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视觉皮层（visual cortex）内18975个神经元在接收稀疏噪声视觉刺激时的神经活动数据。
反卷积处理后的神经活动数据存储于"spks.npy"文件中。"F.npy"、"Fneu.npy"、"stat.npy"及"ops.npy"的详细说明可参考suite2p官方输出文档页面：https://github.com/MouseLand/suite2p/wiki/Outputs
稀疏噪声视觉刺激的帧序列存储于"mov.npy"文件内，各帧的时间戳信息则存储于"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"文件内。该数据集的经下采样处理的帧子集视频存储于"cam1_TX39_20hz.avi"文件中。
若需了解如何加载数据、将其与视觉刺激帧对齐、计算神经元感受野（receptive field）以及基于行为数据进行预测的示例代码，可参考该Jupyter Notebook：https://github.com/MouseLand/rastermap/blob/master/tutorial/tutorial.ipynb