Do our findings replicate?
A replication initiative for image-related neuroscience
Do our findings replicate?
A replication initiative for image-related neuroscience
Recent advances based on condition-rich neuroimaging datasets have transformed our understanding of how the brain represents the visual world. Re:Vision asks how robust these findings are across datasets, image distributions, and methods for testing generalization. To address this, we use the new LAION-fMRI dataset, designed to sample the space of natural images at exceptional scale and diversity.
Condition-rich fMRI datasets have opened powerful new ways to study visual representations, but each dataset samples only part of the visual world. Do our findings replicate, and do they generalize to the natural image distribution?
Our main goal is to test the robustness of findings from image-related neuroscience. Do they replicate on a broader fMRI dataset?
Our second goal is to specifically test which of these findings generalize to the full image distribution of LAION-fMRI and remain robust across image distributions.
Contains fMRI responses to images from LAION-natural, NSD/MSCOCO (natural scenes), THINGS (object images), and out-of-distribution images. The CLIP embedding space highlights the coverage of LAION-fMRI across these image types.
the effective dimensionality of NSD or THINGS in CLIP embedding space, which measures how many independent axes of variation a stimulus set covers.
LAION-fMRI contains densely-sampled 7T fMRI data with >30 image-viewing sessions, extensive retinotopy, resting-state, and diffusion imaging.
Browse the responses voxel-by-voxel in our interactive 3D brain explorer. Pick any subject and ROI, rotate the cortical surface, and see which stimuli drove each voxel most strongly.
Open the brain explorer
laion-fmri.hebartlab.com/brain
Best viewed on a larger screen
Embedded preview · rotate, pan, and inspect ROIs directly
Open in new tabAwarded to the team that demonstrates the most rigorous and well-executed replication of a published finding.
Awarded to the team that provides the most compelling evidence for (or against) generalization using the LAION-fMRI dataset.
Awarded to original authors of replicated papers that best cooperate with and support the replication team.
These cash prizes will be awarded by the re:vision board after the final submission of the report. They will be split between the members of the winning team.
The winners of the prizes are chosen based on how rigorous the submission was and how well it was presented in the report. They are independent of whether the replication / generalization was successful.
Submit proposal
Submit a short proposal on how to replicate / generalize the study you signed up for.
Due September 15th 2026
Conduct replication
Replicate the main findings using LAION-fMRI. You will not have to collect any data.
Submit report
Submit a report on your replication.
Due February 15th 2027
You will be given the chance to be part of the consortium paper and win one of our prizes.
Initiative kickoff at our VSS satellite + dataset release. Includes a 3.5-hour hands-on session with Q&A and dataset tutorials.
Deadline for participants to sign up and submit a short proposal.
Deadline for participants to submit the report on their replication attempt.
1st and only round of reviews from the re:vision board.
Deadline for the final revised reports.
The organizers and board will synthesize the reports we receive to write a summary paper. Every participant that submitted a valid report will be given the chance to be on the paper.
Practical details on how to participate in our initiative. If your question is not covered, you can contact us via the e-mail address below.
Anyone with an interest in imaging neuroscience. We advise that at least one member of your replication team has experience with fMRI analysis.
No. All fMRI data, preprocessed betas, retinotopic maps, and image annotations are provided through our Python package. You may need to generate some metadata (e.g., using an AI model) depending on the study you replicate.
The initiative board evaluates reports for methodological clarity and rigor of replication. All valid replications will be included in the final summary paper, irrespective of the result of the replication.
Any published result generated with a condition-rich dataset. We provide a list with suggested studies but you are welcome to choose a different study as long as at least some of its main findings are in principle replicable using LAION-fMRI.
You cannot replicate your own findings, but if you have a result you would like to see replicated we are happy to connect you with someone to conduct the replication.
Teams that submit a valid replication are invited to join the re:vision consortium and will be given the chance to be authors on the final paper. They will also have a chance to win one of the prizes.
Yes, we allow up to 2 replication attempts of the same study. So sign up quickly if you have a specific study in mind that you would like to replicate. If you sign up for a study, we will reserve it for you for 4 weeks so you have time to write your proposal.
We allow 1-3 researchers to conduct a replication together. All team members will be given the chance to be part of the final paper if the team submits a valid replication to the board. Additionally, you can contact the original authors of the paper to ask for help with specific methods or code.
Contact the original authors for advice on how they generated this data. In many cases models can generate a wide variety of metadata. Contact us if you have specific questions.
All teams that submit a valid replication report will be given the chance to join the re:vision consortium and be listed as co-authors on the final summary paper once they have signed off the paper's content. This applies to every team member (up to 3 people per team).
Negative results are equally valuable and will be included in the consortium paper. The goal of this initiative is to get an honest picture of which findings hold and which do not.
Yes. The initiative is open to anyone with the relevant expertise, regardless of institutional affiliation. We only ask that at least one team member has experience with fMRI data analysis.
We support open science practices. Teams are strongly encouraged to share their analysis code (e.g., on GitHub) as part of their final report. Code does not have to be pretty as long as it works. The fMRI dataset itself is already publicly available through our Python package.
Yes. The suggested list covers the most widely-cited studies in the field, but you may choose a different published study as long as its main findings are in principle replicable using the LAION-fMRI dataset.
Yes — re:vision (often written without the colon as the revision initiative or revision challenge) is a community replication initiative for visual neuroscience, built on the LAION-fMRI dataset. The colon in "re:vision" is purely stylistic and the two names refer to the same project.
Organized by researchers at the Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig and the Justus-Liebig-University, Giessen, Germany.
Expert reviewers who will evaluate submissions and provide feedback on replication reports.
For inquiries, contact us at re-vision-initiative@uni-giessen.de
If you wish to stay updated on the re:vision initiative, join our mailing list,
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