A Scaling Study for fMRI Foundation Models
cs.LG
Submitted: 2026-09-23
Updated: 2026-09-23
Terminology
Sources
- Scaling Vision Transformers for Functional MRI with Flat Maps
- Scaling Data-Constrained Language Models
- LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics
- Brain Harmony: A Multimodal Foundation Model Unifying Morphology and Function into 1D Tokens
- Training Compute-Optimal Large Language Models
- Scaling Laws for Neural Language Models
- SLIM-Brain: A Data- and Training-Efficient Foundation Model for fMRI Data Analysis
- FlexiBrain: Resolution-Agnostic Voxel-Level Encoding for Native fMRI
- Omni-fMRI: A Universal Atlas-Free fMRI Foundation Model
- A Brain Graph Foundation Model: Pre-Training and Prompt-Tuning across Broad Atlases and Disorders
- Brain-DiT: A Universal Multi-state fMRI Foundation Model with Metadata-Conditioned Pretraining
- BrainWorld: A Structural-Prior-Conditioned Generative Model for Whole-Brain 4D fMRI Dynamics
- BrainMass: Advancing Brain Network Analysis for Diagnosis with Large-scale Self-Supervised Learning
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