Decoding Local Field Potentials for Neural Interfaces.
Decoding Local Field Potentials for Neural Interfaces.
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DOI：
10.1109/tnsre.2016.2612001
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发表时间：
2017-10
期刊：
影响因子：
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通讯作者：
Hall TM
中科院分区：
文献类型：
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作者：
Jackson A;Hall TM
局部场电位 (LFP) 的稳定性和频率含量为长期、低功耗神经接口提供了关键优势。然而，解释 LFP 可能需要新的信号处理技术，这些技术应该通过对这些记录如何从底层神经元群体的协调活动中产生的科学理解来提供信息。我们回顾了当前用于脑机接口（BMI）应用的 LFP 解码方法，并提出了未来研究的几个方向。为了促进更好地理解 LFP 和尖峰活动之间的关系，我们共享了猴子运动皮层的多电极记录数据集，并描述了我们探索的两种无监督分析方法，用于提取适合仿生解码和生物反馈训练的低维特征空间。
The stability and frequency content of local field potentials (LFPs) offer key advantages for long-term, low-power neural interfaces. However, interpreting LFPs may require new signal processing techniques which should be informed by a scientific understanding of how these recordings arise from the coordinated activity of underlying neuronal populations. We review current approaches to decoding LFPs for brain–machine interface (BMI) applications, and suggest several directions for future research. To facilitate an improved understanding of the relationship between LFPs and spike activity, we share a dataset of multielectrode recordings from monkey motor cortex, and describe two unsupervised analysis methods we have explored for extracting a low-dimensional feature space that is amenable to biomimetic decoding and biofeedback training.