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Impact of brain tissue filtering on neurostimulation fields: a modeling study

机译:脑组织过滤对神经刺激场的影响:模型研究

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摘要

Electrical neurostimulation techniques, such as deep brain stimulation (DBS) and transcranial magnetic stimulation (TMS), are increasingly used in the neurosciences, e.g., for studying brain function, and for neurotherapeutics, e.g., for treating depression, epilepsy, and Parkinson’s disease. The characterization of electrical properties of brain tissue has guided our fundamental understanding and application of these methods, from electrophysiologic theory to clinical dosing-metrics. Nonetheless, prior computational models have primarily relied on ex-vivo impedance measurements. We recorded the in-vivo impedances of brain tissues during neurosurgical procedures and used these results to construct MRI guided computational models of TMS and DBS neurostimulatory fields and conductance-based models of neurons exposed to stimulation. We demonstrated that tissues carry neurostimulation currents through frequency dependent resistive and capacitive properties not typically accounted for by past neurostimulation modeling work. We show that these fundamental brain tissue properties can have significant effects on the neurostimulatory-fields (capacitive and resistive current composition and spatial/temporal dynamics) and neural responses (stimulation threshold, ionic currents, and membrane dynamics). These findings highlight the importance of tissue impedance properties on neurostimulation and impact our understanding of the biological mechanisms and technological potential of neurostimulatory methods.
机译:电神经刺激技术,例如深部脑刺激(DBS)和经颅磁刺激(TMS),越来越多地用于神经科学,例如,用于研究脑功能,以及用于神经疗法,例如,用于治疗抑郁症,癫痫病和帕金森氏病。脑组织电学特性的表征指导了我们对这些方法的基本理解和应用,从电生理理论到临床剂量计量。尽管如此,先前的计算模型主要依赖于体外阻抗测量。我们记录了神经外科手术过程中脑组织的体内阻抗,并使用这些结果构建了TMS和DBS神经刺激场的MRI指导计算模型以及暴露于刺激下的基于电导的神经元模型。我们证明了组织通过频率依赖性的电阻和电容特性来承载神经刺激电流,而过去的神经刺激建模工作通常无法解释这些特性。我们表明,这些基本的脑组织特性可以对神经刺激场(电容和电阻电流组成以及时空动态)和神经反应(刺激阈值,离子电流和膜动力学)产生重大影响。这些发现突出了组织阻抗特性对神经刺激的重要性,并影响了我们对神经刺激方法的生物学机制和技术潜力的理解。

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