arXiv CS
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Latent Prediction Yields Cross-Subject Alignable Representations in Sensory-Evoked fMRI
Decoding sensory-evoked functional magnetic resonance imaging (fMRI) data is a central analytical tool in cognitive neuroscience. Here we ask whether self-supervised learning (SSL), which has been scarcely explored in this domain, can yield representations that support strong downstream performance.
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