Data and code from: Preserved temporal hierarchy but frequency-specific alterations in dynamical regimes of EEG microstate multimers during reversible unconsciousness

Employing a spectral analysis framework based on Chaos Game Representation (CGR), we investigated the higher-order dynamics of EEG microstate sequences across delta, theta, alpha, beta, gamma, and broad frequency bands during reversible unconsciousness (anesthesia and sleep). Robust periodic components consistently emerged within microstate sequences across theta, alpha, beta, and gamma bands, persisting across distinct states of consciousness. Converging evidence from both deconstruction via surrogate data and reconstruction via a hierarchical generative model demonstrates that the multimer structure, along with the conditional duration distribution, constitutes the underlying mechanism of microstate periodicity. Furthermore, we show that temporal smoothing abolishes these intrinsic periodic components. Most notably, during both deep sedation and N3 sleep, the beta band microstate sequence exhibited a consistent increase in peak power and a decrease in center frequency, resulting in hi..., , # Data and Code for: Preserved temporal hierarchy but frequency-specific alterations in dynamical regimes of EEG microstate multimers during reversible unconsciousness

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## 1. General Description

This repository contains the processed EEG microstate sequences, analysis code (MATLAB), and figure generation data associated with the manuscript mentioned above. The study investigates the temporal dynamics of EEG microstates during different states of consciousness using Chaos Game Representation (CGR) and multimer analysis.

The data is organized into three main datasets (Datasets 1, 2, and 3).

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## 2. Folder Structure Overview

The main compressed file `Data_and_codes.zip` contains the following directories:

* **Dataset1/**: Contains microstate sequences (.txt), analysis scripts (.m), and result variables (.mat) for the sedation dataset.
* **Dataset2/**: Contains data and scripts for the sedation dataset.
* **Dataset3/**: Contains data and scripts for the sleep dataset.
* **Figur...,

本研究采用基于混沌游戏表示（Chaos Game Representation, CGR）的频谱分析框架，探究了可逆意识丧失状态（麻醉与睡眠）下，脑电图（Electroencephalogram, EEG）微状态序列在δ、θ、α、β、γ及全频段的高阶动力学特性。在θ、α、β及γ频段的微状态序列中，始终存在稳定的周期性成分，且该成分在不同意识状态下均得以保留。通过替代数据解构与层级生成模型重构得到的一致性证据表明，微状态多聚体结构与条件时长分布共同构成了微状态周期性的底层机制。此外，本研究证实时间平滑操作会消除这些固有的周期性成分。尤为值得注意的是，在深度镇静与N3睡眠阶段，β频段微状态序列均表现出峰值功率持续升高、中心频率持续降低的特征，最终导致……
# 配套数据与代码：可逆意识丧失状态下脑电微状态多聚体动力学系统保留时间层级但呈现频段特异性改变

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## 1. 总体描述
本仓库包含上述论文关联的预处理脑电微状态序列、分析代码（MATLAB）及绘图生成数据。本研究采用混沌游戏表示（CGR）与多聚体分析方法，探究了不同意识状态下脑电微状态的时间动力学特性。
数据集分为三个主要部分（数据集1、数据集2与数据集3）。

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## 2. 文件夹结构概览
主压缩文件`Data_and_codes.zip`包含以下目录：
* **Dataset1/**：包含镇静数据集的微状态序列文件（.txt）、分析脚本（.m）及结果变量文件（.mat）。
* **Dataset2/**：包含镇静数据集的相关数据与脚本。
* **Dataset3/**：包含睡眠数据集的相关数据与脚本。
* **Figur...