Single-Trial EEG Connectivity of Default Mode Network Before and During Encoding Predicts Subsequent Memory Outcome - Kim, Dahye; Jeong, Woorim; Kim, June Sic; Chung, Chun Kee (Frontiers in Systems Neuroscience, 2020)
The successful memory process produces specific activity in the brain network. Since the brain activity of the pre-stimulus and encoding phases has a crucial effect on subsequent memory outcomes (e.g., remembered or forgotten), previous studies have tried to predict the memory performance in this period. Conventional studies have used the spectral power or event-related potential of specific regions as the classification feature. However, since multiple brain regions work collaboratively to process memory, it could be a better option to use functional connectivity within the memory-related brain network to predict subsequent memory performance. In this study, we acquired the EEG signals while performing an associative memory task that remembers scene–word pairs. For the connectivity analysis, we estimated the cross mutual information within the default mode network with the time–frequency spectra at the pre-stimulus and encoding phases. Then, we predicted the success or failure of subsequent memory outcome with the connectivity features. We found that the classifier with support vector machine achieved the highest classification accuracy of (80.83 ± 12.65) % (mean ± standard deviation) using the beta (13 – 30) Hz connectivity at encoding phase among the multiple frequency bands and task phases. Using the pre-stimulus beta connectivity, it also achieved the classification accuracy of (72.45 ± 12.52) %. Among the features, the connectivity related to the dorsomedial prefrontal cortex was found to contribute to successful memory encoding. The connectivity related to the posterior cingulate cortex was found to contribute to the failure of memory encoding. The present study showed for the first time the successful prediction with high accuracy of subsequent memory outcome using single-trial functional connectivity.