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This is the Algonauts 2023 submission report for team "BlobGPT". Our modelconsists of a multi-subject linear encoding head attached to a pretrained trunkmodel. The multi-subject head consists of three components: (1) a sharedmulti-layer feature projection, (2) shared plus subject-specific low-dimensionlinear transformations, and (3) a shared PCA fMRI embedding. In this report, weexplain these components in more detail and present some experimental results.Our code is available at https://github.com/cmi-dair/algonauts23.

A Parameter-efficient Multi-subject Model for Predicting fMRI Activity