Background

The past years have seen increased appreciation of electroencephalographic (EEG) recordings in non-human primates (NHP) as a tool for translational research. In humans, even large EEG electrode grids can easily and quickly be placed on standardized positions using commercially available EEG caps. In the NHP, the identification of standardized EEG electrode positions is more complicated and time-consuming.

New method

Here we introduce a surface metric and software package (NHP1020) that automates the planning of large, approximately evenly spaced electrode grids for EEG recordings in the NHP.

Results

Based on one CT and one MRI image as well as two intracranial markers, the NHP1020 software defines electrode positions on the brain surface using a surface-based spherical metric similar to the one used by the international 10-20 system. Standardized electrode grids can be shared, imported or defined with few high-level commands.

Existing methods

NHP EEG electrodes can be placed relative to extracranial markers and measurements or relative to underlying neural structures of interest. Both approaches are time-consuming and require manual intervention. Furthermore, the use of extracranial markers in this species may be more problematic than in humans, because cranial muscles and ridges are larger and keep maturing long into adulthood.

Conclusion

The presented surface metric and the NHP1020 toolbox provide fast and automated identification of entire electrode grids in the non-human primate based on a two-dimensional metric on the brain surface.

中文翻译：

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猕猴脑电图电极网格的表面度量和软件工具箱。

背景

过去几年，人们越来越多地将非人类灵长类动物 (NHP) 的脑电图 (EEG) 记录作为转化研究的工具。在人类中，即使是大型 EEG 电极网格也可以使用市售 EEG 帽轻松快速地放置在标准化位置。在 NHP 中，标准化 EEG 电极位置的识别更加复杂和耗时。

新方法

在这里，我们介绍了一个表面度量和软件包 (NHP1020)，它可以自动规划用于 NHP 中 EEG 记录的大型、近似均匀间隔的电极网格。

结果

基于一张 CT 和一张 MRI 图像以及两个颅内标记，NHP1020 软件使用类似于国际 10-20 系统使用的基于表面的球形度量来定义大脑表面上的电极位置。可以使用少量高级命令共享、导入或定义标准化电极网格。

现有方法

NHP EEG 电极可以相对于颅外标记和测量或相对于感兴趣的潜在神经结构放置。这两种方法都很耗时，需要人工干预。此外，在该物种中使用颅外标记可能比在人类中更成问题，因为颅内肌肉和脊椎更大，并且在成年后仍会保持成熟。

结论

提出的表面度量和 NHP1020 工具箱基于大脑表面的二维度量提供了对非人类灵长类动物中整个电极网格的快速和自动识别。