Connectionists: vision: a community-driven replication initiative for image-related neuroscience

[Alessandro Gifford]

Dear colleagues,

We are excited to announce re:vision, a community-driven initiative for
replicating and generalizing findings in image-related neuroscience and
we'd love for you to take part.

Condition-rich fMRI datasets have transformed how we study visual
representations, but they rest on two assumptions: that their stimuli
sample natural images broadly, and that findings generalize across that
distribution. These assumptions are rarely tested directly. re:vision sets
out to change that.

The initiative is built on the new LAION-fMRI dataset: densely-sampled 7T
fMRI responses to 25,000+ natural images, designed to cover the space of
natural images at exceptional scale and diversity. Participants pick a
published finding, replicate it using LAION-fMRI, and test whether it holds
and generalizes. No new data collection is required, all data, preprocessed
betas, and annotations are provided through our Python package.

Anyone with an interest in neuroscience can participate in teams of 1 - 3
researchers. From the PI that wants to get their hands dirty again to the
master's student looking for a thesis project. We advise that at least one
member of your replication team has experience with fMRI analysis.

Why participate?

   -

   Be part of the consortium paper — every team that submits a valid report
   is given the chance to co-author the final publication.
   -

   Compete for cash prizes: a $2,500 Replication Award, a $2,500
   Generalization Award, and a $1,000 Facilitator Award.

Key dates:

   -

   Sign-up & proposal: by September 15th 2026
   -

   Report submission: by February 15th 2027

You can learn more, browse suggested studies, and sign up at
re-vision-initiative.org.

Please feel free to forward this to colleagues or students who might be
interested.

Kind regards
the re:vision team

re:vision team:

Luca Kämmer, Justus-Liebig-University Gießen & Max Planck Institute CBS

Josefine Zerbe, Justus-Liebig-University Gießen & Max Planck Institute CBS

Johannes Roth, Justus-Liebig-University Gießen & Max Planck Institute CBS

Alessandro Gifford, Freie Universität Berlin

Apurva Ratan Murty, Georgia Institute of Technology
Iris Groen, Amsterdam University

Michael Bonner, Johns Hopkins University

Margaret Henderson, Carnegie Mellon University

Radoslaw Cichy, Freie Universität Berlin

Martin Hebart, Justus-Liebig-University Gießen & Max Planck Institute CBS
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