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Do Vision Model See Like the Brain? A Comparison Across EEG Encoding Model
Convolutional neural networks (CNNs) and vision transformers are both used to model the human visual system, but whether the two architectures diverge at a specific point in network depth is unclear. We compared six CNNs and two vision transformers by computing the Pearson correlation (r) between each model's predicted and measured EEG response at every layer or block, in ten participants viewing 200 natural images. For the transformer models, we also tested four token representations, from the classification (CLS) token alone to CLS combined with all patch tokens. CNNs showed strongest corres
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-22T14:41:31.000Z
First collected: 2026-09-23T04:11:12.117Z. This is not the publication date.