We present Alljoined1, a dataset built specifically for EEG-to-Image decoding. Recognizing that an extensive and unbiased sampling of neural responses to visual stimuli is crucial for image reconstruction efforts, we collected data from 8 participants looking at 10,000 natural images each. We have currently gathered 46,080 epochs of brain responses recorded with a 64-channel EEG headset. The dataset combines response-based stimulus timing, repetition between blocks and sessions, and diverse image classes with the goal of improving signal quality. For transparency, we also provide data quality scores. We publicly release the dataset and all code at https://linktr.ee/alljoined1.

翻译：我们提出了Alljoined1数据集，该数据集专为脑电解码图像任务构建。考虑到对视觉刺激的神经响应进行广泛且无偏采样对于图像重建工作至关重要，我们收集了8名受试者各观察10000张自然图像时的数据。目前，我们已采集到46080个时段的64通道脑电头部响应数据。该数据集结合了基于响应的刺激时序、跨模块与跨会话的重复呈现以及多样化的图像类别，旨在提升信号质量。为保障透明度，我们还提供了数据质量评分。我们已公开发布该数据集及所有代码，访问地址为https://linktr.ee/alljoined1。