Soh Cheol, Hervault Mario, Rohl Andrea H, Greenlee Jeremy D W, Wessel Jan R
Department of Psychological and Brain Sciences, University of Iowa, United States; Cognitive Control Collaborative, University of Iowa, United States.
Department of Psychological and Brain Sciences, University of Iowa, United States; Cognitive Control Collaborative, University of Iowa, United States.
J Neurosci Methods. 2025 Jun;418:110448. doi: 10.1016/j.jneumeth.2025.110448. Epub 2025 Apr 11.
Investigations of the electrophysiological mechanisms of the human subcortex have relied on recording local field potentials (LFPs) during deep-brain stimulation (DBS) neurosurgery. However, the neurosurgical setting severely restricts the research use of these recordings. Recently developed sensing-capable DBS devices wirelessly stream subcortical LFPs in outpatient settings. These recordings have tremendous potential for research. However, synchronizing them with other behavior or neural recordings is challenging, as the clinical devices do not accept digital timing information.
Switching the DBS device on introduces transient yet consistent artifacts in both the LFP and simultaneous scalp-EEG recordings. We use these artifacts as a reference to align these recordings (N = 20). We tested whether the alignment was precise enough to match a ground truth state (large artifacts produced by transcranial magnetic stimulation, TMS), yielded trial-averaged event-locked LFPs, and phase consistency across trials. We further evaluated the consistency of task-related LFPs across outpatient and perisurgical recordings.
RESULTS AND COMPARISON WITH EXISTING METHOD(S): Previous alignment methods were limited because they relied on inconsistent on/offset features of DBS artifacts caused by ongoing stimulation. Moreover, they only provided limited validation. Our highly precise alignment method showed a maximum deviation of only 8 ms - clearly superior to prior techniques. Furthermore, event-related activity patterns were comparable across outpatient and perisurgical LFP recordings.
We present a method and a MATLAB toolbox that inserts the most precise digital timing information into wirelessly-streamed DBS-LFP recordings to date. By enabling event-related research with high-temporal precision, this method greatly enhances the utility of these recordings.
对人类大脑皮层下电生理机制的研究一直依赖于在深部脑刺激(DBS)神经外科手术期间记录局部场电位(LFP)。然而,神经外科手术环境严重限制了这些记录的研究用途。最近开发的具有传感功能的DBS设备可在门诊环境中无线传输皮层下LFP。这些记录具有巨大的研究潜力。然而,将它们与其他行为或神经记录同步具有挑战性,因为临床设备不接受数字定时信息。
开启DBS设备会在LFP和同步头皮脑电图记录中引入短暂但一致的伪迹。我们使用这些伪迹作为参考来对齐这些记录(N = 20)。我们测试了这种对齐是否精确到足以匹配真实状态(经颅磁刺激,TMS产生的大伪迹),是否产生试验平均事件锁定LFP以及跨试验的相位一致性。我们进一步评估了门诊和围手术期记录中与任务相关的LFP的一致性。
以前的对齐方法存在局限性,因为它们依赖于持续刺激引起的DBS伪迹不一致的开启/关闭特征。此外,它们只提供了有限的验证。我们高度精确的对齐方法显示最大偏差仅为8毫秒 - 明显优于先前技术。此外,门诊和围手术期LFP记录中的事件相关活动模式具有可比性。
我们提出了一种方法和一个MATLAB工具箱,可将迄今为止最精确的数字定时信息插入到无线传输的DBS-LFP记录中。通过实现具有高时间精度的事件相关研究,该方法大大提高了这些记录的实用性。