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Alljoined1，一个专为脑电图到图像解码构建的数据集。鉴于对视觉刺激的神经响应进行全面无偏采样对图像重建工作至关重要，我们收集了8名参与者各观看10,000幅自然图像的实验数据。目前已采集到46,080个时段的脑电响应数据，采用64通道脑电帽进行记录。该数据集融合了基于响应的刺激时序、模块间与实验间重复以及多样化图像类别，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。我们通过https://linktr.ee/alljoined1 公开释放该数据集及全部代码。