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

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Connor Lane, Gregory Kiar

Published: 03 Aug 2023, Last Modified: 01 Sept 2025OpenReview Archive Direct UploadEveryoneCC BY 4.0
Abstract: This is the Algonauts 2023 submission report for team "BlobGPT". Our model consists of a multi-subject linear encoding head attached to a pretrained trunk model. The multi-subject head consists of three components: (1) a shared multi-layer feature projection, (2) shared plus subject-specific low-dimension linear transformations, and (3) a shared PCA fMRI embedding. In this report, we explain these components in more detail and present some experimental results. Our code is available at this https URL.