Department of Artificial Intelligence, Korea University, Seoul, Republic of Korea.
Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea.
PLoS One. 2022 Sep 8;17(9):e0274101. doi: 10.1371/journal.pone.0274101. eCollection 2022.
Many studies have focused on understanding memory processes due to their importance in daily life. Differences in timing and power spectra of brain signals during encoding task have been linked to later remembered items and were recently used to predict memory retrieval performance. However, accuracies remain low when using non-invasive methods for acquiring brain signals, mainly due to the low spatial resolution. This study investigates the prediction of successful retrieval using estimated source activity corresponding either to cortical or subcortical structures through source localization. Electroencephalogram (EEG) signals were recorded while participants performed a declarative memory task. Frequency-time analysis was performed using signals from encoding and retrieval tasks to confirm the importance of neural oscillations and their relationship with later remembered and forgotten items. Significant differences in the power spectra between later remembered and forgotten items were found before and during the presentation of the stimulus in the encoding task. Source activity estimation revealed differences in the beta band power over the medial parietal and medial prefrontal areas prior to the presentation of the stimulus, and over the cuneus and lingual areas during the presentation of the stimulus. Additionally, there were significant differences during the stimuli presentation during the retrieval task. Prediction of later remembered items was performed using surface potentials and estimated source activity. The results showed that source localization increases classification performance compared to the one using surface potentials. These findings support the importance of incorporating spatial features of neural activity to improve the prediction of memory retrieval.
许多研究都集中在理解记忆过程上，因为它们在日常生活中非常重要。在编码任务中，大脑信号的时间和功率谱差异与之后被记住的项目有关，并且最近被用于预测记忆检索性能。然而，使用非侵入性方法获取大脑信号时，准确性仍然较低，主要是由于空间分辨率较低。本研究通过源定位，使用对应于皮质或皮质下结构的估计源活动来研究成功检索的预测。参与者在执行陈述性记忆任务时记录脑电图（EEG）信号。使用编码和检索任务的信号进行频时分析，以确认神经振荡的重要性及其与之后记住和忘记的项目的关系。在编码任务中，在呈现刺激之前和期间，在后来记住的项目和忘记的项目之间发现了功率谱的显著差异。源活动估计显示，在呈现刺激之前，在中顶叶和中前额叶区域，以及在呈现刺激期间，在楔前叶和舌状叶区域，β波段功率存在差异。此外，在检索任务的刺激呈现期间也存在显著差异。使用表面电位和估计的源活动来预测之后记住的项目。结果表明，与使用表面电位相比，源定位提高了分类性能。这些发现支持了将神经活动的空间特征纳入其中以提高记忆检索预测的重要性。
