Predicting episodic memory formation for movie events

Tang, Hanlin; Singer, Jed; Ison, Matias J.; Pivazyan, Gnel; Romaine, Melissa; Frias, Rosa; Meller, Elizabeth; Boulin, Adrianna; Carroll, James; Perron, Victoria; Dowcett, Sarah; Arellano, Marlise; Kreiman, Gabriel

Abstract

© The Author(s) 2016. Episodic memories are long lasting and full of detail, yet imperfect and malleable. We quantitatively evaluated recollection of short audiovisual segments from movies as a proxy to real-life memory formation in 161 subjects at 15 minutes up to a year after encoding. Memories were reproducible within and across individuals, showed the typical decay with time elapsed between encoding and testing, were fallible yet accurate, and were insensitive to low-level stimulus manipulations but sensitive to high-level stimulus properties. Remarkably, memorability was also high for single movie frames, even one year post-encoding. To evaluate what determines the efficacy of long-term memory formation, we developed an extensive set of content annotations that included actions, emotional valence, visual cues and auditory cues. These annotations enabled us to document the content properties that showed a stronger correlation with recognition memory and to build a machine-learning computational model that accounted for episodic memory formation in single events for group averages and individual subjects with an accuracy of up to 80%. These results provide initial steps towards the development of a quantitative computational theory capable of explaining the subjective filtering steps that lead to how humans learn and consolidate memories.

Citation

Tang, H., Singer, J., Ison, M. J., Pivazyan, G., Romaine, M., Frias, R., …Kreiman, G. (2016). Predicting episodic memory formation for movie events. Scientific Reports, 6, Article 30175. https://doi.org/10.1038/srep30175

• Journal Article Type: Article
• Acceptance Date: Jun 28, 2016
• Online Publication Date: Sep 30, 2016
• Publication Date: Sep 30, 2016
• Deposit Date: Dec 4, 2018
• Publicly Available Date: Dec 5, 2018
• Journal: Scientific Reports
• Electronic ISSN: 2045-2322
• Publisher: Nature Publishing Group
• Peer Reviewed: Peer Reviewed
• Volume: 6
• Article Number: 30175
• DOI: https://doi.org/10.1038/srep30175
• Public URL: https://nottingham-repository.worktribe.com/output/1051844
• Publisher URL: https://www.nature.com/articles/srep30175
• Contract Date: Dec 4, 2018