Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Institute for Interdisciplinary Brain and Behavioral Sciences, Crean College of Health and Behavioral Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA, USA.
Sci Data. 2020 Mar 4;7(1):78. doi: 10.1038/s41597-020-0415-9.
A challenge for data sharing in systems neuroscience is the multitude of different data formats used. Neurodata Without Borders: Neurophysiology 2.0 (NWB:N) has emerged as a standardized data format for the storage of cellular-level data together with meta-data, stimulus information, and behavior. A key next step to facilitate NWB:N adoption is to provide easy to use processing pipelines to import/export data from/to NWB:N. Here, we present a NWB-formatted dataset of 1863 single neurons recorded from the medial temporal lobes of 59 human subjects undergoing intracranial monitoring while they performed a recognition memory task. We provide code to analyze and export/import stimuli, behavior, and electrophysiological recordings to/from NWB in both MATLAB and Python. The data files are NWB:N compliant, which affords interoperability between programming languages and operating systems. This combined data and code release is a case study for how to utilize NWB:N for human single-neuron recordings and enables easy re-use of this hard-to-obtain data for both teaching and research on the mechanisms of human memory.
系统神经科学数据共享面临的一个挑战是使用了多种不同的数据格式。Neurodata Without Borders: Neurophysiology 2.0 (NWB:N) 已经成为一种用于存储细胞水平数据以及元数据、刺激信息和行为的标准化数据格式。为了促进 NWB:N 的采用，下一步的关键是提供易于使用的处理管道，以便从 NWB:N 导入/导出数据。在这里，我们提供了一个 1863 个单神经元的 NWB 格式数据集，这些神经元是从 59 名接受颅内监测的人类受试者的内侧颞叶中记录下来的，他们在执行识别记忆任务时进行了记录。我们提供了 MATLAB 和 Python 中用于分析和将刺激、行为和电生理记录导入/导出到 NWB 的代码。这些数据文件符合 NWB:N 标准，这使得编程语言和操作系统之间具有互操作性。这个包含数据和代码的发布是如何将 NWB:N 用于人类单神经元记录的一个案例研究，并为人类记忆机制的教学和研究提供了对这个难以获取的数据的轻松重复使用。
