Cinematic Memories: EEG-Based Decoding of Recall Using Naturalistic Stimuli

Identifying neural correlates of long-term memory retrieval has been an area of considerable research. Previous studies used custom-built, static stimuli to elicit and study memory processes, limiting the insights into brain activity in a natural environment. Instead, we used movie clips to identify neural correlates of memory retrieval. We extracted features from the time-frequency domain from electroencephalography (EEG) signals to classify whether a 10-second-long video clip had been remembered, obtaining greater-than-chance memory decoding (median area under the receiver operating characteristic curve = 0.64) in a naturalistic movie-watching task with greater real-world validity than word-list or image recall paradigms. Feature analysis revealed that remembered clips, compared to not recognised clips, showed increased event-related desynchronisation (ERD) in the theta and low alpha bands early after stimulus onset, followed by stronger ERD in the alpha bands. While beta-band differences were observed at the group level, high within-class variability precluded their use for reliable single-trial classification, with theta and alpha activity emerging as the primary discriminative features. Our ERD/S analysis generalises observations previously demonstrated in the literature using simpler stimuli and more controlled experimental designs. Finally, we observed a significant correlation between classifier performance and retrospective memory ratings of participants (ρ=0.49) demonstrating that individual differences in memory ability are reflected in neural activity patterns. This work demonstrates the potential of naturalistic stimuli to advance memory research using EEG, revealing neural dynamics that may not be detectable with simpler stimuli, with possible implications for the development of clinical tools in memory assessment.