Treffer: Indirect neural activation by a time-varying magnetic field-impact of the presence of implants.

Objective. Implanted devices exposed to time-varying magnetic fields in clinical environments-such as magnetic resonance imaging (MRI) and transcranial magnetic stimulation (TMS)-may induce unintended interactions with surrounding neural tissue. These interactions can lead to inadvertent nerve stimulation; however, the underlying mechanisms governing magnetic field-implant-neuron coupling remain poorly understood and require further investigation. Approach. We developed a biophysical model integrated with analytical calculations to quantify the influence of implanted objects on magnetically induced electric fields. To assess the physiological impact of these distortions, we constructed a multi-compartment model of a myelinated axon and evaluated its response to a single magnetic pulse across varying intensities. Activation thresholds were determined, and the underlying ion channel dynamics were further analyzed to elucidate the mechanisms of neural excitation induced by the altered field. Main results. The presence of the implant significantly altered the spatial distribution of the magnetically induced electric field, leading to indirect activation of nearby axons. Key factors such as implant-axon distance, implant size, and geometry critically influenced the extent of field distortion and the threshold required for neural activation. Variations in magnetic field intensity affected both the timing and location of axonal activation. Notably, high-intensity stimulation resulted in accelerated initiation of action potentials due to implant-induced electric field distortions. These intensity-dependent effects also modulated ion channel dynamics, further shaping the neural response. Significance. This study establishes foundational principles governing the interaction between externally applied time-varying magnetic fields, implanted devices, and surrounding neural tissue. It highlights essential safety considerations for MRI and TMS procedures, particularly when implants are located within regions subject to stimulation. The analytical framework developed herein offers a versatile tool for predicting electromagnetic effects across diverse implant types and clinical scenarios, supporting both improved device design and informed regulatory guidance.
(Creative Commons Attribution license.)