Neural oscillations in memory strategies

Abstract

We rely on our long-term memory (LTM) system to remember a wide range of information on a daily basis. However, we know from experience, whether forgetting a necessary item on a grocery list or answers to a test question, we are not always able to accurately recall that information. What determines how well information is stored in LTM? One factor is how memory stimuli are encoded. Memory strategies are designed to help counteract failures by providing memory cues to associate with necessary memory stimuli. Past literature has evaluated the effects of strategies on memory accuracy, but less is known about the neural mechanisms underlying such strategies. The current proposal aims to alleviate this gap by using electroencephalography (EEG) while participants completed a modified version of a Paired-Associates Learning task and reported which strategy they used to encode the paired words. Overall, the proposal answered three key research questions: 1) What neural patterns are active in the brain when we experience a memory failure?, 2) Do effective memory strategies differ neurophysiologically from less effective memory strategies?, and 3) Do neural signatures validate strategy reports and memory performance? The current proposal used time-frequency analyses to look at multiple processes occurring in the brain at once. It is proposed that the theta band will help participants actively encode and refresh information in short-term memory (i.e., attention or processing), gamma band will help participants store memory representations (i.e., storage), and alpha will work to suppress irrelevant information during the task. More importantly, the current proposal is interested in how theta and gamma work together to shift information to LTM. We found neural evidence that memory failures exhibit lower theta power and differing gamma power depending on how much information is required to remember (e.g., 3 sets of word pairs vs. 10 sets of word pairs). We also found evidence that effective strategies recruit higher gamma power, which could be related to storing or tying current information in LTM. Lastly, we found that brain patterns based on “effective” and “less effective” behavioral data is hard to dissociate, but we suggest that more information is needed to explore this question. Specifically, the unexpected alpha power enhancement and gamma suppression indicates that there is more to these bands than previously thought. Exploratory analyses also found an increase in beta power for Less Effective – Correct strategies compared to all other conditions. It is possible that beta power could be an internal rehearsal loop for strategy types. Future research is needed to understand what alpha and beta enhancement is doing and replicate the pattern of gamma suppression found in the current study.