Lee Somin, Henry Julia, Tryba Andrew K, Esengul Yasar, Warnke Peter, Wu Shasha, van Drongelen Wim
Medical Scientist Training Program, The University of Chicago, Chicago, IL, 60637, USA.
Committee on Neurobiology, The University of Chicago, Chicago, IL, 60637, USA.
Sci Rep. 2022 Aug 11;12(1):13701. doi: 10.1038/s41598-022-18071-5.
Infraslow activity (ISA) is a biomarker that has recently become of interest in the characterization of seizure recordings. Recent data from a small number of studies have suggested that the epileptogenic zone may be identified by the presence of ISA. Investigation of low frequency activity in clinical seizure recordings, however, has been hampered by technical limitations. EEG systems necessarily include a high-pass filter early in the measurement chain to remove large artifactual drifts that can saturate recording elements such as the amplifier. This filter, unfortunately, attenuates legitimately seizure-related low frequencies, making ISA difficult to study in clinical EEG recordings. In this study, we present a deconvolution-based digital inverse filter that allows recovery of attenuated low frequency activity in intracranial recordings of temporal lobe epilepsy patients. First, we show that the unit impulse response (UIR) of an EEG system can be characterized by differentiation of the system's step response. As proof of method, we present several examples that show that the low frequency component of a high-pass filtered signal can be restored by deconvolution with the UIR. We then demonstrate that this method can be applied to biologically relevant signals including clinical EEG recordings obtained from seizure patients. Finally, we discuss how this method can be applied to study ISA to identify and assess the seizure onset zone.
超慢活动（ISA）是一种生物标志物，最近在癫痫发作记录的特征描述中受到关注。少数研究的最新数据表明，癫痫ogenic区可能通过ISA的存在来识别。然而，临床癫痫发作记录中低频活动的研究受到技术限制的阻碍。脑电图系统在测量链的早期必然包括一个高通滤波器，以去除可能使记录元件（如放大器）饱和的大的人为漂移。不幸的是，这个滤波器会衰减与癫痫发作相关的低频，使得在临床脑电图记录中难以研究ISA。在本研究中，我们提出了一种基于反卷积的数字逆滤波器，它可以恢复颞叶癫痫患者颅内记录中衰减的低频活动。首先，我们表明脑电图系统的单位脉冲响应（UIR）可以通过系统阶跃响应的微分来表征。作为方法的证明，我们给出了几个例子，表明高通滤波信号的低频成分可以通过与UIR进行反卷积来恢复。然后，我们证明这种方法可以应用于生物相关信号，包括从癫痫患者获得的临床脑电图记录。最后，我们讨论了如何应用这种方法来研究ISA以识别和评估癫痫发作起始区。
