Mitigating Mismatch Compression in Differential Local Field Potentials.
Mitigating Mismatch Compression in Differential Local Field Potentials.
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DOI：
10.1109/tnsre.2022.3217469
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发表时间：
2023
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能够测量差分局部场电位（∂LFP）的深部脑刺激（DBS）设备使神经记录与临床治疗得以同时进行。识别各种脑部疾病的振荡相关性或疾病读数的工作正在增加，但必须谨慎进行，以确保读数不会因大脑环境而失真。在本报告中，我们确定、描述并减轻了∂LFP中一种主要的失真来源，我们将其称为失配压缩（MC）。通过使用MC的体内、计算机模拟和体外模型，我们表明两个记录电极中的阻抗失配会导致对刺激伪影的不完全抑制以及随后的增益压缩，从而使振荡功率失真。然后我们开发并验证了一个开源的减轻流程，该流程可减轻由MC引起的失真。这项工作为自适应DBS应用提供了更可靠的振荡读数。
Deep brain stimulation (DBS) devices capable of measuring differential local field potentials (∂LFP) enable neural recordings alongside clinical therapy. Efforts to identify oscillatory correlates of various brain disorders, or disease readouts, are growing but must proceed carefully to ensure readouts are not distorted by brain environment. In this report we identified, characterized, and mitigated a major source of distortion in ∂LFP that we introduce as mismatch compression (MC). Using in vivo, in silico, and in vitro models of MC, we showed that impedance mismatches in the two recording electrodes can yield incomplete rejection of stimulation artifact and subsequent gain compression that distorts oscillatory power. We then developed and validated an opensource mitigation pipeline that mitigates the distortions arising from MC. This work enables more reliable oscillatory readouts for adaptive DBS applications.