Removing deep brain stimulation artifacts from the electroencephalogram: Issues, recommendations and an open-source toolbox

被引:35
作者
Lio, Guillaume [1 ,2 ,3 ]
Thobois, Stephane [1 ,2 ,3 ,4 ]
Ballanger, Benedicte [1 ,2 ,5 ]
Lau, Brian [6 ]
Boulinguez, Philippe [1 ,2 ,5 ]
机构
[1] Univ Lyon, F-69622 Lyon, France
[2] Univ Lyon 1, Villeurbanne, France
[3] CNRS, Ctr Neurosci Cognit, Bron, France
[4] Hop Neurol & Neurochirurg P Wertheimer, Hosp Civils Lyon, Bron, France
[5] Ctr Rech Neurosci Lyon, INSERM, CNRS, U1028,UMR5292, Lyon, France
[6] UPMC Univ Paris 06, Sorbonne Univ, UMR S 1127, CNRS UMR 7225,Inst Cerveau & Moelle Epiniere, F-75013 Paris, France
关键词
Deep brain stimulation; EEG; MEG; Artifacts; Antialiasing; Oversampling; Low-pass filtering; Matched filters; Hampel; Template subtraction; ICA; SUBTHALAMIC NUCLEUS STIMULATION; INDEPENDENT COMPONENT ANALYSIS; MULTI-SUBJECT DECOMPOSITION; VISUAL-EVOKED POTENTIALS; SHORT-LATENCY ACTIVATION; HIGHER-ORDER STATISTICS; PARKINSONS-DISEASE; MOVEMENT-DISORDERS; RESPONSE-INHIBITION; NETWORK ACTIVITY;
D O I
10.1016/j.clinph.2018.07.023
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
A major question for deep brain stimulation (DBS) research is understanding how DBS of one target area modulates activity in different parts of the brain. EEG gives privileged access to brain dynamics, but its use with implanted patients is limited since DBS adds significant high-amplitude electrical artifacts that can completely obscure neural activity measured using EEG. Here, we systematically review and discuss the methods available for removing DBS artifacts. These include simple techniques such as oversampling, antialiasing analog filtering and digital low-pass filtering, which are necessary but typically not sufficient to fully remove DBS artifacts when each is used in isolation. We also cover more advanced methods, including techniques tracking outliers in the frequency-domain, which can be effective, but are rarely used. The reason for that is twofold: First, it requires advanced skills in signal processing since no user friendly tool for removing DBS artifacts is currently available. Second, it involves fine-tuning to avoid over-aggressive filtering. We highlight an open-source toolbox incorporating most artifact removal methods, allowing users to combine different strategies. (C) 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:2170 / 2185
页数:16
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