Department of Electrical and Computer Engineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA.
Neuroimage. 2014 Jan 1;84:712-23. doi: 10.1016/j.neuroimage.2013.09.028. Epub 2013 Sep 22.
We show that it is possible to successfully predict subsequent memory performance based on single-trial EEG activity before and during item presentation in the study phase. Two-class classification was conducted to predict subsequently remembered vs. forgotten trials based on subjects' responses in the recognition phase. The overall accuracy across 18 subjects was 59.6% by combining pre- and during-stimulus information. The single-trial classification analysis provides a dimensionality reduction method to project the high-dimensional EEG data onto a discriminative space. These projections revealed novel findings in the pre- and during-stimulus periods related to levels of encoding. It was observed that the pre-stimulus information (specifically oscillatory activity between 25 and 35Hz) -300 to 0ms before stimulus presentation and during-stimulus alpha (7-12Hz) information between 1000 and 1400ms after stimulus onset distinguished between recollection and familiarity while the during-stimulus alpha information and temporal information between 400 and 800ms after stimulus onset mapped these two states to similar values.
我们表明,基于研究阶段中项目呈现前后的单次 EEG 活动,成功预测后续记忆表现是可能的。基于受试者在识别阶段的反应,我们进行了二分类以预测随后记住和忘记的试验。通过结合刺激前和刺激期间的信息,18 名受试者的总体准确率为 59.6%。单次试验分类分析提供了一种降维方法,将高维 EEG 数据投影到一个可区分的空间中。这些投影揭示了与编码水平相关的刺激前和刺激期间的新发现。观察到,刺激前信息(特别是刺激前 25 到 35Hz 之间的振荡活动)-刺激前 300 到 0ms 和刺激期间 alpha(7-12Hz)信息在刺激后 1000 到 1400ms 之间区分了回忆和熟悉度,而刺激期间的 alpha 信息和刺激后 400 到 800ms 之间的时间信息将这两种状态映射到相似的值。