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Single-Unit Stability Using Chronically Implanted Multielectrode Arrays

机译:使用长期植入的多电极阵列的单单元稳定性

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摘要

The use of chronic intracortical multielectrode arrays has become increasingly prevalent in neurophysiological experiments. However, it is not obvious whether neuronal signals obtained over multiple recording sessions come from the same or different neurons. Here, we develop a criterion to assess single-unit stability by measuring the similarity of 1) average spike waveforms and 2) interspike interval histograms (ISIHs). Neuronal activity was recorded from four Utah arrays implanted in primary motor and premotor cortices in three rhesus macaque monkeys during 10 recording sessions over a 15- to 17-day period. A unit was defined as stable through a given day if the stability criterion was satisfied on all recordings leading up to that day. We found that 57% of the original units were stable through 7 days, 43% were stable through 10 days, and 39% were stable through 15 days. Moreover, stable units were more likely to remain stable in subsequent recording sessions (i.e., 89% of the neurons that were stable through four sessions remained stable on the fifth). Using both waveform and ISIH data instead of just waveforms improved performance by reducing the number of false positives. We also demonstrate that this method can be used to track neurons across days, even during adaptation to a visuomotor rotation. Identifying a stable subset of neurons should allow the study of long-term learning effects across days and has practical implications for pooling of behavioral data across days and for increasing the effectiveness of brain–machine interfaces.
机译:慢性皮质内多电极阵列的使用在神经生理学实验中变得越来越普遍。但是,通过多个记录会话获得的神经元信号是否来自相同或不同的神经元,这一点并不明显。在这里,我们通过测量1)平均尖峰波形和2)尖峰间隔直方图(ISIHs)的相似性,制定了评估单机稳定性的标准。在15到17天的时间内进行10次记录,记录了从四个犹他州阵列植入三只恒河猴的主要运动和前运动皮质的神经元活动。如果直到当天的所有记录都满足稳定性标准,则将一个单元定义为在给定的一天内是稳定的。我们发现原始单位中有57%的稳定期是7天,43%的稳定期是10天,39%的稳定期是15天。此外,稳定的单位在随后的记录会话中更可能保持稳定(即,在四个会话中保持稳定的神经元的89%在第五个记录中保持稳定)。通过使用波形和ISIH数据而不是仅使用波形,可以减少误报的数量,从而提高性能。我们还证明了该方法可用于跨天跟踪神经元,即使在适应运动运动的过程中也是如此。确定稳定的神经元子集应该可以研究整天的长期学习效果,并且对整天的行为数据汇总以及提高脑机接口的有效性具有实际意义。

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