AIMC Topic: Transcranial Magnetic Stimulation

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Effects of robotic therapy associated with noninvasive brain stimulation on motor function in individuals with incomplete spinal cord injury: A systematic review of randomized controlled trials.

The journal of spinal cord medicine
CONTEXT: Motor deficits are among the most common consequences of incomplete spinal cord injury (SCI). These impairments can affect patients' levels of functioning and quality of life. Combined robotic therapy and non-invasive brain stimulation (NIBS...

verified anatomically aware deep learning for real-time electric field simulation.

Journal of neural engineering
Transcranial magnetic stimulation (TMS) has emerged as a prominent non-invasive technique for modulating brain function and treating mental disorders. By generating a high-precision magnetically evoked electric field (E-field) using a TMS coil, it en...

Robotic transcranial magnetic stimulation in the treatment of depression: a pilot study.

Scientific reports
There has been an increasing demand for robotic coil positioning during repetitive transcranial magnetic stimulation (rTMS) treatment. Accurate coil positioning is crucial because rTMS generally targets specific brain regions for both research and cl...

DELMEP: a deep learning algorithm for automated annotation of motor evoked potential latencies.

Scientific reports
The analysis of motor evoked potentials (MEPs) generated by transcranial magnetic stimulation (TMS) is crucial in research and clinical medical practice. MEPs are characterized by their latency and the treatment of a single patient may require the ch...

Attention-assisted hybrid 1D CNN-BiLSTM model for predicting electric field induced by transcranial magnetic stimulation coil.

Scientific reports
Deep learning-based models such as deep neural network (DNN) and convolutional neural network (CNN) have recently been established as state-of-the-art for enumerating electric fields from transcranial magnetic stimulation coil. One of the main challe...

Reliability of active robotic neuro-navigated transcranial magnetic stimulation motor maps.

Experimental brain research
Transcranial magnetic stimulation (TMS) motor mapping is a safe, non-invasive method used to study corticomotor organization and intervention-induced plasticity. Reliability of resting maps is well established, but understudied for active maps and un...

Computation of transcranial magnetic stimulation electric fields using self-supervised deep learning.

NeuroImage
Electric fields (E-fields) induced by transcranial magnetic stimulation (TMS) can be modeled using partial differential equations (PDEs). Using state-of-the-art finite-element methods (FEM), it often takes tens of seconds to solve the PDEs for comput...

Sex differences in rTMS treatment response: A deep learning-based EEG investigation.

Brain and behavior
INTRODUCTION: The present study aimed to investigate sex differences in response to repetitive transcranial magnetic stimulation (rTMS) in Major Depressive Disorder (MDD) patients. Identifying the factors that mediate treatment response to rTMS in MD...

Impaired phase synchronization of motor-evoked potentials reflects the degree of motor dysfunction in the lesioned human brain.

Human brain mapping
The functional corticospinal integrity (CSI) can be indexed by motor-evoked potentials (MEP) following transcranial magnetic stimulation of the motor cortex. Glial brain tumors in motor-eloquent areas are frequently disturbing CSI resulting in differ...

Causal decoding of individual cortical excitability states.

NeuroImage
Brain responsiveness to stimulation fluctuates with rapidly shifting cortical excitability state, as reflected by oscillations in the electroencephalogram (EEG). For example, the amplitude of motor-evoked potentials (MEPs) elicited by transcranial ma...