Advancing Brain-to-Image Decoding: Deep Learning Insights

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This presentation outlines the project on 'Natural Image Reconstruction' which focuses on reconstructing images from fMRI signals. Key objectives include addressing challenges in voxel signal mapping and overcoming dataset constraints. The methodology involves brain encoders, generative models, and hierarchical brain-region modeling, utilizing the Horikawa17 dataset spanning seven visual regions. Expected outcomes aim to reduce signal-to-image translation gaps, enhance reconstruction details,...