AUTHOR=Jun Soyeon , Kim June Sic , Chung Chun Kee 

TITLE=Prediction of Successful Memory Encoding Based on Lateral Temporal Cortical Gamma Power

JOURNAL=Frontiers in Neuroscience

VOLUME=Volume 15 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2021.517316

DOI=10.3389/fnins.2021.517316

ISSN=1662-453X

ABSTRACT=Prediction of successful memory encoding is important for learning. High frequency activity (HFA) such as gamma frequency activity (30-150 Hz) of the cortical oscillations, is induced during memory tasks and is thought to reflect underlying neuronal processes. While previous studies have shown medio-temporal electrophysiological characteristics are related to memory formation, the effect of neocortical neural activity has been little explored. Here, the main aim of the present study was to evaluate whether the gamma activity in human electrocorticography (ECoG) signal can differentiate memory process into remembered from forgotten as a predication marker. To this end, we employed a support vector machine (SVM). ECoG recordings were collected from six subjects during performance of verbal memory recognition tasks. Two-class classification using a support vector machine was performed to predict subsequently remembered vs. forgotten trials based on individually selected frequencies (low gamma; 30 ~60 Hz, high gamma; 60 ~ 150 Hz) of time points of pre- and during- stimulus intervals. The SVM classifier distinguished memory performance between remembered vs. forgotten trials with a mean maximum accuracy of 87.5% using temporal cortical gamma activity during interval (0 ~ 1 sec). Our results confirm the functional relevance of ECoG for memory formations and suggest the lateral temporal cortical HFA could be utilized for feature as memory prediction.