Apache-2.0（仅限代码仓库中的源代码）Apache-2.0 (the repository’s source code only)
权重许可
尚未厘清：无法从检查点的托管记录中读到它自己的许可与条款，代码仓库的代码许可也不能证明它涵盖权重unresolved: the checkpoint’s own licence and terms could not be read from its hosting record, and the repository’s code licence is not evidence that it covers the weights
权重
不分发任何原始或转换后的权重；哈希只用于标识所用的检查点，不授予任何权利no original or converted weights are distributed; the hashes identify the checkpoint used and grant nothing
权利审查
依据所有者的决定发布，只发布聚合结果，与那项试点比较相同。检查点的许可无法读到；没有找到发布者禁止发布独立计算的聚合结果的规定；不分发任何原始或转换后的权重。Published by the owner’s decision, aggregate results only, as the pilot comparison is. The checkpoint’s licence could not be read; no publisher prohibition on independently computed aggregate results was found; no original or converted weights are distributed.
输入
已发布的 250 Hz 微伏时间窗，重采样到 256 Hz 并除以 1,000（换算为毫伏）；只用实际记录的通道，每个通道对应它自己的通道 token（T3、T4、T5、T6 分别按 T7、T8、P7、P8 命名）；不做插值、填充、补零通道或平均参考the published 250 Hz microvolt windows, resampled to 256 Hz and divided by 1,000 (millivolts); only the recorded channels, each as its channel token (T3, T4, T5 and T6 named T7, T8, P7 and P8); no interpolation, padding, zero-filled channels or average reference
池化
四个汇总 token 在各时间片段上取平均后拼接：每个时间窗 2,048 个值the four summary tokens averaged over time patches and concatenated: 2,048 values per window
各行脚注
每个核心时间窗都比 EEGPT 预训练用的 4 秒时间窗短：1 秒或 2 秒，睡眠则是十五段各 2 秒的数据。无论时间窗多长，编码器对每个 0.25 秒片段的计算方式都相同；时间窗越短，可供平均的片段越少。Every core window is shorter than EEGPT’s 4-second pretraining window: 1 or 2 seconds, and sleep as fifteen 2-second segments. The encoder computes each 0.25-second patch the same way at any length; a shorter window gives fewer patches to average.读出用的是本站固定的分类头，接在冻结的汇总 token 上，与已发布的 LaBraM、CBraMod 各行相同：在 2,048 个池化值上做岭回归（alpha 100），空闲协议上则是逐人的逻辑回归分类头。它不是作者在下游任务中用的分类头（可学习的空间滤波器加线性分类头）；输入的时间窗也没有做 EEGPT 预训练时用的平均参考。The readout is the site’s fixed probe on the frozen summary tokens, as for the published LaBraM and CBraMod rows: ridge (alpha 100) on 2,048 pooled values, and on idle a per-person logistic head. It is not the authors’ downstream probe, a learnable spatial filter with a linear head, and the windows are fed without the average reference EEGPT was pretrained with.
预训练语料： 五个公开数据集，按论文表 1 所列：PhysioMI（PhysioNet 运动想象与运动执行数据）、HGD、TSU（清华大学 40 目标 SSVEP 基准数据集）、SEED 与 M3CV；58 个电极、256 Hz、毫伏、平均参考、4 秒时间窗。Five public datasets, as the paper’s Table 1 lists them: PhysioMI (PhysioNet motor imagery and execution), HGD, TSU (the Tsinghua 40-target SSVEP benchmark), SEED and M3CV; 58 electrodes, 256 Hz, millivolts, average reference, 4-second windows.
核查说明： 背景：BETA 不在 EEGPT 作者公开的预训练数据清单中，但清华大学的 40 目标 SSVEP 基准数据集（Wang 等，2017）在清单中，名为 TSU。BETA 的作者把 BETA 描述为该基准的扩展：出自同一团队，采用相同的 40 目标布局，记录是它自己的；两者是否有共同的被试，作者没有说明。For context: BETA is not in EEGPT’s published pretraining list, but the Tsinghua 40-target SSVEP benchmark (Wang et al., 2017) is, as TSU. BETA’s authors describe BETA as an extension of that benchmark, from the same group with the same 40-target layout and its own recordings; whether anyone took part in both is not stated.
BCI Report