National Center for Adaptive Neurotechnologies, Wadsworth Center, New York State Department of Health, Albany, NY, USA.
National Center for Adaptive Neurotechnologies, Wadsworth Center, New York State Department of Health, Albany, NY, USA; Department of Neurology, Albany Medical College, Albany, NY, USA.
J Neurosci Methods. 2019 Jan 1;311:67-75. doi: 10.1016/j.jneumeth.2018.09.034. Epub 2018 Oct 4.
Electrical stimulation of the cortex using subdurally implanted electrodes can causally reveal structural connectivity by eliciting cortico-cortical evoked potentials (CCEPs). While many studies have demonstrated the potential value of CCEPs, the methods to evaluate them were often relatively subjective, did not consider potential artifacts, and did not lend themselves to systematic scientific investigations.
We developed an automated and quantitative method called SIGNI (Stimulation-Induced Gamma-based Network Identification) to evaluate cortical population-level responses to electrical stimulation that minimizes the impact of electrical artifacts. We applied SIGNI to electrocorticographic (ECoG) data from eight human subjects who were implanted with a total of 978 subdural electrodes. Across the eight subjects, we delivered 92 trains of approximately 200 discrete electrical stimuli each (amplitude 4-15 mA) to a total of 64 electrode pairs.
We verified SIGNI's efficacy by demonstrating a relationship between the magnitude of evoked cortical activity and stimulation amplitude, as well as between the latency of evoked cortical activity and the distance from the stimulated locations.
SIGNI reveals the timing and amplitude of cortical responses to electrical stimulation as well as the structural connectivity supporting these responses. With these properties, it enables exploration of new and important questions about the neurophysiology of cortical communication and may also be useful for pre-surgical planning.
通过诱发皮质-皮质诱发电位(CCEPs),使用硬脑膜下植入的电极对皮层进行电刺激,可以因果性地揭示结构连接。虽然许多研究已经证明了 CCEPs 的潜在价值,但评估它们的方法通常相对主观,没有考虑潜在的伪影,也不适合系统的科学研究。
我们开发了一种名为 SIGNI(基于刺激诱导伽马的网络识别)的自动化和定量方法,用于评估皮质群体对电刺激的反应,最大限度地减少电伪影的影响。我们将 SIGNI 应用于 8 名植入总共 978 个硬脑膜下电极的人类受试者的脑电图(ECoG)数据。在这 8 名受试者中,我们共传递了 92 个大约 200 个离散电刺激的序列(幅度为 4-15 mA),总共刺激了 64 对电极。
我们通过证明诱发皮质活动的幅度与刺激幅度之间的关系,以及诱发皮质活动的潜伏期与刺激位置之间的距离之间的关系,验证了 SIGNI 的功效。
SIGNI 揭示了皮质对电刺激的反应的时间和幅度,以及支持这些反应的结构连接。凭借这些特性,它可以探索关于皮质通讯神经生理学的新的和重要的问题,也可能对术前规划有用。