Multivariate classification of multichannel long-term electrophysiology data identifies different sleep stages in fruit flies, Part 14 of 16

Sleep is observed in most animals, which suggests it subserves a fundamental process associated with adaptive biological functions. However, the evidence to directly associate sleep with a specific function is lacking, in part because sleep is not a single process in many animals. In humans and other mammals, different sleep stages have traditionally been identified using electroencephalograms (EEGs), but such an approach is not feasible in different animals such as insects. Here, we perform long-term multichannel local field potential (LFP) recordings in the brains of behaving flies undergoing spontaneous sleep bouts. We developed protocols to allow for consistent spatial recordings of LFPs across multiple flies, allowing us to compare the LFP activity across awake and sleep periods and further compare the same to induced sleep. Using machine learning, we uncover the existence of distinct temporal stages of sleep and explore the associated spatial and spectral features across the fly b..., , , ## Data from: Multivariate classification of multichannel long-term electrophysiology data identifies different sleep stages in fruit flies, Part 14 of 16

## Description of the data and file structure

This is a part of the multi-part dataset containing local field potential (lfp) recordings and video data of 16 `Drosophila melanogaster` flies.
This part contains data from `19_22012019_SponSleep_LFP`

## Dataset contents

Each dataset (after collation for individual fly using software below) consists of a specific spontaneous sleep recording for each fly. For e.g. 19_22012019_SponSleep_LFP contains lfp and video recorded from a particular drosophila on 22-01-2019. Within each folder there are two subfolders.

* lfp: contains two further subfolders:
* folder ending with `_Calib` contains lfp data recorded when calibration (electrode insertion) was performed as a single block.
* folder ending with `_LFP` contains lfp data of the full recording, either as a single block or...

睡眠现象广泛存在于绝大多数动物类群中，这提示睡眠承担着与适应性生物学功能相关的核心生理过程。然而，目前仍缺乏将睡眠与特定功能直接关联的实验证据，部分原因在于许多动物的睡眠并非单一均质的过程。传统上，人类与其他哺乳动物的睡眠分期可通过脑电图（electroencephalogram, EEG）进行识别，但该方法在昆虫等其他动物中并不可行。
本研究对处于自发睡眠周期的自由活动果蝇的脑部进行了长期多通道局部场电位（local field potential, LFP）记录。我们开发了可在多只果蝇间实现一致空间布局的LFP记录方案，得以比较清醒与睡眠状态下的LFP活动，并进一步将其与诱导睡眠状态进行对比。通过机器学习方法，我们发现果蝇存在不同的睡眠时间分期，并探究了与之相关的空间与频谱特征……
数据来源：《多通道长期电生理数据的多变量分类识别果蝇睡眠分期》，第14/16部分

数据与文件结构说明
本数据集为多部分合集的一部分，包含16只黑腹果蝇（Drosophila melanogaster）的局部场电位记录与视频数据。本部分数据对应`19_22012019_SponSleep_LFP`样本。

数据集内容
经下述软件整理后，针对单只果蝇的数据集包含该个体的特定自发睡眠记录。例如，`19_22012019_SponSleep_LFP`包含2019年1月22日采集自某只果蝇的LFP与视频数据。每个数据集文件夹下包含两个子文件夹：
* lfp：包含两个下级子文件夹：
* 以`_Calib`结尾的文件夹：存储电极校准（电极植入）阶段采集的单次块LFP数据。
* 以`_LFP`结尾的文件夹：存储完整记录的LFP数据，可分为单次块或……