Predicting movement from multiunit activity
Predicting movement from multiunit activity
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DOI：
10.1523/jneurosci.1321-07.2007
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发表时间：
2007-08-01
影响因子：
5.3
通讯作者：
Abeles, Moshe
中科院分区：
文献类型：
--
作者：
Stark, Eran;Abeles, Moshe
先前的研究已经表明，皮质内活动可以用来操作假肢装置，如假肢。以前使用的神经元信号要么是几十到几百个尖峰神经元的活动，这是很难长时间记录，或局部场电位，这是高度相关的彼此。在这里，我们表明，通过估计多单位活动（MUA），微电极周围的许多神经元的叠加活动，并使用少量的电极，获得了准确的预测即将到来的运动。与单单位尖峰相比，单MUA记录更容易获得，并且记录随时间推移更稳定。与局部场电位相比，对MUA记录是相当少的冗余。与任何其他皮质内信号相比，单个MUA记录的信息量更大。即使在没有尖峰的情况下，MUA也能提供信息。通过结合信息从多电极记录从运动皮层的猴子，执行离散或连续跟踪运动，我们表明，预测的基础上多通道MUA是上级那些基于尖峰或局部场电位。这些结果表明，相当多的信息被保留在多个神经元的叠加活动，因此表明，在同一个地方的神经元处理类似的信息。他们还说明，复杂的运动可以预测使用相对简单的信号处理，而无需检测尖峰，因此，持有的潜力，大大加快运动皮层假体设备的发展。
Previous studies have shown that intracortical activity can be used to operate prosthetic devices such as an artificial limb. Previously used neuronal signals were either the activity of tens to hundreds of spiking neurons, which are difficult to record for long periods of time, or local field potentials, which are highly correlated with each other. Here, we show that by estimating multiunit activity (MUA), the superimposed activity of many neurons around a microelectrode, and using a small number of electrodes, an accurate prediction of the upcoming movement is obtained. Compared with single-unit spikes, single MUA recordings are obtained more easily and the recordings are more stable over time. Compared with local field potentials, pairs of MUA recordings are considerably less redundant. Compared with any other intracortical signal, single MUA recordings are more informative. MUA is informative even in the absence of spikes. By combining information from multielectrode recordings from the motor cortices of monkeys that performed either discrete prehension or continuous tracing movements, we demonstrate that predictions based on multichannel MUA are superior to those based on either spikes or local field potentials. These results demonstrate that considerable information is retained in the superimposed activity of multiple neurons, and therefore suggest that neurons within the same locality process similar information. They also illustrate that complex movements can be predicted using relatively simple signal processing without the detection of spikes and, thus, hold the potential to greatly expedite the development of motor-cortical prosthetic devices.