RSVP reading of book chapter in MEG

Subjects read Chapter 9 of Harry Potter and the Sorcerer's Stone one word at a time while their activity was recorded using an Elekta MEG scanner. Words were presented for 0.5 seconds each. The Carnegie Mellon University and the University of Pittsburgh Institutional Review Boards have approved and overseen this study. This study was performed by Tom Mitchell's lab at Carnegie Mellon University. To access this data, please fill the following form, we will contact you shortly with more information: <strong>https://forms.gle/9pjRk6B7aw79w2xs6</strong> <br> This data was used in the following publications: Wehbe, L., Vaswani, A., Knight, K., &amp; Mitchell, T. (2014, October). Aligning context-based statistical models of language with brain activity during reading. In <em>Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)</em> (pp. 233-243). Toneva, M., &amp; Wehbe, L. (2019). Interpreting and improving natural-language processing (in machines) with natural language-processing (in the brain). <em>Advances in Neural Information Processing Systems</em>, <em>32</em>. Schwartz, D., Toneva, M., &amp; Wehbe, L. (2019). Inducing brain-relevant bias in natural language processing models. <em>Advances in neural information processing systems</em>, <em>32</em>. Toneva, M., Mitchell, T. M., &amp; Wehbe, L. (2022). Combining computational controls with natural text reveals new aspects of meaning composition. <em>BioRxiv</em>, 2020-09. The files shared here include a time array indicating the timing of each column of data, and a label array indicating the order of each word in the stimulus text. To access the full MEG data, please fill the form above.

受试者逐词阅读《哈利·波特与魔法石》（*Harry Potter and the Sorcerer's Stone*）第九章，同时使用Elekta脑磁图（MEG）扫描仪记录其脑活动。每个单词的呈现时长为0.5秒。本研究已获得卡内基梅隆大学（Carnegie Mellon University）与匹兹堡大学（University of Pittsburgh）机构审查委员会（Institutional Review Boards）的批准与监管。本研究由卡内基梅隆大学汤姆·米切尔（Tom Mitchell）实验室完成。若需获取该数据集，请填写以下表单，我们将尽快与您联系以提供更多信息：<strong>https://forms.gle/9pjRk6B7aw79w2xs6</strong> <br> 本数据集已应用于以下发表成果：Wehbe, L., Vaswani, A., Knight, K., & Mitchell, T. (2014年10月). 将基于语境的语言统计模型与阅读过程中的脑活动进行对齐. 见《2014年自然语言处理经验方法会议（EMNLP）论文集》(pp. 233-243). Toneva, M., & Wehbe, L. (2019). 利用大脑中的自然语言处理过程解读并改进机器自然语言处理模型. 《神经信息处理系统进展》, 第32卷. Schwartz, D., Toneva, M., & Wehbe, L. (2019). 在自然语言处理模型中引入与大脑相关的偏差. 《神经信息处理系统进展》, 第32卷. Toneva, M., Mitchell, T. M., & Wehbe, L. (2022). 结合计算控制与自然文本揭示意义构建的新维度. 《BioRxiv》, 2020-09. 本次共享的文件包含用于标注各数据列时序的时间数组，以及用于指示刺激文本中单词顺序的标签数组。若需获取完整的脑磁图数据，请填写上述表单。