Abstract
The successful memory process produces specific activity in the brain network. As the brain activity of the prestimulus 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, as 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 prestimulus 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 prestimulus beta connectivity, the classification accuracy of 72.45% ± 12.52% is also achieved. 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.
Highlights
Differences in brain activity between the subsequently remembered and forgotten trials at learning are often referred to as subsequent memory effects (SMEs) (Paller and Wagner, 2002; Klimesch, 2012)
The present study showed that subsequent memory outcome can be successfully predicted using the functional connectivity within default mode network (DMN) regions
Successful memory encoding is related to the medial temporal lobe and prefrontal cortex (Wagner et al, 1998; Paller and Wagner, 2002; Reber et al, 2002; Kim, 2011), whereas the failure of memory encoding is related to posterior cingulate cortex (PCC) and temporoparietal junction (Otten and Rugg, 2001; Kim, 2011)
Summary
Differences in brain activity between the subsequently remembered and forgotten trials at learning are often referred to as subsequent memory effects (SMEs) (Paller and Wagner, 2002; Klimesch, 2012). In addition to SMEs during the encoding phase, previous studies showed that prestimulus activities could predict subsequent memory outcome, as anticipatory activity prior to stimulus presentation could play a critical role in how a stimulus will be processed (Otten et al, 2006; Guderian et al, 2009; Addante et al, 2011, 2015; Burke et al, 2014; Cohen et al, 2015; Schneider and Rose, 2016) In this regard, there have been studies that predicted subsequent memory outcome (e.g., remembered or forgotten) using single-trial EEG SMEs features of prestimulus, and during the encoding phase. As the brain works collaboratively to process memory, other than features of local signal amplitude, a better option to predict subsequent memory outcome could be to use the functional connectivity between multiple brain regions
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