Efficient Multi Subject Visual Reconstruction from fMRI Using Aligned Representations
Fuente:
arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866911199153618944 |
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| author | Zangos, Christos Ebadulla, Danish Sprague, Thomas Christopher Singh, Ambuj |
| author_facet | Zangos, Christos Ebadulla, Danish Sprague, Thomas Christopher Singh, Ambuj |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_01670 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Efficient Multi Subject Visual Reconstruction from fMRI Using Aligned Representations Zangos, Christos Ebadulla, Danish Sprague, Thomas Christopher Singh, Ambuj Image and Video Processing Computer Vision and Pattern Recognition Machine Learning 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. |
| title | Efficient Multi Subject Visual Reconstruction from fMRI Using Aligned Representations |
| topic | Image and Video Processing Computer Vision and Pattern Recognition Machine Learning |
| url | https://arxiv.org/abs/2505.01670 |