DINA is a dual-tower contrastive model that aligns images with mouse V1 neural activity to enable decoding and shows that low-level visual structure, not semantics or fine details, primarily supports the alignment.
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Interpreting V1 Population Activity via Image-Neural Latent Representation Alignment
DINA is a dual-tower contrastive model that aligns images with mouse V1 neural activity to enable decoding and shows that low-level visual structure, not semantics or fine details, primarily supports the alignment.