Centre for Bio-Inspired Technology, Imperial College London, London, SW7 2AZ, UK.
Department of Electrical and Electronic Engineering, Imperial College London, London, SW7 2AZ, UK.
Sci Rep. 2021 Sep 24;11(1):19045. doi: 10.1038/s41598-021-98021-9.
Extracellular recordings are typically analysed by separating them into two distinct signals: local field potentials (LFPs) and spikes. Previous studies have shown that spikes, in the form of single-unit activity (SUA) or multiunit activity (MUA), can be inferred solely from LFPs with moderately good accuracy. SUA and MUA are typically extracted via threshold-based technique which may not be reliable when the recordings exhibit a low signal-to-noise ratio (SNR). Another type of spiking activity, referred to as entire spiking activity (ESA), can be extracted by a threshold-less, fast, and automated technique and has led to better performance in several tasks. However, its relationship with the LFPs has not been investigated. In this study, we aim to address this issue by inferring ESA from LFPs intracortically recorded from the motor cortex area of three monkeys performing different tasks. Results from long-term recording sessions and across subjects revealed that ESA can be inferred from LFPs with good accuracy. On average, the inference performance of ESA was consistently and significantly higher than those of SUA and MUA. In addition, local motor potential (LMP) was found to be the most predictive feature. The overall results indicate that LFPs contain substantial information about spiking activity, particularly ESA. This could be useful for understanding LFP-spike relationship and for the development of LFP-based BMIs.
局部场电位 (LFPs) 和尖峰。先前的研究表明，尖峰（以单单位活动 (SUA) 或多单位活动 (MUA) 的形式）可以从中等精度的 LFPs 中推断出来。SUA 和 MUA 通常通过基于阈值的技术提取，当记录显示出低信噪比 (SNR) 时，该技术可能不可靠。另一种称为整个尖峰活动 (ESA) 的尖峰活动可以通过无阈值、快速和自动化的技术提取，并在多项任务中取得了更好的性能。然而，它与 LFPs 的关系尚未得到研究。在这项研究中，我们旨在通过从执行不同任务的三只猴子的运动皮层区域记录的皮层内 LFPs 中推断 ESA 来解决这个问题。来自长期记录会话和跨受试者的结果表明，ESA 可以从中等精度的 LFPs 中推断出来。平均而言，ESA 的推断性能始终且显著高于 SUA 和 MUA。此外，发现局部运动电位 (LMP) 是最具预测性的特征。总体结果表明，LFPs 包含有关尖峰活动的大量信息，特别是 ESA。这对于理解 LFP-尖峰关系以及开发基于 LFP 的 BMI 可能很有用。
