Cortico-hippocampal networks carry information about characters and their relationships in an extended narrative

Neuropsychologia. 2023 Dec 15:191:108729. doi: 10.1016/j.neuropsychologia.2023.108729. Epub 2023 Nov 10.

Abstract

Social information is a centerpiece of human experience. Despite a wealth of research into the way we understand social relationships and how aspects of social life might be supported by the brain, relatively little is known about how the brain represents individual people and their relationships with others. How do intrinsic networks in the brain track people and their connections in complex situations? Here, we sought to understand this issue using an open neuroimaging dataset in which people freely viewed "The Grand Budapest Hotel." Using support vector machine classification of fMRI activity patterns, we found that character identity could be decoded throughout subsystems of the brain's "Default Mode" Network, especially in regions of an Anterior Temporal and a Medial Prefrontal subsystem, as well as a Medial Temporal Network (MTN). We tested character relationships in two ways - onscreen co-occurrence and shared semantic information from an independent sample of character descriptions - and found evidence for these representations throughout the "Default Mode" Network, and the MTN. The extent to which each variant of character relationships fit neural patterns differed across networks, with abstract semantic relatedness being especially prominent in regions of Anterior Temporal and Medial Prefrontal Networks. These data show that subsystems of the brain's "Default Mode" Network and MTN carry information about individual people as well as their connections, and highlight a particularly strong role for the Anterior Temporal network in representing this information.

Keywords: Anterior temporal; Default mode network; Multivariate decoding; Naturalistic neuroimaging; Posterior medial.

MeSH terms

  • Brain Mapping*
  • Brain*
  • Hippocampus / diagnostic imaging
  • Humans
  • Magnetic Resonance Imaging
  • Neuroimaging