Efficient Multi Subject Visual Reconstruction from fMRI Using Aligned Representations

Christos Zangos; Danish Ebadulla; Thomas Christopher Sprague; Ambuj Singh

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arXiv · 2505.01670

Efficient Multi Subject Visual Reconstruction from fMRI Using Aligned Representations

Christos Zangos·Danish Ebadulla·Thomas Christopher Sprague·Ambuj Singh

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Abstract

This work introduces a novel approach to fMRI-based visual image reconstruction using a subject-agnostic common representation space. We show that the brain signals of the subjects can be aligned in this common space during training to form a semantically aligned common brain. This is leveraged to demonstrate that aligning subject-specific lightweight modules to a reference subject is significantly more efficient than traditional end-to-end training methods. Our approach excels in low-data scenarios. We evaluate our methods on different datasets, demonstrating that the common space is subject and dataset-agnostic.

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BibTeX RIS

Christos Zangos, Danish Ebadulla, Thomas Christopher Sprague, Ambuj Singh. 2025-05-03. Efficient Multi Subject Visual Reconstruction from fMRI Using Aligned Representations. https://arxiv.org/abs/2505.01670

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