A view-engage-predict framework for enhancing brain-behavior mapping with naturalistic movie-watching fMRI
Yunrui Zhang, Emily S Finn, Mert R Sabuncu, Amy Kuceyeski · 2026
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Description
Yunrui Zhang and colleagues built a deep-learning model that predicts thinking scores and sex from brain scans taken while people watch movies. Most brain-behaviour mapping uses resting brain scans, but movie-watching scans may map the brain better. Their 2026 framework, called view-engage-predict, used both still and sliding-window brain-connection patterns from movie viewing.
Movie scans beat resting scans even against five times more resting data, with sense and higher-order brain networks mattering most. Higher thinking-score accuracy tracked with stronger brain sync across viewers and longer stretches of faces and voices on screen, effects absent for sex prediction. The authors present movie watching as a strong tool for probing how brains differ.
Catalog record
| CREATOR | Yunrui Zhang, Emily S Finn, Mert R Sabuncu, Amy Kuceyeski |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 86 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |