domains of time, frequency, and space. To quantify the results, a three-axis accelerometer sensor is used to record the movement acceleration of the right hand. The results showed that, the variation of the stimulation parameters (stimulation current intensity, frequency difference and ratio of currents of the two electrodes) changed the stimulation area inside the two hemispheres of the brain and movement range of the right hand. Moreover, the relationship between the difference frequency of the stimulation of the two pairs of electrodes and the range of motion was analyzed using a three-order polynomial regression model.
