SLIM-Brain: Efficient fMRI Foundation Model
Published:Dec 26, 2025 06:10
•1 min read
•ArXiv
Analysis
This paper introduces SLIM-Brain, a novel foundation model for fMRI analysis designed to address the data and training inefficiency challenges of existing methods. It achieves state-of-the-art performance on various benchmarks while significantly reducing computational requirements and memory usage compared to traditional voxel-level approaches. The two-stage adaptive design, incorporating a temporal extractor and a 4D hierarchical encoder, is key to its efficiency.
Key Takeaways
- •SLIM-Brain is a new foundation model for fMRI analysis.
- •It addresses data and training inefficiency.
- •It uses a two-stage adaptive design.
- •It achieves state-of-the-art performance.
- •It requires less computational resources than traditional methods.
Reference
“SLIM-Brain establishes new state-of-the-art performance on diverse tasks, while requiring only 4 thousand pre-training sessions and approximately 30% of GPU memory comparing to traditional voxel-level methods.”