Inferring entire spiking activity from local field potentials.
Inferring entire spiking activity from local field potentials.
复制标题
从局部场电位推断整个尖峰活动。
DOI：
10.1038/s41598-021-98021-9
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发表时间：
2021-09-24
影响因子：
4.6
通讯作者：
Bouganis CS
中科院分区：
文献类型：
--
作者：
Ahmadi N;Constandinou TG;Bouganis CS
细胞外记录通常通过将它们分成两个不同的信号来分析：局部场电位（LFP）和尖峰。以前的研究表明，尖峰，在单单位活动（SUA）或多单位活动（MUA）的形式，可以推断出仅从LFP与中等良好的准确性。SUA和MUA通常通过基于阈值的技术提取，当记录表现出低信噪比（SNR）时，该技术可能不可靠。另一种类型的尖峰活动，称为整个尖峰活动（ESA），可以通过无阈值，快速和自动化的技术提取，并导致在几个任务中更好的性能。然而，其与LFP的关系尚未被调查。在这项研究中，我们的目标是解决这个问题，推断ESA从LFPs内记录从运动皮层区的三只猴子执行不同的任务。长期记录会话和跨受试者的结果表明，ESA可以从LFP中以良好的准确性推断出来。平均而言，ESA的推理性能始终显著高于SUA和MUA。此外，局部运动电位（LMP）被认为是最具预测性的特征。总体结果表明，LFP包含大量关于尖峰活动的信息，特别是ESA。这对于理解LFP-锋电位关系和基于LFP的BMI的发展可能是有用的。
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.
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DOI：
10.1109/tnsre.2016.2612001
发表时间：
2017-10
期刊：
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
影响因子：
--
作者：
Jackson A;Hall TM
通讯作者：
Hall TM
影响因子：
16.2
作者：
Kajikawa Y;Schroeder CE
通讯作者：
Schroeder CE
影响因子：
1.2
作者：
Belitski, Andrei;Panzeri, Stefano;Magri, Cesare;Logothetis, Nikos K.;Kayser, Christoph
通讯作者：
Kayser, Christoph
细胞外田地和电流的起源-EEG，ECOG，LFP和尖峰。
DOI：
10.1038/nrn3241
发表时间：
2012-05-18
期刊：
Nature reviews. Neuroscience
影响因子：
--
作者：
Buzsáki G;Anastassiou CA;Koch C
通讯作者：
Koch C
影响因子：
3.7
作者：
Brosch, M;Bauer, R;Eckhorn, R
通讯作者：
Eckhorn, R