Diomedi S, Vaccari F E, Gamberini M, De Vitis M, Filippini M, Fattori P
Dept. of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy.
Alma Mater Research Institute for Human-Centered Artificial Intelligence, University of Bologna, Bologna, Italy.
Sci Data. 2024 Jun 13;11(1):624. doi: 10.1038/s41597-024-03479-7.
Facilitating data sharing in scientific research, especially in the domain of animal studies, holds immense value, particularly in mitigating distress and enhancing the efficiency of data collection. This study unveils a meticulously curated collection of neural activity data extracted from six electrophysiological datasets recorded from three parietal areas (V6A, PEc, PE) of two Macaca fascicularis during an instructed-delay foveated reaching task. This valuable resource is now accessible to the public, featuring spike timestamps, behavioural event timings and supplementary metadata, all presented alongside a comprehensive description of the encompassing structure. To enhance accessibility, data are stored as HDF5 files, a convenient format due to its flexible structure and the capability to attach diverse information to each hierarchical sub-level. To guarantee ready-to-use datasets, we also provide some MATLAB and Python code examples, enabling users to quickly familiarize themselves with the data structure.
促进科学研究中的数据共享,尤其是在动物研究领域,具有巨大价值,特别是在减轻痛苦和提高数据收集效率方面。本研究揭示了一个精心策划的神经活动数据集,该数据集是从两只猕猴的三个顶叶区域(V6A、PEc、PE)记录的六个电生理数据集中提取的,记录过程为指令延迟中心注视伸手任务。这个宝贵的资源现已向公众开放,具有尖峰时间戳、行为事件时间以及补充元数据,所有这些都与对整体结构的全面描述一起呈现。为了提高可访问性,数据以HDF5文件形式存储,这种格式很方便,因为其结构灵活且能够将各种信息附加到每个层次子级别。为了确保数据集随时可用,我们还提供了一些MATLAB和Python代码示例,使用户能够快速熟悉数据结构。