Recording of 19,000 neurons across mouse visual cortex during sparse noise stimuli

This repository contains the activity of 18,975 neurons across visual cortex during the presentation of sparse noise visual stimuli.<br>The deconvolved data is in the "spks.npy". "F.npy", "Fneu.npy", "stat.npy" and "ops.npy" are documented on the suite2p page: https://github.com/MouseLand/suite2p/wiki/Outputs<br>The frames of the sparse noise stimuli are in "mov.npy". The frame times are in "iframe.npy".<br>The behavioral data (already aligned to the neural frames) is in "cam1_TX39_2019_05_31_1_proc_resampled.npy". A subsampled subset of frames is in "cam1_TX39_20hz.avi".<br>For an example of how to load the data, align it to the image stimuli, compute receptive fields and predict from behavior, see this notebook: https://github.com/MouseLand/rastermap/blob/master/tutorial/tutorial.ipynb

本数据集仓库收录了分布于视觉皮层的18975个神经元在稀疏噪声视觉刺激呈现过程中的神经活动数据。
去卷积数据存储于"spks.npy"文件中。"F.npy"、"Fneu.npy"、"stat.npy"及"ops.npy"的相关说明可参阅suite2p官方文档页面：https://github.com/MouseLand/suite2p/wiki/Outputs
稀疏噪声刺激的帧序列存储于"mov.npy"文件中，各帧的时间戳信息存储于"iframe.npy"文件中。
已与神经成像帧完成对齐的行为数据存储于"cam1_TX39_2019_05_31_1_proc_resampled.npy"文件中；其子采样帧子集存储于"cam1_TX39_20hz.avi"文件中。
若需了解如何加载数据、将其与图像刺激对齐、计算感受野（receptive field）并基于行为数据开展预测的示例，请参阅该Jupyter笔记本：https://github.com/MouseLand/rastermap/blob/master/tutorial/tutorial.ipynb