Beyond Differences: Cross-Subject and Cross-Dataset fMRI Brain Decoding of visual stimuli

Motivation: Brain decoding has been limited by the need for large data amounts and subject-specific methodologies. Current techniques require extensive scanning, which is costly and time-consuming, restricting their applicability. Goal(s): The study aims to establish a novel, more efficient approach for cross-subject brain decoding of visual stimuli. Approach: Using the NSD we applied regularized ridge regression to align brain activity across different subjects on common stimuli representations, employing the state-of-the art Brain-Diffuser pipeline for decoding and image reconstruction. Results: The ridge regression alignment method surpassed others, enabling consistent cross-subject decoding with significantly reduced data—demonstrating feasibility and a potential 90% scan time reduction. Impact: A reliable technique for cross-subject, -scanner and -field strength alignment can pave the way for efficient brain decoding without the need for extensive data collection and/or ultra-high field strengths.