Institut de Neurosciences de la Timone (INT), UMR 7289, CNRS-Aix Marseille Université, 13005 Marseille, France.
Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA Institute Brain Structure-Function Relationships (INM-10), 52425 Jülich, Germany.
Sci Data. 2018 Apr 10;5:180055. doi: 10.1038/sdata.2018.55.
We publish two electrophysiological datasets recorded in motor cortex of two macaque monkeys during an instructed delayed reach-to-grasp task, using chronically implanted 10-by-10 Utah electrode arrays. We provide a) raw neural signals (sampled at 30 kHz), b) time stamps and spike waveforms of offline sorted single and multi units (93/49 and 156/19 SUA/MUA for the two monkeys, respectively), c) trial events and the monkey's behavior, and d) extensive metadata hierarchically structured via the odML metadata framework (including quality assessment post-processing steps, such as trial rejections). The dataset of one monkey contains a simultaneously saved record of the local field potential (LFP) sampled at 1 kHz. To load the datasets in Python, we provide code based on the Neo data framework that produces a data structure which is annotated with relevant metadata. We complement this loading routine with an example code demonstrating how to access the data objects (e.g., raw signals) contained in such structures. For Matlab users, we provide the annotated data structures as mat files.
我们发布了两段在两只猕猴运动皮层中记录的电生理数据集，这些数据是在一项指令性延迟伸手抓握任务中使用慢性植入的 10x10 犹他电极阵列获得的。我们提供了 a) 原始神经信号（以 30 kHz 的采样率），b) 离线排序的单元和多单元的时间戳和尖峰波形（两只猴子的单单元和多单元分别为 93/49 和 156/19），c) 试验事件和猴子的行为，以及 d) 通过 odML 元数据框架分层结构的广泛元数据（包括试验拒绝等质量评估后处理步骤）。一只猴子的数据集包含同时以 1 kHz 采样率记录的局部场电位 (LFP)。为了在 Python 中加载数据集，我们提供了基于 Neo 数据框架的代码，该代码生成了一个带有相关元数据的注释数据结构。我们用一个示例代码补充了这个加载例程，演示了如何访问这种结构中包含的数据对象（例如原始信号）。对于 Matlab 用户，我们提供了注释的数据结构作为 mat 文件。
