Technical Program

Paper Detail

Paper: PS-1B.63
Session: Poster Session 1B
Location: H Fläche 1.OG
Session Time: Saturday, September 14, 16:30 - 19:30
Presentation Time:Saturday, September 14, 16:30 - 19:30
Presentation: Poster
Publication: 2019 Conference on Cognitive Computational Neuroscience, 13-16 September 2019, Berlin, Germany
Paper Title: Narratives as Networks: Predicting Memory from the Structure of Naturalistic Events
Manuscript:  Click here to view manuscript
License: Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 Unported License.
Authors: Hongmi Lee, Janice Chen, Johns Hopkins University, United States
Abstract: A naturalistic spoken recall paradigm with fMRI was used to investigate how the structure of a complex realistic experience affects memory. Subjects watched short movie clips and then verbally recalled the movie details aloud while being scanned. To quantify the structure of the movies, we transformed each movie plot into a network, where nodes are individual movie events and the connections between them are determined by content similarity. Inter-event similarity was computed by correlating high-dimensional sentence embeddings derived from human-generated text descriptions of the movie events. Behavioral results showed that the centrality of events within the network (i.e., the overall number and strength of connections with other events) positively predicted recall performance. Higher centrality also predicted stronger univariate activation and the reactivation of event-specific multi-voxel patterns during recall in the posterior medial cortex, a brain area thought to represent abstract ‘situation models.’ Representational similarity analysis revealed that the neural pattern similarity structure of default network areas during recall reflected the text-based narrative network structure. Our study introduces a novel approach to quantify the structure of complex narratives and demonstrates that inter-event structure predicts behavioral and neural markers of memory under naturalistic conditions.