Design of Multichannel Transcranial Temporal Interfering Stimulation System Using an Individual MRI
Bahn, S.; Lee, C.; Kang, B.-Y.
Show abstract
Transcranial temporal interfering stimulation (tTIS) is an electrical stimulation method, in which two high-frequency alternating electric fields generate interference in the deep brain. This study aimed to design and verify the performance of a system that can precisely stimulate the deep brain using a multichannel tTIS based on an MRI image of an individuals brain. The optimization process, based on the parallel genetic algorithm with a GPU, was computationally verified using a modeled head that housed the deep brain. The hardware digitally stimulated the pre-interpreted head in a calculative manner, and the performance of the method was verified using an ideal head circuit. When four or more electrodes per frequency were used to stimulate the left thalamus, the rate of misstimulation was controlled to less than 2% on average for approximately 1 min. In the absence of deep-brain modeling, the average stimulus applied was reduced to 77.9%. The predicted signal had a 98.21% coefficient of determination for the modulations obtained by stimulating a head-type circuit using the proposed hardware. We designed a system that can stimulate the deep region of the brain through a multichannel tTIS, with due consideration for its practical application during the entire process. CCS CONCEPTS: * Theory and algorithms for application domains [->] Theory and algorithms for application domains; * Computing methodologies [->] Modeling and simulation; * Applied computing [->] Physical sciences and engineering
Matching journals
The top 2 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Non-invasive stimulation with Temporal Interference: Optimization of the electric field deep in the brain with the use of a genetic algorithm 99%
- Magnetic Temporal Interference for Noninvasive Focal Brain Stimulation 97%
- Input-Output Slope Curve Estimation in Neural Stimulation Based on Optimal Sampling Principles 97%
Similar papers in this journal
- Identifiability analysis and noninvasive online estimation of the first-order neural activation dynamics in the brain with closed-loop transcranial magnetic stimulation 96%
- Effective Ultrasonic Stimulation in Human Peripheral Nervous System 93%
- Bio-Physical Modeling of Galvanic Human Body Communication in Electro-Quasistatic Regime 92%
Similar papers in this journal
- Closed-loop control of functional electrical stimulation using a selectively recording and bidirectional nerve cuff interface 95%
- Neural stimulation hardware for the selective intrafascicular modulation of the vagus nerve 95%
- M2M-InvNet: Human Motor Cortex Mapping from Multi-Muscle Response Using TMS and Generative 3D Convolutional Network 94%
Similar papers in this journal
- Impact of galvanic vestibular stimulation electrode current density on brain current flow patterns: Does electrode size matter? 97%
- Rattractor - Instant guidance of a rat into a virtual cage using a deep brain stimulation 95%
- Filter bank common spatial pattern and envelope-based features in multimodal EEG-fTCD brain-computer interfaces 94%
Similar papers in this journal
- Key Factors in the Cortical Response to Transcranial Electrical Stimulations--A Multi-Scale Modeling Study 97%
- A Leadfield-Free Optimization Framework for Transcranially Applied Electric Currents 95%
- Neuronal Spike Shapes (NSS): A Straightforward Approach to Investigate Heterogeneity in Neuronal Excitability States. 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.