Your Emotions, My Brain: Generalizable Neural Signatures of Emotional Memory Reactivation During Sleep

Abstract

Reactivation in sleep alters the structure of memories and can potentially be used to restructure upsetting representations. Reactivation can be triggered with auditory cues and then detected using machine learning and electroencephalography (EEG), but can we also detect the emotionality of reactivated memories? We examined this by presenting auditory cues that had been associated with negative or neutral stimuli in wake during subsequent NREM sleep and training a classifier to detect the emotionality of subsequent EEG responses. We were able to detect the reinstatement of emotionality 0.4-0.6 seconds after cue presentation. Importantly, we used a between-participant machine learning pipeline to identify shared neural signatures of emotionality across individuals without fine-tuning the model on testing participants. This approach eliminates the need for individualized wake localizer sessions, establishing a methodologically efficient framework for investigating emotional processing during sleep. Detection of emotional reactivation in sleep will help us to understand how such reactivation impacts upon the emotionality of the memories in the long term, potentially facilitating development of treatments for PTSD and depression through memory restructuring in sleep.