EEG Dataset for natural image recognition through Visual Stimuli

Electroencephalography (EEG) is a technique for measuring the electrical activity of the brain in the form of action potentials using electrodes placed on the scalp. The technique is gaining popularity for research investigations due to its non-invasive nature and ease of application. EEG exposes a wide range of human brain potentials, including event-related, sensory, and visually evoked potentials (VEPs), and helps to build complex applications. The current dataset consists of thirty-two subjects' EEG recordings in response to visual stimuli (VEPs). The purpose of collecting such data is because of its contribution in the advancement of visual decoding and supporting EEG-based image classification and reconstruction. The primary goal is to investigate the cognitive mechanisms behind known and unknown perceptions. The dataset was collected using a standardised experimental setup that included several experimental phases to capture the essence of the experiment. Thirty-five adult participants participated in the data collection process. They had no visual impairment and took the Vividness of Visual Imagery Questionnaire (VVIQ) test to answer sixteen questions based on their memory and imagination. Out of the thirty-five participants, thirty-two cleared the test and their EEG were recorded. The data was collected using a 14-channel EPOC X – 14 EEG device. The recordings were sampled at 128 Hz, and the 10 – 20 system was followed for electrode placement. EMOTIVPro software was used for collection and annotation. The brain activity signals were collected while the participants were viewing an image displayed on a white screen. The image consists of natural objects like apple (class A), flower (class F), car (class C) and human face (class P). The file “VVIQuestionnaire.pdf” is the questionnaire used to ascertain the visual imagination of the participants. The other file “Participant_info.csv” contains the details of the participants (age, gender, image class viewed, and Participant ID) and their VVIQ score. The names of the participants have been purposely removed for reasons of anonymity and a unique participant ID has been assigned to each participant. These IDs are further used to represent the EEG of the participants. Each class folder further contains two subfolders: A1, A2 (for class A); C1, C2 (for class C); P1, P2 (for class P); and F1, F2 (for class F). All these folders contain the data acquired from the different participants who were shown these images as a csv and edf file. This file structure makes data easier to access and analyse based on the class of visual stimuli images and experimental design employed.脑电图（Electroencephalography, EEG）是一种通过放置于头皮的电极，以动作电位形式采集大脑电活动的技术。该技术因具备非侵入性、操作简便的特性，正日益受到科研领域的广泛关注。脑电图可采集涵盖事件相关电位、感觉诱发电位以及视觉诱发电位（Visual Evoked Potentials, VEPs）在内的多种人脑电活动信号，可用于构建复杂应用场景。 本数据集包含32名受试者在接受视觉刺激（视觉诱发电位）时的脑电记录。收集此类数据的核心目的在于推动视觉解码技术的发展，并为基于脑电的图像分类与重建研究提供支撑。本数据集的研究目标为探究已知与未知感知背后的认知机制。 本次数据采集采用标准化实验范式，包含多轮实验环节以完整捕获实验核心内容。实验共招募35名成年受试者，所有受试者均无视觉障碍，并需完成《视觉表象鲜明度问卷》（Vividness of Visual Imagery Questionnaire, VVIQ），该问卷包含16道基于个人记忆与想象的题目。35名受试者中共有32名通过该问卷测试，其脑电数据被正式采集。 数据采集使用14通道EPOC X–14脑电设备，采样率设置为128 Hz，电极放置遵循国际10–20系统标准。数据的采集与标注工作通过EMOTIVPro软件完成。 受试者在观看白色屏幕上呈现的图像时，同步采集其脑电活动信号。实验图像包含四类自然物体：苹果（类别A）、花朵（类别F）、汽车（类别C）与人脸（类别P）。 文件"VVIQuestionnaire.pdf"为用于评估受试者视觉表象能力的问卷原文。文件"Participant_info.csv"则包含受试者的详细信息：年龄、性别、所观看的图像类别、受试者编号，以及其VVIQ得分。为保障受试者匿名性，所有参与者的真实姓名均已移除，每位受试者被分配唯一编号，该编号用于对应其脑电数据。 每个类别文件夹下均包含两个子文件夹：A1、A2对应类别A；C1、C2对应类别C；P1、P2对应类别P；F1、F2对应类别F。所有子文件夹中均存储了对应受试者的脑电数据，格式为CSV与EDF文件。该文件结构可基于视觉刺激图像类别与所采用的实验设计，大幅提升数据的访问与分析效率。