View, engage, predict: enhancing brain-behavior mapping with naturalistic movie-watching fMRI

Yunrui Zhang, Emily S. Finn, Mert R. Sabuncu, Amy Kuceyeski

bioRxiv DOI:10.1101/2025.07.28.666907 Under review. 2025

How does the human brain respond while watching movies, and what can this reveal about individual traits? In this work, we show that certain movie clips can predict cognitive scores and sex from fMRI functional connectivity more effectively than five times as much resting-state data. For cognition prediction, a movie clip’s predictive power is strongly linked to how well it synchronizes brain activity across people and to the amount of social and human-related content. These effects were not observed for sex prediction.

[Code] [Paper]

A (k,t)-RAKI Method for Interpolating Sparse Data in Accelerated MRSI Acquisitions

Yunrui Zhang, Ruiyang Zhao, Zepeng Wang

International Society of Magnetic Resonance in Medicine (ISMRM) 2024 Power Pitch

In this work, we adapted and extended the self-supervised learning-based RAKI method by incorporating the FID dimension into a 3D, complex-valued convolutional network, for MRSI reconstruction. We improved the design by training a single network to handle multi-coil data simultaneously instead of the coil-by-coil interpolation in the original RAKI method. We demonstrate reduced aliasing by the proposed method and consequently improved spatiospectral processing results, using in vivo 1H-MRSI data.

[Code] [Paper]