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使用光谱、空间和时间维度约减从灵长类前额叶皮层局部场电位解码眼跳意图。

Decoding Saccade Intention From Primate Prefrontal Cortical Local Field Potentials Using Spectral, Spatial, and Temporal Dimensionality Reduction.

机构信息

Ottawa Hospital Research Institute, 725 Parkdale Ave., Ottawa, ON, K1Y 4E9, Canada.

Department of Neurologic Surgery, Mayo Clinic, 200 First St., Rochester, MN 55902, United States.

出版信息

Int J Neural Syst. 2021 Jun;31(6):2150023. doi: 10.1142/S0129065721500234. Epub 2021 Apr 30.

Abstract

Most invasive Brain Computer Interfaces (iBCIs) use spike and Local Field Potentials (LFPs) from the motor or parietal cortices to decode movement intentions. It has been debated whether harvesting signals from other brain areas that encode global cognitive variables, such as the allocation of attention and eye movement goals in a variety of spatial reference frames, may improve the outcome of iBCIs. Here, we explore the ability of LFP signals, sampled from the lateral prefrontal cortex (LPFC) of macaque monkeys, to encode eye-movement intention during the pre-movement fixation period of a delayed saccade task. We use spectral dimensionality reduction to examine the spatiotemporal properties of the extracted non-rhythmic broadband activity and explore its usefulness in decoding saccade goals. The dynamics of the broadband signal in low spatial dimensions across the pre-movement fixation period uncovered saccade target separation; its discriminative potential was confirmed using support vector machine classifications. These findings reveal that broadband LFP from the LPFC can be used to decode intended saccade target location during pre-movement periods. We further provide a general workflow that can be implemented in iBCIs and it is relatively robust to the loss of spikes in individual electrodes.

摘要

大多数侵入式脑机接口(iBCI)使用来自运动或顶叶皮层的尖峰和局部场电位(LFPs)来解码运动意图。人们一直在争论,从其他编码全局认知变量的大脑区域获取信号,例如在各种空间参照系中注意力的分配和眼球运动目标,是否可以改善 iBCI 的结果。在这里,我们探索了从猕猴外侧前额叶皮层(LPFC)采样的 LFPs 信号在延迟扫视任务的运动前注视期期间编码眼球运动意图的能力。我们使用频谱降维来检查提取的非周期性宽带活动的时空特性,并探索其在解码扫视目标中的有用性。在运动前注视期内,低空间维度上的宽带信号的动力学揭示了扫视目标的分离;使用支持向量机分类法证实了其判别潜力。这些发现表明,LPFC 的宽带 LFPs 可用于在运动前期间解码预期的扫视目标位置。我们进一步提供了一种可以在 iBCI 中实施的通用工作流程,并且它相对稳健,不受单个电极中尖峰丢失的影响。

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