Wang Dong, Zhang Qiaosheng, Li Yue, Wang Yiwen, Zhu Junming, Zhang Shaomin, Zheng Xiaoxiang
Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou 310027, People's Republic of China. College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, People's Republic of China.
J Neural Eng. 2014 Jun;11(3):036009. doi: 10.1088/1741-2560/11/3/036009. Epub 2014 May 8.
Many serious concerns exist in the long-term stability of brain-machine interfaces (BMIs) based on spike signals (single unit activity, SUA; multi unit activity, MUA). Some studies showed local field potentials (LFPs) could offer a stable decoding performance. However, the decoding stability of LFPs was examined only when high quality spike signals were recorded. Here we aim to examine the long-term decoding stability of LFPs over a larger time scale when the quality of spike signals was from good to poor or even no spike was recorded.
Neural signals were collected from motor cortex of three monkeys via silicon arrays over 230, 290 and 690 days post-implantation when they performed 2D center out task. To compare long-term stability between LFPs and spike signals, we examined them in neural signals characteristics, directional tuning properties and offline decoding performance, respectively.
We observed slow decreasing trends in the number of LFP channels recorded and mean LFP power in different frequency bands when spike signals quality decayed over time. The number of significantly directional tuning LFP channels decreased more slowly than that of tuning SUA and MUA. The variable preferred directions for the same signal features across sessions indicated non-stationarity of neural activity. We also found that LFPs achieved better decoding performance than SUA and MUA in retrained decoder when the quality of spike signals seriously decayed. Especially, when no spike was recorded in one monkey after 671 days post-implantation, LFPs still provided some kinematic information. In addition, LFPs outperformed MUA in long-term decoding stability in a static decoder.
Our results suggested that LFPs were more durable and could provide better decoding performance when spike signals quality seriously decayed. It might be due to their resistance to recording degradation and their high redundancy among channels.
基于尖峰信号（单单元活动，SUA；多单元活动，MUA）的脑机接口（BMI）的长期稳定性存在许多严重问题。一些研究表明，局部场电位（LFP）可以提供稳定的解码性能。然而，仅在记录到高质量尖峰信号时才研究了LFP的解码稳定性。在这里，我们旨在研究在尖峰信号质量从好到差甚至没有记录到尖峰信号的更大时间尺度上LFP的长期解码稳定性。
在三只猴子执行二维中心向外任务时，通过硅阵列在植入后230、290和690天从其运动皮层收集神经信号。为了比较LFP和尖峰信号之间的长期稳定性，我们分别在神经信号特征、方向调谐特性和离线解码性能方面对它们进行了研究。
当尖峰信号质量随时间衰减时，我们观察到记录的LFP通道数量和不同频段的平均LFP功率呈缓慢下降趋势。具有显著方向调谐的LFP通道数量的下降比调谐SUA和MUA的通道数量下降得更慢。跨会话中相同信号特征的可变首选方向表明神经活动的非平稳性。我们还发现，当尖峰信号质量严重衰减时，在重新训练的解码器中，LFP比SUA和MUA具有更好的解码性能。特别是，在一只猴子植入后671天没有记录到尖峰信号时，LFP仍然提供了一些运动学信息。此外，在静态解码器中，LFP在长期解码稳定性方面优于MUA。
我们的结果表明，当尖峰信号质量严重衰减时，LFP更持久，并且可以提供更好的解码性能。这可能是由于它们对记录退化的抵抗力以及通道之间的高冗余性。
