论文标题
减轻差异局部场电位中的不匹配压缩
Mitigating Mismatch Compression in Differential Local Field Potentials
论文作者
论文摘要
双向深脑刺激（BDDBS）设备能够记录局部局部田间电位（DLFP），可与临床治疗同时进行神经记录。在DLFP中，识别各种脑疾病或疾病读数的客观信号的努力在DLFP中具有挑战性，尤其是在主动DBS期间。在本报告中，我们确定了，表征和减轻DLFP中的主要失真来源，我们将其引入不匹配压缩（MC）。 MC发生在跨DLFP通道上的阻抗不匹配的继发性，导致伪像和下游放大器增益压缩不完全排斥。在硅和体外模型中，我们证明了MC解释了与DBS振幅敏感的阻抗相关的畸变。然后，我们使用这些模型来制定和验证MC的缓解策略，该策略作为开放库库提供，以提供更可靠的振荡疾病读数。
Bidirectional deep brain stimulation (bdDBS) devices capable of recording differential local field potentials (dLFP) enable neural recordings alongside clinical therapy. Efforts to identify objective signals of various brain disorders, or disease readouts, are challenging in dLFP, especially during active DBS. In this report we identified, characterized, and mitigated a major source of distortion in dLFP that we introduce as mismatch compression (MC). MC occurs secondary to impedance mismatches across the dLFP channel resulting in incomplete rejection of artifacts and downstream amplifier gain compression. Using in silico and in vitro models we demonstrate that MC accounts for impedance-related distortions sensitive to DBS amplitude. We then use these models to develop and validate a mitigation strategy for MC that is provided as an opensource library for more reliable oscillatory disease readouts.
