认知脑电数据

研究内容：基于本项目所研究的新型认知评估范式，通过多模态同步任务（如EEG（脑电）+fNIRS（近红外脑功能）+眼动+平衡、fNIRS+步态双任务、fNIRS+OT 任务手功能等，其中眼动、平衡、OT 任务手功能为智能传感信息），建立行为特征与神经影像特征的耦合关系；进而优选高敏感性的EEG/fNIRS 通道，构建高准确性的行为学与低通道EEG/fNIRS 的特征组合。在上述优选的基础上，结合认知行为学测试，从感知觉（眼动平衡）检测出发、到执行控制（低通道fNIRS+步态双任务、低通道fNIRS+OT 任务）、记忆与情景（低通道干电极EEG+低通道fNIRS）开展自适应筛查检测，提高筛查的快速性与敏感性。基于大样本数据与深度学习，构建适用于社区的多模态认知障碍筛查模型。针对认知障碍患者在医院的精细分析与康复效果的即时评价的挑战，对照患者/正常人，研究静息态、任务态下的脑活动响应模式，探究认知障碍的神经/血氧响应机制，建立与认知能力相关的EEG/fNIRS 评价指标（包括时空频模式、网络连接等）及确定个体化认知训练靶点。
数据内容：认知脑电数据；数据采集地点：广东省佛山市；数据采集时间：2020.12-2021.1；设备名称：脑电采集设备；运行环境：无；数据类型：文件；预估数据量/记录数：105例；数据格式：DSI

Research Content: Based on the novel cognitive assessment paradigm developed in this project, the coupling relationship between behavioral characteristics and neuroimaging features is established via multimodal synchronous tasks, including: 1) EEG (electroencephalogram) + fNIRS (functional near-infrared spectroscopy) + eye tracking + balance assessment; 2) fNIRS + gait dual-task; 3) fNIRS + OT (occupational therapy) hand function task, where eye tracking, balance assessment and OT hand function task belong to intelligent sensing information. Subsequently, high-sensitivity EEG/fNIRS channels are screened out to construct a feature combination combining high-accuracy behavioral characteristics and low-channel EEG/fNIRS data. On this optimized basis, combined with cognitive behavioral tests, adaptive screening tests are conducted, starting from sensory-perception detection (eye tracking and balance assessment), then moving to executive control (low-channel fNIRS + gait dual-task, low-channel fNIRS + OT task), and finally to memory and episodic cognition (low-channel dry-electrode EEG + low-channel fNIRS), thereby improving the rapidity and sensitivity of screening. Based on large-sample datasets and deep learning, a multimodal cognitive impairment screening model suitable for community scenarios is developed. To address the challenges of precise in-hospital analysis and real-time evaluation of rehabilitation effects for cognitive impairment patients, brain activity response patterns under resting state and task state are studied by comparing with healthy controls, the neural/blood oxygen response mechanisms of cognitive impairment are explored, EEG/fNIRS evaluation indicators related to cognitive ability (including spatiotemporal-frequency patterns, network connections, etc.) are established, and individualized cognitive training targets are determined.

Data Content: Cognitive electroencephalogram data; Data collection location: Foshan City, Guangdong Province, China; Data collection period: December 2020 to January 2021; Equipment name: Electroencephalogram acquisition equipment; Operating environment: None; Data type: File; Estimated data volume/number of records: 105 cases; Data format: DSI

搜集汇总

背景与挑战

背景概述

该数据集是来自国家重点研发计划项目的认知脑电数据，旨在通过多模态同步任务（如EEG、fNIRS、眼动等）研究老年认知障碍的评估与康复，包含105例在广东省佛山市采集的DSI格式数据。数据集聚焦于构建行为与神经影像特征的耦合关系，并开发高敏感性的筛查模型，适用于康复医学和模式识别等学科领域。